[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|phone” _builder_version=”4.16″ min_height=”549px” custom_padding=”|150px|108px|150px|false|true” custom_padding_tablet=”|50px||50px|false|true” custom_padding_phone=”|20px||20px|false|true” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ background_color=”#f1f1f1″ border_width_all=”6px” border_color_all=”#122f47″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ text_font=”|600|||||||” text_text_color=”#122f47″ text_font_size=”38px” text_line_height=”1.4em” text_orientation=”center” global_colors_info=”{}”]<\/p>\n
Numpy Mastery is a step-by-step course that will enable you to memorize Numpy syntax, and wrangle your numeric data with ease.<\/p>\n
[\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2020\/02\/blue-key-image.png” align=”center” _builder_version=”4.16″ width=”22%” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ background_color=”#e8e8e8″ custom_padding=”|100px|40px|100px||” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ text_font=”Georgia||||||||” text_font_size=”50px” text_orientation=”center” text_font_size_tablet=”” text_font_size_phone=”40px” text_font_size_last_edited=”on|phone” text_text_align=”center” global_colors_info=”{}”]<\/p>\n
“Learning this way is almost addictive!”<\/p>\n
[\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” text_orientation=”right” text_text_align=”right” global_colors_info=”{}”]<\/p>\n
\u2013 Victor O., Sharp Sight student<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.16″ custom_padding=”26px|158px|60px|148px|false|false” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”0|20px||20px|false|false” locked=”off” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_margin=”32px|auto||auto||” custom_padding=”0|50px|40px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”40px” text_letter_spacing=”1px” text_line_height=”1.1em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”38px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”22px” header_2_font_size_phone=”17px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n
In Numpy Mastery, you’ll learn essential data manipulation skills, systematically<\/h2>\n
[\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”||0px|||” global_colors_info=”{}”]<\/p>\n
Numpy Mastery will teach you the essential skills of data manipulation using the Numpy package.<\/p>\n
But the course is highly structured.<\/em><\/p>\n You’ll learn Numpy tools in a way that’s efficient, effective, and fast.<\/p>\n To do this, the course is divided up into several different modules:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”50px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 1, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy Basics<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In module 1, you’ll learn the essential foundations of Numpy.<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-basics_laptop-video-example_v2.png” alt=”An image of a laptop with a video showing Numpy Basics.” title_text=”numpy-basics_laptop-video-example_v2″ align=”center” _builder_version=”4.16″ max_width=”80%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you\u2019ll learn:<\/p>\n If you’re a true beginner to Numpy, these topics will be explained in a clear, easy to understand manner.<\/p>\n And if you have some experience with Numpy, you’ll solidify your knowledge and learn how to think about some Numpy topics that commonly trip people up.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”52px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 2, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Essential Array Creation Techniques<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n After learning about Numpy basics, you’ll learn two of the most important ways to create Numpy arrays.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”3_5,2_5″ custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_margin=”|20px||20px|false|true” custom_padding=”0px|3px|4px|3px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”3_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-linspace_laptop-video-example.png” alt=”An image that shows a laptop with a video explaining the syntax of Numpy Linspace” title_text=”numpy-linspace_laptop-video-example” _builder_version=”4.16″ max_width=”90%” module_alignment=”center” custom_padding=”5px|||||” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”|||-22px||” custom_padding=”|0px||||” global_colors_info=”{}”]<\/p>\n <\/p>\n <\/p>\n <\/p>\n You’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”40px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Again, everything will be explained in a clear, straightforward manner that makes it easy for you to understand.<\/p>\n And you’ll get practice exercises that will help you systematically practice, memorize, and master these array creation techniques.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”65px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 3, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n How to Rearrange Numpy Arrays<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”||0px|||” global_colors_info=”{}”]<\/p>\n In this module, you’ll learn how to rearrange existing Numpy arrays into new shapes and forms.<\/p>\n <\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-sort_laptop-video-example.png” alt=”An image of a laptop, showing a video that’s explaining how Numpy Sort works.” title_text=”numpy-sort_laptop-video-example” _builder_version=”4.16″ max_width=”80%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”65px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 4, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy Zeros, Ones, Empty, and Full<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”||0px|||” global_colors_info=”{}”]<\/p>\n In this module, you’ll learn how to create numpy arrays that contain all 1s, all 0s, or other types of highly specific values.<\/p>\n <\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-zeros_laptop-video-example.png” alt=”An image of a laptop, with some code explaining the Numpy Zeros function.” title_text=”numpy-zeros_laptop-video-example” _builder_version=”4.16″ max_width=”80%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”65px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 5, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy “Random” Functions<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”||0px|||” global_colors_info=”{}”]<\/p>\n In this module, you’ll learn how to create numpy arrays that contain different types of randomly generated numbers, or numbers drawn from probability distributions.<\/p>\n <\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-random-normal_laptop-video-example.png” alt=”An image of a laptop explaining the syntax of Numpy Random Normal.” title_text=”numpy-random-normal_laptop-video-example” _builder_version=”4.16″ max_width=”80%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”54px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 6, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n How to Combine Numpy Arrays<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”2_5,3_5″ custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”2px|50px|1px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”2_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”40px|||||” global_colors_info=”{}”]<\/p>\n In this module, you’ll learn several techniques for combining multiple Numpy arrays..<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”3_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-concatonate_laptop-video-example.png” alt=”An image of a laptop showing an example of Numpy concatenate.” title_text=”numpy-concatonate_laptop-video-example” _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”19px|100px|5px|100px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In these lessons, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”52px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 7, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n How to “Split” Arrays<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”3_5,2_5″ custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_margin=”|20px||20px|false|true” custom_padding=”0px|3px|4px|3px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”3_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-vsplit_laptop-video-example.png” alt=”An image of a laptop, showing an example of how to use Numpy Vsplit.” title_text=”numpy-vsplit_laptop-video-example” _builder_version=”4.16″ max_width=”90%” module_alignment=”center” custom_padding=”5px|||||” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”80px|0px||||” global_colors_info=”{}”]<\/p>\n Here, you’ll learn to split arrays into multiple pieces.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”19px|100px|5px|100px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In these lessons, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”54px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 8, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy Statistical Functions<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In these lessons, you’ll learn tools for computing statistics based on your Numpy data.<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-sum_laptop-video-example.png” alt=”An image of a laptop, showing an example of how to use Numpy Sum.” title_text=”numpy-sum_laptop-video-example” align=”center” _builder_version=”4.16″ max_width=”75%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”19px|100px|5px|100px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”54px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 9, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy Math Functions<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In the math module, you’ll learn tools for performing mathematical computations on your Numpy arrays.<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-power_laptop-video-example.png” alt=”An image of a laptop showing how to use the Numpy Power function.” title_text=”numpy-power_laptop-video-example” align=”center” _builder_version=”4.16″ max_width=”75%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”54px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Module 10, you’ll learn:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n “Miscellaneous” Numpy Functions<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In the final module, you’ll learn how to use a few “miscellaneous” Numpy functions.<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2022\/03\/numpy-where_laptop-video-example.png” alt=”An image of a laptop, showing an example of Numpy Where.” title_text=”numpy-where_laptop-video-example” align=”center” _builder_version=”4.16″ max_width=”75%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”19px|100px|5px|100px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you’ll learn:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ custom_margin=”0px|0px|0px|0px” custom_padding=”0|0|0px|0px|false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ width=”100%” max_width=”100%” custom_margin=”0px|0px|0px|0px” custom_padding=”0|0px|0px|0px|false|false” use_custom_width=”on” width_unit=”off” custom_width_percent=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”0px|0px|0px|0px” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2019\/04\/cube-pixel-row.png” show_bottom_space=”off” align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” _builder_version=”4.16″ custom_margin=”|0px||0px” custom_padding=”|0px||0px” custom_css_main_element=”width: 100vw;” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.16″ custom_padding=”26px|158px|60px|148px|false|false” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”0|20px||20px|false|false” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_margin=”32px|auto||auto||” custom_padding=”0|50px|40px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”Montserrat||||||||” text_font_size=”20px” text_letter_spacing=”1px” text_line_height=”1em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”38px” custom_margin=”5px||5px||false|false” custom_padding=”0px||0px” header_2_font_size_tablet=”22px” header_2_font_size_phone=”17px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Discover our system to help you…<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” locked=”off” global_colors_info=”{}”]<\/p>\n Become Fluent in Numpy<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”||0px|||” global_colors_info=”{}”]<\/p>\n Numpy Mastery is designed to enable you to master numeric data manipulation within only a few weeks.<\/p>\n Here’s how …<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”50px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Numpy mastery, you’ll:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Learn all of the [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n In Numpy Mastery, you’ll learn all of the critical tools of numeric data manipulation with Numpy. <\/p>\n You’ll learn everything you need to know to create, aggregate, compute, and reshape your numeric data.<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2020\/06\/numpy-axes_laptop-video-image.png” title_text=”numpy-axes_laptop-video-image” align=”center” _builder_version=”4.16″ max_width=”80%” module_alignment=”center” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Specifically, you\u2019ll learn:<\/p>\n If you’re a true beginner to Numpy, these topics will be explained in a clear, easy to understand manner, so everything will make perfect sense.<\/p>\n (People who have read our tutorials at the Sharp Sight blog know that crystal clear explanation is how we do things…)<\/p>\n But even if you have a little experience with Numpy, you’ll discover a training system that will enable you to memorize and master all of these foundational techniques.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.22.1″ custom_margin=”30px||||false|false” custom_padding=”0|49px|40px|49px|false|true” custom_padding_tablet=”|20px||20px||true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Numpy Mastery, you’ll discover our …<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Ultra Efficient Practice System<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n When you join Numpy Mastery, you’ll discover our unique practice system<\/strong> that will help you become “fluent” in critical Numpy syntax.<\/p>\n This training system will enable you to quickly master the syntax for cleaning, modifying, aggregating, and reshaping your numeric data.<\/p>\n By mastering the essential syntax, you\u2019ll build the foundation for writing more complicated pieces of data wrangling code.<\/p>\n The simple syntax that you learn will become the \u201cbuilding blocks\u201d for more complex data manipulation.<\/p>\n It\u2019s like learning a foreign language. First, you need to master essential vocabulary. But after that, you can start putting that vocabulary together in more complex ways. If you practice diligently, you\u2019ll become \u201cfluent\u201d in that language. You\u2019ll be able to speak fluidly and rapidly.<\/p>\n It’s the same thing with learning a toolkit like Numpy.\u00a0 You have to learn the “vocabulary” and then you move on to building things that are more complex.<\/p>\n Numpy Mastery will show you exactly how to become “fluent” in Numpy via deliberate practice.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”52px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n In Numpy Mastery, you’ll discover how to:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Memorize<\/em> [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n A critical part of helping you become “fluent” is helping you memorize all of the syntax that you’ve learned.<\/p>\n Have you ever sat down to write some code, only to find that you’ve forgotten the syntax?<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”3_5,2_5″ custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_margin=”|20px||20px|false|true” custom_padding=”0px|3px|4px|3px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”3_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2020\/06\/remember-numpy-forever_laptop-video-example.png” alt=”An image of a laptop, which is playing a video that explains the Numpy Mastery memorization system.” title_text=”remember-numpy-forever_laptop-video-example” _builder_version=”4.16″ max_width=”90%” module_alignment=”center” custom_padding=”5px|||||” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_5″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”40px|0px|||false|false” global_colors_info=”{}”]<\/p>\n Numpy Mastery solves this, because the practice system you’ll use in the course is based on deep insights from psychology and neuroscience …<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”40px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_padding=”|0px||||” global_colors_info=”{}”]<\/p>\n And it essentially enables you to “hack” your memory so that you learn Numpy syntax, and remember it forever.<\/p>\n So if you’ve ever been a cut-and-paste coder ….<\/p>\n Then looking up syntax on Google or Stack Overflow will be a thing of the past.<\/p>\n If you practice like we show you, you’ll know all of the critical Numpy syntax, from memory, permanently.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”65px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n If you practice consistently with our training system, you’ll …<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” 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_builder_version=”4.16″ custom_padding=”54px|50px|23px|50px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_font_size=”20px” min_height=”45px” custom_margin=”||4px|||” custom_padding=”||13px|||” global_colors_info=”{}”]<\/p>\n Ultimately, we want to help you …<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”Montserrat|700|||||||” text_font_size=”46px” text_line_height=”1.4em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” custom_margin=”5px||15px||false” custom_padding=”0px||0px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Become 10x more productive<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”19px|100px|5px|100px|false|true” custom_padding_tablet=”5px|20px||20px|false|true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Ultimately, this course will skyrocket your productivity with Numpy.<\/p>\n If you struggle to wrangle your numeric data …<\/p>\n If you constantly have to stop your work to look up syntax …<\/p>\n If you keep getting stuck with your Python data science projects, and you feel like your productivity could be so much better …<\/p>\n Then this is the course you’ve been looking for.<\/p>\n Looking up syntax will be a thing of the past, because you’ll memorize everything you learn (we’ll show you how).<\/p>\n You’ll be able to confidently write your code, because you’ll know how to use all of the essential tools.<\/p>\n And you’ll dramatically increase your productivity …<\/p>\n Because once you know the syntax, and once you know how to use it, productivity is the natural outcome.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|phone” _builder_version=”4.16″ background_color=”#007fe0″ custom_padding=”|100px|40px|100px||” custom_padding_tablet=”” custom_padding_phone=”|20px||20px” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ custom_padding=”1px||0px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ text_font=”Georgia||||||||” text_text_color=”#ffffff” text_font_size=”48px” text_line_height=”1.1em” text_orientation=”center” text_font_size_tablet=”” text_font_size_phone=”30px” text_font_size_last_edited=”on|desktop” text_text_align=”center” global_colors_info=”{}”]<\/p>\n “Your practice method is simply effective beyond words”<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”|300|||||||” text_text_color=”#ffffff” text_font_size=”20px” header_font=”||||||||” text_orientation=”right” text_text_align=”right” global_colors_info=”{}”]<\/p>\n \u2013 Joshua F., Sharp Sight student<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|phone” _builder_version=”4.16″ custom_padding=”|150px||150px||” custom_padding_tablet=”” custom_padding_phone=”|20px||20px” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”30px|49px|40px|49px|false|true” custom_padding_tablet=”|20px||20px||true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”||||||||” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”39px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n \u00a0I get it …<\/p>\n You’re probably skeptical.<\/p>\n Mastering Numpy in a few weeks sounds too good to be true.<\/p>\n But it IS possible.\u00a0<\/p>\n You can become “fluent” in Numpy and master data manipulation skills in only a few weeks.<\/p>\n Our past students have had amazing results.<\/p>\n Here’s what our past students have had to say about our courses and training methodology:<\/p>\n <\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Edwin W.” job_title=”Founder, dataisliteracy.org” portrait_url=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2019\/03\/edwin-w-dataisliteracy.jpg” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n “I enrolled in your data science program this past year \u2026. It\u2019s amazing!<\/p>\n Having taught for 20 years, you have one of best approaches I\u2019ve seen to teaching.”<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Vasily M.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cI want to say thank you for the quality of the course.<\/p>\n The concepts are combined very well with this course. It\u2019s great.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=” Alexandre F.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cThe course is amazing.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Sharon P.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cYou deliver excellent information, parsed into just the right units, and provide an awesome way to practice and internalize the material.<\/p>\n \u2026 the course is delivering on all the promises, and it\u2019s improving my understanding of everything.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Paolo C.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cBeing able to write down key code snippets without looking up anywhere else is so useful.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Ganapathy G.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cThe course is very good.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Joshua F.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cI\u2019m really enjoying the lectures, coding walkthroughs, and practice.<\/p>\n They\u2019ve been tremendously helpful and I can really see my fluency developing.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Corey H.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cI have been practicing almost every day and find that it really helped me memorize all the syntax.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Michael G.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cI feel much more comfortable and proficient after going through the videos and practicing.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”41px|0px|0px|0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_testimonial author=”Joshua F.” portrait_url=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iNTAwIiBoZWlnaHQ9IjUwMCIgdmlld0JveD0iMCAwIDUwMCA1MDAiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CiAgICA8ZyBmaWxsPSJub25lIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiPgogICAgICAgIDxwYXRoIGZpbGw9IiNFQkVCRUIiIGQ9Ik0wIDBoNTAwdjUwMEgweiIvPgogICAgICAgIDxyZWN0IGZpbGwtb3BhY2l0eT0iLjEiIGZpbGw9IiMwMDAiIHg9IjY4IiB5PSIzMDUiIHdpZHRoPSIzNjQiIGhlaWdodD0iNTY4IiByeD0iMTgyIi8+CiAgICAgICAgPGNpcmNsZSBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBjeD0iMjQ5IiBjeT0iMTcyIiByPSIxMDAiLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n \u201cYour DSSR method is simply effective beyond words.\u201d<\/p>\n [\/et_pb_testimonial][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”64px||104px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_divider show_divider=”off” _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.16″ background_color=”#f4f4f4″ custom_padding=”|150px||150px” custom_padding_tablet=”” custom_padding_phone=”|20px||20px” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ background_color=”#ffffff” custom_margin=”|auto|122px|auto||” custom_padding=”30px|80px|40px|80px|false|true” custom_padding_tablet=”|20px||20px||true” custom_padding_phone=”18px|0px||0px|false|false” border_width_all=”3px” border_color_all=”#7c7c7c” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”||||||||” text_font_size=”44px” text_line_height=”1.2em” header_font=”||||||||” header_font_size=”26px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” text_orientation=”center” text_font_size_tablet=”” text_font_size_phone=”32px” text_font_size_last_edited=”on|phone” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” text_text_align=”center” global_colors_info=”{}”]<\/p>\n When you join Numpy Mastery<\/strong>, you’ll get everything you need to master Numpy extremely fast:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”30px|49px|40px|49px|false|true” custom_padding_tablet=”|20px||20px||true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|600|||||||” text_font_size=”45px” text_line_height=”1.2em” header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Numpy Mastery [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”||35px|||” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ text_font=”|600|||||||” text_font_size=”28px” text_line_height=”1.5em” custom_margin=”||51px|||” custom_padding=”50px|40px||35px||” global_colors_info=”{}”]<\/p>\n No matter what stage you’re at in your data science training, if you answered “yes” to even ONE of of the questions above, you should join Numpy Mastery, RIGHT NOW.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” text_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n BUT!<\/p>\n If you’re looking for a course that will magically turn you into a data unicorn without any effort at all, then don’t join.<\/p>\n If you’re out of cash and really can’t afford the course, don’t join.<\/p>\n Numpy Mastery is a step-by-step system that will enable you to rapidly master numeric data manipulation in Python …<\/p>\n IF you do the work.<\/p>\n You must be willing to put in some effort in order to get the results.<\/p>\n If you’re willing to do that, then Numpy Mastery can help you master data wrangling with Numpy within weeks<\/span>.<\/em> [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.16″ custom_padding=”43px|158px|0.8px|148px|false|false” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_accordion open_toggle_text_color=”#000000″ open_toggle_background_color=”#f2f2f2″ closed_toggle_background_color=”#f2f2f2″ icon_color=”#a3a3a3″ use_icon_font_size=”on” icon_font_size=”33px” _builder_version=”4.17.4″ toggle_text_color=”#000000″ toggle_font=”||||||||” toggle_font_size=”26px” closed_toggle_font=”||||||||” closed_toggle_font_size=”20px” body_font=”||||||||” body_font_size=”20px” background_color=”rgba(0,0,0,0)” global_colors_info=”{}”][et_pb_accordion_item title=”Do I need to know Python?” open=”on” _builder_version=”4.16″ global_colors_info=”{}”]<\/p>\n Yeah, you should to know at least some of the basics.<\/p>\n For example, you’ll need to have a solid understanding of Python data types (particularly numeric data types).<\/p>\n You should also be comfortable typing in code into an IDE.<\/p>\n But as long as you know most of the essentials of “base Python”, Numpy Mastery will teach you everything you need to know about Numpy.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”How does the course work?” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n Numpy Mastery is an online video course.<\/p>\n After purchasing the course, you\u2019ll get access to a member area, where you will find video lectures, code, practice exercises.<\/p>\n The first week, you’ll get access to some setup lessons to help you get set up for the course. The first week will also include some basic material and orientation for the course.<\/p>\n Then, every week, new lessons will be released over the course of about 8 weeks. <\/p>\n The video lessons are available 24 hours per day, and you can watch the lessons at your own pace.<\/p>\n So the course is very \u201cflexible\u201d \u2026 you can review the material when you want. Moreover, you can study wherever you want: your home office, your couch, or anywhere is convenient for you.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cIs this course live?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n This is not a live course. <\/p>\n This is an online video course that you can take at your own pace. You will have access to the course 24 hours a day by logging into the member area. <\/p>\n This makes the course very flexible \u2026 you can watch the videos and practice whenever is convenient for you.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cWhat if I live in India, or China, or Europe?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n You can take this course from anywhere in the world.<\/p>\n This course is 100% online, so you can take it from anywhere, at your own pace.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cHow long do I have access?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n This is an online course, so you have 24\/7 access. <\/p>\n You\u2019ll also have permanent access, so you can return to the material as often as you like (even next year).<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”%22Can I use a different programming language?%22″ _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n No.<\/p>\n This course only uses the Python programming language. There are other good data science programming languages (like R), but this course exclusively uses Python.<\/p>\n If you want to learn how to do data science or data manipulation with R, you should enroll in one of our R-based courses.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Does this course teach Pandas or other data science topics?” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n No, this course only teaches Numpy.<\/p>\n If you want to master Pandas, we have a separate course called Pandas Mastery that will help you rapidly master the Pandas package.<\/p>\n We also have a comprehensive course that teaches data science in Python called Python Data Mastery.<\/p>\n Python Data Mastery teaches Numpy, Pandas, Matplotlib, Seaborn, and more.<\/p>\n If you take Numpy Mastery, you can always upgrade to Python Data Mastery later, for a special upgrade price<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cWill this prepare me to learn machine learning later on?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n Yes.<\/p>\n Although Numpy Mastery does not teach machine learning, it has been specifically structured to prepare you to learn machine learning in the future. <\/p>\n Many machine learning algorithms require numeric data as inputs. In Python (and specifically, Sci-kit Learn), that often means that you need to use Numpy arrays as inputs.<\/p>\n In particular, techniques like Deep Learning, image recognition, and computer vision use Numpy heavily.<\/p>\n If you want to do machine learning in Python, you should almost certainly master Numpy.<\/p>\n This course will help you do that.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cDo I need to know calculus or advanced math?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n No.<\/p>\n Numpy Mastery avoids math topics completely. <\/p>\n A lot of data science \u201cadvice\u201d will tell you that you need to know advanced math to learn data science. This is a huge myth.<\/p>\n Most working data scientists (working in business and industry) do not use math on a daily basis.<\/p>\n Instead, most people who work in the data industry use data wrangling techniques almost every day. <\/p>\n If you want to be a great data scientist, you need to know and master data manipulation. This course will teach you how to wrangle your numeric data in Python.<\/p>\n So, don\u2019t worry if you don\u2019t know calculus or linear algebra. You won\u2019t need it.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cHow much work do I need to put in to the course?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n A couple hours per week.<\/p>\n Every week, a new module will open. Most modules have 3 to 5 lessons, and each lesson has 1 or two videos. <\/p>\n You should be able to watch all of the videos in a module in 60 to 90 minutes.<\/p>\n Most of the modules also have practice exercises. We recommend that you practice with these practice exercises every day for 15 to 20 minutes.<\/p>\n You can adjust your practice level as needed, so if you only have 10 minutes a day, you can do that. <\/p>\n If you study and practice like we show you, you should be able to master Pandas techniques within 4 to 6 weeks. <\/p>\n (If you have less time to put in, it may take longer to get results.)<\/p>\n In any case, between the videos and practice exercises, you should expect the course to take a couple of hours per week.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cWhy are there monthly payments?\u201d” _builder_version=”4.16″ global_colors_info=”{}” open=”off”]<\/p>\n There are two payment options: you can pay in full with a one-time payment OR you can pay in monthly installments.<\/p>\n We created the monthly payment plan to make the course more affordable to people.<\/p>\n If you choose to pay in installments, you will make an installment payment every month for 12 months. By selecting this payment plan, you are committing to 12 complete payments \u2026 that\u2019s the cost of the course.<\/p>\n Keep in mind that if you choose to pay the full cost of the course immediately with a one-time payment, you will get a discount compared to the payment plan option.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”\u201cHow long does the course last? How many lessons?\u201d” _builder_version=”4.17.4″ global_colors_info=”{}” open=”off”]<\/p>\n There are 8 modules, and each module has several lessons and exercises.<\/p>\n When you join, you\u2019ll get access to an introductory “setup” module, and you’ll get access to the first content module soon after. After that, new modules open every week. You\u2019ll see all of the material within about 4 weeks.<\/p>\n But, there are exercises to help you master the syntax. These exercises will help you memorize the syntax.<\/p>\n To really get results, you should practice for a few weeks afterwards. If you practice regularly, as the course recommends, then you should start to see your “fluency” with the techniques develop within a 4 to 6 weeks. If you continue to practice, your fluency will continue to develop beyond that … but only if you practice!<\/p>\n [\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”132px||130px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_divider color=”#6c2be9″ divider_weight=”4px” _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ background_color=”#ececec” border_width_all=”4px” border_color_all=”rgba(0,0,0,0)” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”|600|||||||” text_font_size=”62px” text_line_height=”1.2em” header_font=”Montserrat||||||||” header_2_font=”Montserrat||||||||” header_2_font_size=”46px” text_font_size_tablet=”44px” text_font_size_phone=”28px” text_font_size_last_edited=”on|desktop” global_colors_info=”{}”]<\/p>\n Try the course [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2019\/03\/30-day_riskfree_guarantee.png” align=”center” align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” custom_margin=”|40px|40px|40px” text_font_size_tablet=”28px” text_font_size_phone=”22px” text_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Try the course.<\/p>\n If you\u2019re not completely satisfied with your progress, let me know within 30 days and I\u2019ll refund all of your money, no questions asked.<\/p>\n This is entirely RISK FREE for you. You\u2019ll get to try out the best resource for learning critical data science skills and if you\u2019re not completely satisfied, I\u2019ll refund your money.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ custom_padding=”||0px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_divider show_divider=”off” _builder_version=”4.16″ height=”70px” global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.19.0″ custom_padding=”7px|64px|49.75px|64px|false|true” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” locked=”off” global_colors_info=”{}”][et_pb_row _builder_version=”4.22.1″ max_width=”980px” custom_padding=”0px||0px||true|false” box_shadow_style=”preset2″ box_shadow_horizontal=”-10px” box_shadow_vertical=”10px” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.0″ background_color=”#efefef” custom_padding=”|0px||0px|false|true” global_colors_info=”{}”][et_pb_text _builder_version=”4.22.1″ text_font=”|600|||||||” text_font_size=”52px” text_line_height=”1.2em” text_orientation=”center” custom_margin=”10px||0px||false|false” custom_padding=”0px||0px||false|false” text_font_size_tablet=”38px” text_font_size_phone=”28px” text_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n Yes! I want lifetime access [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font_size=”22px” text_orientation=”center” custom_margin=”20px|75px|20px|75px|false|true” global_colors_info=”{}”]<\/p>\n When you join, you’ll get lifetime access to the Numpy Mastery course, including videos, code, practice exercises, and all future updates.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”|700|||||||” text_font_size=”26px” header_3_text_align=”center” text_orientation=”center” min_height=”6px” custom_margin=”0px||10px||false|false” custom_padding=”0px||0px||true|false” global_colors_info=”{}”]<\/p>\n 5 monthly payments of:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font_size=”33px” header_line_height=”0em” header_2_text_align=”center” header_2_font_size=”78px” min_height=”95px” custom_margin=”0px||10px||false|false” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_button button_url=”https:\/\/sharpsight.teachable.com\/purchase?product_id=5288461″ button_text=”Join Now” button_alignment=”center” _builder_version=”4.23.4″ custom_button=”on” button_text_size=”42px” button_bg_color=”#e59900″ button_border_width=”0px” button_border_color=”#d6d6d6″ button_border_radius=”0px” button_letter_spacing=”0px” button_font=”||||||||” button_use_icon=”off” background_layout=”dark” custom_margin=”0px||20px||false|false” custom_margin_tablet=”” custom_margin_phone=”|5px||5px” custom_margin_last_edited=”on|phone” custom_padding=”||||false|false” custom_padding_tablet=”” custom_padding_phone=”|5px||5px” custom_padding_last_edited=”on|desktop” button_text_size_tablet=”30px” button_text_size_phone=”25px” button_text_size_last_edited=”on|desktop” global_colors_info=”{}” button_text_size__hover_enabled=”on|hover” button_bg_color__hover_enabled=”on|hover” button_bg_color__hover=”#e2aa00″ button_border_width__hover_enabled=”on” button_border_width__hover=”0px” 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[\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Data manipulation is a huge part of data science.<\/p>\n On any given project, somewhere around 80% of your work will be data wrangling …<\/p>\n … getting data<\/p>\n … cleaning data<\/p>\n … reshaping data<\/p>\n … aggregating data<\/p>\n The rumors you hear really are true: data manipulation is typically the majority of any data science project.<\/p>\n If that’s the case, doesn’t it make sense to spend a disproportionate amount of time learning data manipulation?<\/p>\n Doesn’t it make a lot<\/em> of sense to master the skill that makes up 80% of the work?<\/p>\n Doesn’t it make sense that mastering data wrangling will yield a huge “return on investment?<\/p>\n Of course.<\/p>\n If you really want to learn data science, the first skill you must master is data manipulation.<\/p>\n Everything else \u2013 data analysis, machine learning \u2013 it all hinges on data manipulation.<\/p>\n So before you learn more advanced skills, you should focus on data manipulation.<\/p>\n If you’re ready to take data science seriously, enroll today and learn to wrangle your data like a professional.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.19.0″ custom_padding=”7px|64px|49.75px|64px|false|true” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” locked=”off” global_colors_info=”{}”][et_pb_row _builder_version=”4.22.1″ max_width=”980px” custom_padding=”0px||0px||true|false” box_shadow_style=”preset2″ box_shadow_horizontal=”-10px” box_shadow_vertical=”10px” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.0″ background_color=”#efefef” custom_padding=”|0px||0px|false|true” global_colors_info=”{}”][et_pb_text _builder_version=”4.22.1″ text_font=”|600|||||||” text_font_size=”52px” 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[\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n I’m sure you’re busy and crunched for time.<\/p>\n I am too …<\/p>\n That’s exactly why I designed Numpy Mastery to be the most time efficient way to learn and master Numpy.<\/p>\n It’s designed to help you master numeric data manipulation as fast as possible … in the smallest amount of time.<\/p>\n To be clear: I’m not talking about taking shortcuts.\u00a0 Shortcuts are for lazy people who don’t want to put in any effort.<\/p>\n I’m talking about efficiency.<\/em><\/p>\n Everything about Numpy Mastery is designed to be maximally efficient.<\/p>\n … the structure of the course<\/p>\n … the lessons (you can even play the videos at 2x speed)<\/p>\n … the practice exercises (which will help you memorize the syntax in only a few weeks)<\/p>\n Everything about Numpy Mastery is designed to be as time efficient as possible.<\/p>\n If you can put in only 20 or 30 minutes a day …<\/p>\n … and if you practice exactly like we show you<\/p>\n Then you’ll be wrangling your numeric data like a pro in only a few weeks.<\/p>\n If you’re ready to learn Numpy and if you’re ready to stop wasting time, then enroll now.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.19.0″ custom_padding=”7px|64px|49.75px|64px|false|true” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” locked=”off” global_colors_info=”{}”][et_pb_row _builder_version=”4.22.1″ max_width=”980px” custom_padding=”0px||0px||true|false” box_shadow_style=”preset2″ box_shadow_horizontal=”-10px” box_shadow_vertical=”10px” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.0″ background_color=”#efefef” custom_padding=”|0px||0px|false|true” global_colors_info=”{}”][et_pb_text _builder_version=”4.22.1″ text_font=”|600|||||||” 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[\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n Have you ever had to stop your work to look up some code on Google or Stack Overflow?<\/p>\n You can be honest …<\/p>\n I have too.<\/p>\n I’ve been there.<\/p>\n Stopping to look up syntax is a huge drag on your productivity.<\/p>\n That’s why I’ve designed Numpy Mastery to enable you to memorize Numpy Syntax.<\/p>\n If you practice like we show you, you’ll memorize all of the critical tools of Numpy.<\/p>\n … and you’ll be able to write code “fluently”<\/p>\n You’ll be able to write Numpy code quickly, accurately, and from memory.<\/p>\n Being able to write Numpy code fluently will dramatically boost your productivity.<\/p>\n If you already know a little Numpy … it’s easily a 2x or 3x boost.<\/p>\n And if you’re a relative beginner, this course could 10x your productivity in as little as 10 weeks.<\/p>\n If you want to stop wasting time looking up code, and you want to skyrocket your productivity, enroll in the course.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.19.0″ custom_padding=”7px|64px|49.75px|64px|false|true” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” locked=”off” global_colors_info=”{}”][et_pb_row _builder_version=”4.22.1″ max_width=”980px” custom_padding=”0px||0px||true|false” box_shadow_style=”preset2″ box_shadow_horizontal=”-10px” box_shadow_vertical=”10px” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.0″ background_color=”#efefef” custom_padding=”|0px||0px|false|true” global_colors_info=”{}”][et_pb_text _builder_version=”4.22.1″ text_font=”|600|||||||” text_font_size=”52px” text_line_height=”1.2em” text_orientation=”center” custom_margin=”10px||0px||false|false” custom_padding=”0px||0px||false|false” text_font_size_tablet=”38px” 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I want lifetime access [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font_size=”22px” text_orientation=”center” custom_margin=”20px|75px|20px|75px|false|true” global_colors_info=”{}”]<\/p>\n When you join, you’ll get lifetime access to the Numpy Mastery course, including videos, code, practice exercises, and all future updates.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”|700|||||||” text_font_size=”26px” header_3_text_align=”center” text_orientation=”center” min_height=”6px” custom_margin=”0px||10px||false|false” custom_padding=”0px||0px||true|false” global_colors_info=”{}”]<\/p>\n 5 monthly payments of:<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font_size=”33px” header_line_height=”0em” header_2_text_align=”center” header_2_font_size=”78px” min_height=”95px” custom_margin=”0px||10px||false|false” custom_padding=”0px||0px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_button 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button_border_color__hover_enabled=”on” custom_padding__hover_enabled=”on” button_border_color__hover=”#00bdce” button_text_size__hover=”42px” custom_padding__hover=”||||false|false” button_bg_enable_color__hover=”on”][\/et_pb_button][et_pb_text _builder_version=”4.23.4″ text_text_color=”#e09900″ text_font_size=”22px” text_line_height=”1.6em” text_orientation=”center” custom_margin=”|12px|20px|12px|false|true” link_option_url=”https:\/\/sharpsight.teachable.com\/purchase?product_id=5288451″ global_colors_info=”{}”]<\/p>\n Or pay in full today and save $16<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2019\/03\/visa-mastercard-amex.png” align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” _builder_version=”4.19.0″ max_width=”22%” module_alignment=”center” custom_margin=”0px||0px” custom_padding=”0px||20px||false|false” locked=”off” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” _builder_version=”4.16″ custom_padding=”43px|158px|1.8px|148px|false|false” custom_padding_tablet=”21px|50px||50px|false|false” custom_padding_phone=”|20px||20px” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|tablet” _builder_version=”4.16″ custom_padding=”30px|50px|49px|50px|false|true” custom_padding_tablet=”|20px||20px||true” custom_padding_phone=”18px|0px||0px|false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ header_font=”||||||||” header_font_size=”24px” header_2_font=”||||||||” header_2_text_align=”center” header_2_font_size=”46px” header_2_font_size_tablet=”34px” header_2_font_size_phone=”26px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n According to Glassdoor, the average salary of a data scientist was over $120,000 per year in 2018.<\/p>\n <\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.sharpsightlabs.com\/wp-content\/uploads\/2019\/03\/glassdoor-data-science-salary-distribution.png” align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.22.1″ text_font=”||||||||” text_font_size=”22px” global_colors_info=”{}”]<\/p>\n That\u2019s over DOUBLE the median household income in the US.<\/p>\n Do the math.<\/p>\n Mastering data science skills could be worth tens of thousands of dollars in a single year.<\/p>\n And over the course of your career, data science skills could be worth hundreds of thousands of dollars<\/span><\/em>.<\/p>\n Numpy Mastery will help you master a critical data 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essential Numpy tools<\/p>\n\n
Numpy syntax<\/p>\nRead What our Students are saying about\u00a0 our courses and training method<\/h2>\n
![\"\u2705\"](\"https:\/\/s.w.org\/images\/core\/emoji\/11.2.0\/svg\/2705.svg\")
Over 85 video lessons<\/p>\n Over 15 hours of video content<\/p>\n Over 380 practice exercises<\/p>\n A system for practicing syntax (this works so well, you\u2019ll be writing code \u201cwith your eyes closed\u201d)<\/p>\n Lifetime access to course materials (access everyday, 24\/7, permanently)<\/p>\n Free access to all future updates to the Numpy Mastery course<\/p>\n
is right for you if answer YES<\/span> to
any of these questions…<\/p>\n Do you want to learn Numpy?<\/p>\n Do you want to master Numpy as fast as possible?<\/p>\n Do you want to increase your skill in data manipulation?<\/p>\n Do you need to manipulate your numeric data into shape?<\/p>\n Do you feel like you\u2019ve gotten as far as you can on your own?<\/p>\n Are you ready to accelerate your data science learning?<\/p>\n Are you ready to invest in your skill set?<\/p>\n Do you want to learn the best ways to do data manipulation with Numpy?<\/p>\n Do you want to become a data scientist?<\/p>\n You want to be more productive with your data projects?<\/p>\n Do you want to learn the “foundation” for advanced data science topics?<\/p>\n Are you overwhelmed with data science material?<\/p>\n Do you feel \u201clost\u201d or \u201cstuck\u201d when you work with Numpy?<\/p>\n Do you want to use a proven system to help you master data wrangling?<\/p>\n Do you want a clear, and you want a clear step-by-step course that will help you master numeric data manipulation in Python?<\/p>\n Do you sometimes forget Numpy syntax?<\/p>\n Have you ever had to look up Numpy syntax on Google or Stack Overflow?<\/p>\n Are you interested in memorizing Numpy syntax so you never forget it?<\/p>\n Do you want to write Numpy code “fluently” ?<\/p>\nDo you want to dramatically increase your productivity when working with numeric data in Python?<\/p>\n
\n<\/em><\/span><\/p>\nFrequently Asked Questions<\/h2>\n
risk-free for 30 days<\/p>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n
Master the “most important”
\ndata science skill<\/h2>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n
Get the most efficient way
to learn Numpy<\/h2>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n
Skyrocket your productivity<\/h2>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n
A skillset worth thousands<\/h2>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n
You could save yourself
months<\/em><\/span> of time<\/h2>\n
to Numpy Mastery!<\/p>\n$29<\/h2>\n