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. . . the type of top performer that companies pay for.
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Do you want to be a great data scientist? Then first, you need to be a great data analyst.
We’ll give you the practical tools you need to gather data, wrangle data, analyze data, and ultimately produce the critical deliverables that companies need.
Companies are desperate for data-driven insights, so to get hired you need to master data visualization.
We’ll help you build your data visualization skills from beginer to advanced, so you know how to generate the insights that company’s pay for.
Artificial intelligence and machine learning are projected to add trillions of dollars to the world economy.
We’ll make machine learning easy to understand by breaking it down, explaining it step-by-step, and showing you how practice everything you learn.
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If you want to get a high-paying data science job, you need to master data science skills.
To do this though, you can’t just watch a few videos, read a few books, and cut-and-paste some code . . .
To master data science skills, you need to practice.
In our courses, you’ll discover a high-performance system for practicing data science code and concepts.
This system is based on the neurosciece of how humans learn, and it will help you master the material and become a top performer in record time.
“You deliver excellent information, parsed into just the right units, and provide an awesome way to practice and internalize the material.
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Recent Blog Posts
This tutorial will explain how to use the NumPy power function, which is also called np.power. Contents: An review of NumPy Introduction to numpy.power The syntax of numpy.power Examples of NumPy power Frequently asked questions about NumPy power You can click on any...read more
In this tutorial, I'm going to show you how to use the NumPy hstack function, which is also called np.hstack or numpy.hstack. This is a very simple tool that we use to manipulate NumPy arrays. Specifically, we use np.hstack to combine NumPy arrays horizontally. The...read more
This tutorial will explain the NumPy random choice function which is sometimes called np.random.choice or numpy.random.choice. I recommend that you read the whole blog post, but if you want, you can skip ahead. Here are the contents of the tutorial ... Contents: a...read more