Master Data Science 
in 10 Minutes per Day

Discover our step-by-step system for mastering the core Python data science skills you need for a data science job

• Master Python data science syntax in 6-8 weeks
• Master Python data science in as little as 10 minutes
  per day of practice
• Get the skills you need for 6-figure data science job
• Even if you have limited time …

Promotion ends in:

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Hi. I’m Josh Ebner, the founder of Sharp Sight, and a former data scientist at Apple.

I’m sure you know that data science skills are extremely valuable.

And you want to increase your earning power.

For example ….

According to Glassdoor, right now the AVERAGE salary for a U.S. data scientist is almost $150,000.

 

An image that shows the average salary for a data scientist, and the pay range.

 

And at some companies, total compensation is over $300,000 (if you include stock, bonuses, etc).

Becoming a top-tier data scientist is worth thousands of dollars.

And even if you’re a developer or software engineer …

Then adding data skills to your skill-stack can increase your income by $10,000 to $20,000 per year.

Data science is extremely valuable.

Sounds great, right?

Yes …

…. but there’s a catch.

Learning data science is harder than it looks, and it’s very hard to find time.

“I want to learn data science, but it’s so hard to find time.”

So let me guess …

You want to learn data science.

You know that you could make a lot more money if you had strong data science skills.

But … you “just don’t have time.”

So, you put it off…

You say things like:

  • “I don’t have time just now.”
  • “I’ll do it later this year.”
  • “So much to learn, but I have so little time.”
  • “It’s so hard to find time to study.”

Sound familiar?

So you keep putting it off ….

And another week, month, or year goes by.

Data science salaries keep climbing, and you’re still stuck.

There’s got to be a better way, right?

There is …

How I Mastered New Data Science Skills, Even with Limited Time

A few years ago, I was in a similar position as you.

I was very busy.

I had a demanding job.

I had a personal life.

And I even had a few hobbies that I was trying to work on.

In the middle of all of this, I wanted to upskill.

I was making decent money. But I wanted to make more money by improving my skills.

Data science was becoming very popular, and valuable, and I knew that I could make a lot more money with better data science skills.

But the problem was just finding enough time.

Eventually, I made a commitment to find the most efficient way to learn, so I could make the most of my limited time.

To do this, I researched how to learn faster and more efficiently.

It was a bit of a sidetrack, but it paid off.

I read about how Navy SEALs train. I read about how chess masters train. I read about how polyglots learn new languages (polyglots are people who speak multiple languages).

Eventually, I started noticing patterns.

All of these elite performers use similar practice methods to train and learn new skills.

Finally, I “cracked the code” on learning data science.

And everything changed.

What if you could master data science in as little as 10 minutes per day?

After months (even years) of struggling to learn data science, I finally “cracked the code.”

I developed a training system to enable me to very rapidly learn new data science skills.

This system is hyper-efficient.

With as little of 10 minutes of practice per day, this system has enabled me and my students to master Pandas, Numpy, Seaborn, and many other Python skills.

And importantly, this system has helped me and my students memorize the code.

If you’ve ever learned some syntax, and forgotten it later, you need to use our system.

If you practice like we show you, you’ll be able to become “fluent” in Python data science in as little as 3 months.

Here’s how …

Introducing …

PYTHON DATA MASTERY

A systematic, step-by-step course to help you learn and master the essential skills of data science in Python.

 

Learn practical
data science skills

Python Data Mastery focuses on critical, essential data science skills. 

This course avoids unnecessary theory and BS skills that you don’t need.

When you join, you’ll learn the essential foundations of data science in Python.

You’ll start by learning base Python.  Even if this is a bit of a review, you’ll get important practice exercises to help you become “fluent” in all of the important techniques of base Python.

Next, you’ll learn data manipulation.  This will include techniques from NumPy, but also techniques from Pandas.  These toolkits are essential for shaping and “wrangling” data in Python.

Finally, you’ll learn data visualization.  Data visualization is critical at every part of the data workflow, from data exploration, to data analysis, to advanced techniques.

 

Memorize Data Science Syntax

Forgetting data science syntax is a huge barrier to productivity, because you constantly need to stop, and search for how to do something.

That’s why we developed a unique practice system that will help you memorize syntax.

This practice system is based on key insights from cognitive psychology …

An image that shows how the Sharp Sight practice system improves memory and retention over time.

By showing you how to carefully structure your practice, we’ll help you “hack” your memory so that you remember all of the critical syntax for data science in Python, permanently.

This will dramatically increase your “fluency” with writing data science code.

… which in turn, will make you vastly more productive.

 

Discover How to “Put the Pieces Together”

To do real data science work …

Things like data cleaning and data analysis …

You often need to combine multiple tools together in specific ways.

In Python Data Mastery, you’ll discover how to combine together tools from Python data science packages to accomplish real tasks.

An image of Pandas code, analyzing a dataset.

We’ll show you how to “put the pieces together” to do real work.

 

Master data science in 10 minutes per day

I realize that you have very limited time.

So I designed Python Data Mastery to work in as little as 10 minutes per day.

Out practice system uses insights from neuroscience to maximize your training efficiency.

With as little as 10 minutes of practice per day, you’ll be able to learn, memorize, and master how to do data wrangling, data visualization, a data analysis in Python.

It’s the system that I wish that I had years ago …

And if you enroll today, it’s all yours …

A step-by-step system for learning Python data science that’s simple, easy, and effective.

 

“Learning this way is almost addictive!”

– Victor O., Sharp Sight student

In Python Data Mastery, you’ll learn essential data science skills

Python Data Mastery will teach you several critical areas of data science: basic programming, data manipulation, and data visualization.

To do this, you’ll learn four areas within Python:

  • Base Python
  • NumPy
  • Pandas
  • Matplotlib

Specifically, here’s what you’ll learn when you join:

Base Python

In the first two modules, you’ll learn base Python.

The Python programming language forms the foundation of data science in Python, so you need to know quite a bit about data types, logic, and control structures.

 

 

With that in mind, you’ll learn:

  • data types
  • how to perform mathematical calculations in Python
  • logical expressions
  • strings
  • lists and tuples
  • if/else statements
  • for loops
  • functions

If you’re a true beginner to Python, these topics will be explained in a clear, easy to understand manner, so it will all be crystal clear.

And if you have a little experience with Python, you’ll discover a training system that will enable you to become “fluent” in all of these foundational techniques.

NumPy

After learning about base Python, you’ll learn about NumPy.

The NumPy package is a toolkit for working with numeric data. It’s widely used in a variety of tasks within data science, like statistics, data visualization, and machine learning.

Because it’s so common, you really should know Numpy backwards and forwards.

In the NumPy lessons, you’ll learn everything you need to know, like:

  • What NumPy arrays are
  • How to think about array axes
  • How to reshape NumPy arrays
  • How to “split” and “combine” NumPy arrays
  • How to aggregate the numbers in NumPy arrays (i.e., sum, average, min, max)
  • How to generate NumPy arrays with random data

Again, everything will be explained in a clear, straightforward manner that makes it easy for you to understand.

And you get practice exercises that will enable you to master every tool and technique that you learn.

Pandas

Next, you’ll learn about Pandas, which is a toolkit for working with “dataframes.”

If you’re not familiar with them, dataframes are row-and-column data structures that are very common in data science.  They are sort of like Excel spreadsheets, and they are extremely common for storing and analyzing data.

Specifically, you’ll learn:

  • What dataframes are
  • How to create dataframes from raw data
  • How to import csv data into a dataframe
  • How to add variables to dataframes
  • How to delete variables from dataframes
  • How to subset and “slice” dataframes
  • … and more

Pandas is extremely useful for doing data manipulation in Python. In fact, you’ll need Pandas in almost every part of the data science workflow. We’ll help you learn it so well, you’ll be “fluent” in writing Pandas code to manipulate your data.

Matplotlib

You’ll also learn about matplotlib.

Matplotlib is an extremely common data visualization toolkit for Python.

 In the Matplotlib modules, you’ll learn:

  • How to create bar charts
  • How to create scatter plots
  • How to create histograms
  • How to create line charts
  • How to format your data visualizations with “style sheets”

Seaborn

Finally, you’ll also learn about Seaborn.

Seaborn is another data visualization toolkit for Python.  The advantage of Searborn is that it’s easier to use than Matplotlib, and it works better with Pandas DataFrames.

 In the Seaborn modules, you’ll learn:

  • How to create Seaborn bar charts
  • How to create scatter plots with Seaborn
  • How to create density plots
  • How to create line charts with Seaborn
  • How to make “small multiple” charts (this is a powerful technique!)
  • … and more

Learn how to combine syntax

Once you master the individual tools from Pandas, Numpy, and Seaborn, we’ll show you how to “put the pieces together” …

You’ll learn how to combine syntax together to do real data science work.

An image of a laptop, which is playing a video showing how to "chain together" Python methods.

This is the secret to real productivity with Python.

Once you learn how to combine syntax together, you’ll be able to wrangle and visualize your data like a pro.

(If you’ve been looking for something like dplyr pipes from R, you need to learn this!)

Data Cleaning
and Dataset Preparation

After you learn how to combine syntax, you’ll learn the process for data cleaning and dataset preparation.

An image that shows a laptop, playing a video that shows the process for preparing data in R.

In Python Data Mastery, you’ll learn a step-by-step process for getting, cleaning, and reshaping your data.

You’ll learn the high-level process. But we’ll also show you a clear data preparation case study, so you can see exactly how to use Pandas and other tools to clean, reshape, and combine multiple data files into a single dataset that’s ready for visualization and analysis.

An image of code, showing how to merge multiple datasets into a single file.

If you’re struggling with cleaning your data, then these lessons can show you exactly what to do, and how to do it.

Data Analysis

You’ll also learn a step-by-step process for analyzing your data.

You’ll learn how to combine techniques from base Python, Pandas, Seaborn, and other modules to analyze data and find insights.

An image that shows a laptop that's playing a video which explains how to analyze data with dplyr, ggplot2, and the Tidyverse.

So you’ll learn the high-level process of data analysis …

But you’ll also see step-by-step examples of how data analysis is actually done in Python.

An image of some Python data analysis code, and a resulting plot.

We’ll show you how to use data wrangling and data visualization tools together to explore a dataset and find the insights that companies want.

Machine Learning Essentials
with Scikit Learn

After you learn data analysis, you’ll learn machine learning essentials with Scikit Learn.

An image of a presentation, explaining the high-level machine learning process.

You’ll learn what machine learning is, and learn about the high-level process of building ML models.

You’ll also learn the essential syntax of scikit learn.

A simple explanation of the syntax of the Scikit Learn "fit" method.

These lessons will give you a solid foundation in machine learning essentials that will prepare you for more advanced future study.

Bonus Vaults

Python Data Mastery contains bonus vaults of extra material.

  • data visualization teardowns
  • examples of end-to-end projects

In the “data visualization teardown” vault, you’ll learn more about “how to think” about data visualization, and how to “tell stories with data.”

In these video lessons, I break down data visualizations and explain the good, the bad, and the ugly. These lessons will help you sharpen your understanding of how to effectively use data visualizations to communicate valuable insights.

An image of a video that shows a "teardown" of a line chart.
An image of a video showing a "teardown" of a bar chart.
An image showing a video with a quote about data visualization, in the context of a data visualization teardown.

In the project vault, you’ll see an example of an end-to-end project that involves getting data (from Wikipedia), cleaning the data, and visualizing it. This video lesson integrates many of the skills learned in the course, and shows you another example of how they are actually used, in practice.

An image showing Python code, that is cleaning data for a modestly sized Python data science project concerning president ranking data on Wikipedia.

The code that you see in this vault will help you understand how everything fits together, and will give you ideas for how you can put your new data skills to use.

BONUS:
5 Visualization Mistakes
That Make You Look Like an Amateur

Data visualization is as much about good design as it is about writing syntax to create visualizations.

And a big part of good design is avoiding simple design mistakes.

So in this bonus, I’ll show you 5 of the most common data visualization mistakes that amateurs make.

These are things that you NEED to know, so you know what to avoid doing.

You’ll learn:

  • 3 Major Plot Title Mistakes
  • The #1 Worst Visualization That You Need to AVOID (hint: it’s extremely common)
  • The Reason that 3D Charts are Terrible (and what to do instead)

… and more

An image of a video that shows a "teardown" of a line chart.
An image of a video showing a "teardown" of a bar chart.
An image showing a video with a quote about data visualization, in the context of a data visualization teardown.

This bonus will further sharpen your intuition about how to create great visualizations by telling you 5 things that you absolutely need to avoid.

(You really need to see this, because you’re probably doing at least 1 or 2 of them …)

BONUS:
5 Ways To Improve
Your Data Visualizations

Again … data visualization is about more than just writing syntax.

A lot of visualization is knowing how to use different elements of a plot to communicate to an audience visually.

Have you ever heard someone say the phrase “telling stories with data”?

Visual design is a big part of that.

You have to know how to structure your visualizations.

That’s why in this bonus, I’ll show you 5 simple ways to improve the design of your visualizations.

You’ll learn:

  • The RIGHT Way to Use the Plot Title
  • How to Use the Plot Subtitle
  • Why Plot Annotations are Useful (And what to Use Them For)

… and more

An image of a video that shows a "teardown" of a line chart.
An image of a video showing a "teardown" of a bar chart.
An image showing a video with a quote about data visualization, in the context of a data visualization teardown.

In this bonus, you’ll learn more tips and strategies to improve your visualizations, so you create your charts and graphs like a high-paid pro.

BONUS:
Data Science Cheat Sheets

Even though this course will help you memorize critical Python data science syntax, there might be some times when you just need a quick reminder.

So included with the course, you’ll get a …

  • Numpy Cheat Sheet
  • Pandas Cheat Sheet
  • Seaborn Cheat Sheet
An image of a Seaborn Cheat Sheet.
An image of a Pandas cheat sheet.
An image showing a video with a quote about data visualization, in the context of a data visualization teardown.

You can keep the electronic versions on your computer’s desktop for easy reference, or even print out a hard copy to put nearby.

BONUS:
SQL Essentials

Pandas, Numpy, and Seaborn are obviously necessary for data science in Python.

But as a data scientist, SQL is also very important for retrieving data from databases (particularly in large corporate environments).

This bonus will show you the essentials of SQL, as a compliment to your Python data science skills.

An image of a video that shows a "teardown" of a line chart.
An image of a video that shows a "teardown" of a line chart.

When I worked at Apple and Bank of America, SQL was a big part of the job.

So this bonus will probably be very important for you.  

If you want a data science job, these lessons along could be worth the price of the course.

Memorize Python Data Science Syntax
(so you can ace your coding exam)

Python Data Mastery has been designed to help you memorize Python data science syntax.

Like it or not, you need to know Pandas syntax.

For example, when you interview for a data job, they’re going to test you to make sure you know the syntax. They’re going to check that you know what you’re doing.

So imagine…

You’re in your data science coding interview, and they ask you to do some data inspection and visualization on a dataset …

They ask you to load a dataset, inspect it, and then visualize it.

You smile briefly, and then effortlessly type the code ….

Imagine how satisfying it will be to ace your coding interview …

How exciting it will be to get the job offer …

How great it would be to make thousands more than you’re already making.

It’s all possible.

When you join Python Data Mastery, you’ll discover a training system that will help you master all of the critical Python data science syntax you’ll need.

Our training system will enable you to memorize the syntax for cleaning, wrangling, visualizing, and analyzing your data.

This is the key to helping you pass your data science coding interview …

And it’s the key to making you a productive data scientist that companies will pay a lot of money to.

 

“I have been practicing almost every day and it really helped me memorize all the syntax.”

– Corey H., Sharp Sight student

About Your Instructor

josh_blue-shirt_portrait

Hi. I’m Josh Ebner, the founder of Sharp Sight, and a former data scientist at Apple.

I’ve been doing data science and analytics since 2004 (literally since before we called it data science).

I’ve done data science and analytics at some of the biggest and best companies in the world, including Apple, Bank of America, HP, Ogilvy, Kraft, and many others.

Over the course of my career, I’ve written 10s of thousands of lines of data science code for data wrangling, visualization, and analysis.

I believe that data science can be simple and easy, IF you know what you’re doing.

And to know what you’re doing, you need great mentorship.

Therefore, I designed this to teach you what I know, in clear, simple language.

I want to turn you into a skilled data science pro, as quickly and efficiently as possible, using our step-by-step training system.

“Your practice method is simply effective beyond words”

– Joshua F., Sharp Sight student

Read What our Students are saying about  our courses and training method

 I get it …

You’re probably skeptical.

Becoming “fluent” in Python in a few weeks sounds too good to be true.

Mastering essential data science in Python in a few weeks doesn’t seem possible …

But it IS possible. 

You can become “fluent” in Python and master data science skills in only a few weeks.

Our past students have had amazing results.

Here’s what our past students have had to say about our courses and training methodology:

 

“I enrolled in your data science program this past year …. It’s amazing!

Having taught for 20 years, you have one of best approaches I’ve seen to teaching.”

Edwin W.

Founder, dataisliteracy.org

“I want to say thank you for the quality of the course.

The concepts are combined very well with this course. It’s great.”

Vasily M.

“The course is amazing.”

Alexandre F.

“You deliver excellent information, parsed into just the right units, and provide an awesome way to practice and internalize the material.

… the course is delivering on all the promises, and it’s improving my understanding of everything.”

Sharon P.

“Being able to write down key code snippets without looking up anywhere else is so useful.”

Paolo C.

“The course is very good.”

Ganapathy G.

“I’m really enjoying the lectures, coding walkthroughs, and practice.

They’ve been tremendously helpful and I can really see my fluency developing.”

Joshua F.

“I have been practicing almost every day and find that it really helped me memorize all the syntax.”

Corey H.

“I feel much more comfortable and proficient after going through the videos and practicing.”

Michael G.

“Been practicing every day for the last 10 days. Plan on keeping it as a habit for life.

…. It has been phenomenal in helping learn Python!”

Toby P.

“The course helped me to memorize and automate my skills.”

⭐⭐⭐⭐⭐

Dmitriy T.

“Your DSSR method is simply effective beyond words.”

Joshua F.

“I am currently in school for data science and will be getting my bachelors degree in August …

The python course is much more informative than the python course I took at school, and I feel, thanks to you, I will be an expert in the subject soon.”

Amber C.

“I’m getting a ton out of the course and the flashcards … the flashcard drills really reinforce the code. Very effective. ”

David Y.

“In a little over a week since I’ve started, I can see an immense difference in how ‘fluid’ I’ve become.

My overall understanding of how the Python language works, my ability to apply Data Science / Analytics, and of course my general code fluidity has skyrocketed – Thank you ! ”

Bashar K.

“Sharp Sight’s Python Data Mastery is the BEST course for learning data science effectively, and Mr. Ebner is one of the best (and nicest) instructors I have met.

As an Operations Executive, I have applied a majority of course’s knowledge to improving my team’s workflows (using Python and libraries such as Pandas and Seaborn).

And more importantly, you will love Data Science going through this course

A MUST-BUY.”

⭐⭐⭐⭐⭐

Khang G.

When you join Python Data Mastery, you’ll get everything you need to master data science fast:

✅ Over 70 video lessons

✅ Over 500 practice exercises

✅ A system for practicing syntax (this works so well, you’ll be writing code “with your eyes closed”)

✅ Lifetime access to course materials (access everyday, 24/7, permanently)

✅ Free access to all future updates to the Python Data Mastery course

Python Data Mastery
is right for you if answer YES to
any of these questions…

✅ Do you want to learn data science in Python as fast as possible?

✅ Do you want to learn NumPy, Pandas, Matplotlib, or Seaborn?

✅ Do you want to increase your skill in data visualization?

✅ Do you need to manipulate your data into shape?

✅ Do you feel like you’ve gotten as far as you can on your own?

✅ Are you ready to invest in your skill set and accelerate your data science learning?

✅ Do you want to learn the best ways to do data visualization and data manipulation in Python?

✅ Do you want to become a data scientist?

✅ You want to be more productive with your data projects?

✅ Do you want to learn the “foundation” for advanced data science topics?

✅ Are you overwhelmed with data science material?

✅ Have you taken other data science courses, but still feel “lost” or “confused” when you work on projects?

✅ Do you want to use a proven system to help you master data science?

✅ Do you want a clear, and you want a clear step-by-step course that will help you master the foundations of data science in Python?

✅ Do you sometimes forget critical Python Syntax?

✅ Are you interested in memorizing the syntax for doing data science in Python?

✅ Do you want to write Python code “fluently” ?

✅ Do you struggle to find time to study and practice?

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 Python Data Mastery, RIGHT NOW.

BUT!

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.

If you’re out of cash and definitely can’t afford the course, don’t join.

Python Data Mastery is a step-by-step system that will enable you to rapidly master data science …

IF you do the work.

You must be willing to put in some effort in order to get the results.

If you’re willing to do that, then Python Data Mastery can help you master data science within weeks.

Frequently Asked Questions

Do I need to know Python?

No.

While some programming experience will be helpful, if you don’t know Python, this course will get you started.

How does the course work?

Python Data Mastery is an online video course.

After purchasing the course, you’ll get access to a member area, where you will find video lectures, code, practice exercises.

New lessons will be released over several weeks and you can review the material at your own pace. The course is very “flexible” … you can review the material when you want.

“Is this course live?”

This is not a live course.

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.

This makes the course very flexible … you can watch the videos and practice whenever is convenient for you.

“What if I live in India, or China, or Europe?”

You can take this course from anywhere in the world. This course is 100% online, so you can take it from anywhere, at your own pace.

“How long do I have access?”

This is an online course, so you have 24/7 access.

You’ll also have permanent access, so you can return to the material as often as you like (even next year).

"Can I use a different programming language?"

No.

This course only uses the Python programming language. There are other good data science programming languages (like R), but this course exclusively uses Python.

If you want to learn how to do data science with R, you should enroll in our R-based course, Starting Data Science.

“If I want to become a data scientist, would this be a first step?”

Absolutely.

Python Data Mastery is designed to be a “first step” towards becoming a data scientist.

It will teach you core skills that will enable you to be productive almost immediately, and also build on as you develop your skill set.

The skills you’ll learn are the things you’ll be using almost every day as a data scientist.

“Will this prepare me to learn machine learning later on?”

Yes.

Python Data Mastery teaches machine learning essentials using scikit learn.

It also teaches all of the foundational skills that you’ll need for machine learning, like data visualization, data analysis, and data wrangling.

Ultimately, Python Data Mastery teaches you the necessary foundations that you’ll need for more advanced study of machine learning in the future.

“Do I need to know calculus and advanced math?”

No.

Python Data Mastery avoids advanced math topics completely. Most “advice” will tell you that you need to know advanced math to learn data science. This is a huge myth.

Most working data scientists (working in business and industry) do not use math on a daily basis.

Python Data Mastery teaches practical data skills.

So, don’t worry if you don’t know calculus or linear algebra. You won’t need it.

“How much work do I need to put in to the course?”

A couple hours per week.

You can adjust your practice level as needed, so if you only have 10 minutes a day, you can do that.

If you can work for a couple hours per week, you should be able to master the syntax I show you within about 8 weeks.

If you have less time to put in, it may take longer to get results.

“How long does the course last? How many lessons?”

There are 10 modules, and each module as several lessons and exercises.

When you join, you’ll immediately see the first module. Then, new modules open every week. You’ll see all of the material within a few weeks.

But, there are exercises to help you master the syntax. To really get results, you should practice for a few weeks afterwards. You should start to see your “fluency” with the techniques develop within a few weeks. And your fluency will continue to develop beyond that … but only if you practice!

Try the course
risk-free for 30 days

Try the course.

If you’re not completely satisfied with your progress, let me know within 30 days and I’ll refund all of your money, no questions asked.

This is entirely RISK FREE for you. You’ll get to try out the best resource for learning critical data science skills and if you’re not completely satisfied, I’ll refund your money.

Yes! I want lifetime access
to Python Data Mastery!

When you join, you’ll get lifetime access to the Python Data Mastery course, including videos, code, practice exercises, and all future updates.

Only 1 payment today of:

$697

$197

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