Master Data Science in Python
in a Few Weeks

• Master Python data science syntax
• Learn essential data science skills in weeks
• Become “fluent” in writing Python code

You’ve probably heard all of the hype:

Data is the new oil.

Data is the new currency.

Data will be worth millions.

Yeah, these phrases are sometimes a little over the top …

But for the most part, they are TRUE.

Data is changing almost every major industry, from finance, to medicine, to marketing.

And the people who master data science are getting PAID.

Take a look ….

According to Glassdoor, right now the AVERAGE salary for a U.S. data scientist is over $120,000.

I’m sure you know … data science is extremely valuable.

There’s just one catch.

Learning data science is really f*cking hard.

“I’ve studied for months,
but I still feel confused”

If you’re like most people, you’ve probably tried a lot of ways to learn data science:

Let me guess …

You’ve probably read several books

… read dozens of free blog posts

…. watched free Youtube videos

…. searched on stackoverflow

Maybe you’ve even tried a few online courses.

If those other methods were really effective, you probably wouldn’t be here.

I’ve heard from countless students who have studied for months, but still haven’t made good progress.

For most people, books and common data science training methods don’t work.

After months (even years) of study, many data science students still can’t write data science code from memory.

And they get confused when they start working on a project.

I have some good news though

Most data science courses have big problems

Here’s the good news …

The problem isn’t you.

You’re absolutely smart enough to learn data science …

The real problem is that most of the materials for learning data science are poorly designed.

Most learning materials suffer from at least one of several problems:

• They’re too theoretical
• They are poorly structured
• They don’t give you a practice system (so you forget everything)

Problem #1
Most Courses are too theoretical

Many data science courses are too theoretical.

For example, many data science students ask me if they need to spend their first year learning statistics and calculus in order to master data science.

No … statistics and math are overrated as data science skills.

They are useful for writing academic papers, but they are less useful in a practical setting.

When I worked at Apple, no one ever asked me to write out statistics equations.

Now I’ll admit that statistics and math have their place in data science. But if you’re getting started, you should avoid theory.

You need practical skills.

You need to be able to wrangle data. 

You need to be able to visualize data. 

You need to be able to analyze data. 

You need to be able to get things done.

Problem #2
Most data science materials are poorly structured

A lot of data science materials lack structure.

This is true of many paid data science courses that give you access to hundreds of lessons, without clear roadmaps …

But it’s also especially true of free materials, if you’re searching on the internet, trying to “figure it out” on your own.

Have you ever tried to learn an advanced technique, but felt a little lost?

Me too …

What you need is a course with clear structure.

You need to learn data science techniques in a way that emphasizes foundational skills.  Skills that build naturally on one another, so when you get to the advanced techniques, everything just makes sense.

Problem #3
Most courses don’t show you how to practice

Maybe the biggest problem is that most courses don’t give you a system to practice what you learn.

This is a big problem.

With most materials, it’s common that a student will learn techniques.

… but will then forget almost everything.

I actually know a guy who spent $30,000 on a data science masters degree.  A few months after he graduated, he had forgotten almost everything!

Have you ever learned some Python syntax, only to forget it a few days later?

Me too!

I feel your pain.

Forgetting syntax is frustrating.

And it’s a waste of time!

But, there’s a secret that I discovered about how to memorize Python syntax.

There’s a way that you can learn data science in Python and NEVER FORGET IT.

… what if you could master data science fast?

What if you could master the essential skills of data science faster than you thought?

A few years ago, I was just like you.

I tried everything to learn data science: books, YouTube, free blog posts.

I learned a little bit, but I forgot many things within a few weeks.  And I struggled to apply what I learned to projects.

But I kept at it …

… I knew there must be a better way to learn data science.

And I eventually “cracked the code.”

I developed a system for mastering data science fast.

This system will show you how to memorize all of the critical data science syntax.

It will help you become “fluent” in writing Python code

… and it will help you master data science in a few weeks, not years.

I want to show you how.

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.

Become “fluent” in python

Importantly, this course is designed to help you become “fluent” in writing Python code.

When most students learn data science in Python, they “learn” techniques, but then forget almost everything.  So when they try to work on a project, they struggle and have to do Google searches for syntax every 5 minutes.

Python Data Mastery solves that problem.

Inside the course, you’ll discover a secret training system that will enable you to memorize everything you learn.

This system will enable you to become “fluent” in writing Python code.  When you eventually begin working on Python data science projects, you’ll write code quickly, effortlessly, and from memory.

Master data science within weeks

Python Data Mastery is designed to be the most efficient, most effective way to master data science in Python.

Ultimately, if you follow the system, you will be able to master critical data science skills within weeks.

The first key to learning efficiently is the structure of the course.  We’ve structured this course methodically.  You’ll learn the right material at the right time.  One topic will flows into the next … so learning will be simple, natural, and effortless.

Moreover, our unique training system is desigened for maximum efficiency.  We used insights from psychology and neuroscience to “hack” your memory.  When you follow our training system, you’ll effortlessly memorize all of the Python syntax you learn within weeks.

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

 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.

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!)

Learn data preparation
and data analysis

Finally, after you learn how to combine syntax, you’ll lear the process for data preparation and data analysis.

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

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

Become “fluent” in the essential skills of data science

Python Data Mastery has been carefully designed to help you become “fluent” in Python … to help you master the techniques of data science in Python.

Imagine…

You sit down at your computer to work on a data science project, and you type the code effortlessly.

That is what real skill looks like.

When you join Python Data Mastery, you’ll discover a training system that will help you become “fluent” in critical Python syntax.

Our training system will enable you to memorize the syntax for base Python, NumPy, Pandas, Matplotlib, and Seaborn.

By memorizing the essential syntax, you’ll build the foundation for writing more complicated pieces of data science code.

The simple syntax that you memorize will become the “building blocks” for more complex data science projects.

It’s 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 dilligently, you’ll become “fluent” in that language. You’ll be able to speak fluidly and rapidly.

It’s the same thing with learning a programming language like Python.  You have to learn the “vocabulary” and then you move on to building things that are more complex.

Python Data Mastery will show you exactly how to become “fluent” in Python …

After a few weeks of practice, you’ll be able to write Python data science code fluently, rapidly, and from memory.

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:

Frequently Asked Questions

This could be worth hundreds of
thousands of dollars

According to Glassdoor, the average salary of a data scientist was over $120,000 per year in 2018.

That’s over DOUBLE the median household income in the US.

Do the math.

Mastering data science skills could be worth tens of thousands of dollars in a single year.

And over the course of your career, data science skills could be worth hundreds of thousands of dollars.

Python Data Mastery is specifically structured to help you learn and master essential data science skills as fast as possible.

Don’t hesitate.

The possible return on investment could easily be 10x what you spend on the course.

Invest in your future by enrolling now.

You could save yourself
years of time

Time is your most valuable resource.

It’s a terrible waste of your time to try to figure data science out by yourself. Some data science students waste years learning useless skills, or struggling to learn anything at all, because they don’t have any plan.

Python Data Mastery will save you valuable time …

The course is highly structured and extremely efficient.

It’s designed to enable you to learn data science in Python as fast as possible, by teaching you the right things, in the right order, and giving you a high-performance practice system for mastering what you learn.

You could save yourself hundreds of hours of unnecessary work.

Don’t try to figure it out alone.

If you join, you’ll get a step-by-step plan.  You’ll also get a high performance practice system that will enable you to master data science skills in a matter of weeks.

Don’t try to figure it out alone. Save yourself your valuable time.

Do the math. If you value an hour of your time at $50 dollars, and this course saves you just 100 hours, that’s $5000 saved.

And personally, I value my time a lot higher than $50 an hour.

If you do too … if you value your time at more than $50/hour, then you could save thousands of dollars.

Do the math.

This course could save you thousands of dollars, just by saving you time.

Invest in a system that works

If you’re like most data science students, you’ve tried a lot of methods to learn data science.

… books, free blog posts, YouTube videos, searches on Google and Stack Overflow.

You might have even taken a few online courses.

I probably don’t need to tell you this, but most methods simply don’t work.

Let me ask you: have you read a data science book and “learned” a few things, but then found that you forgot almost all of it a few weeks later?

I’d be willing to bet that you have.

I personally know one data science student who spent $30,000 on a prestigious data science masters degree.

He learned a few things, but a few weeks after the program ended, he realized that he forgot most of it.

Think about that.  $30K.  Gone.

There’s a happy ending to this story though.

He enrolled in one of our data science courses, and became highly proficient in writing data science code within a few weeks.

And there are many other students who have had great results.

You can get great results too …

…. imagine if you were fluent in writing Python code.

…. imagine if you could memorize data science syntax.

…. imagine that you could do these things in a matter of weeks.

You can, if you invest yourself and enroll in Python Data Mastery.

Learn data science
from home

If you find yourself at home more often right now, Python Data Mastery is perfect for you.

This course is 100% online.

The lecture lessons are taught by video, and you can watch them whenever you like. And you can watch the videos as many times as you like.

We provide you with practice code that you can download and run on your home computer, along with a set of “code walkthrough” videos that explain the code line by line.

And the course will give you a set of practice exercises that you can use to master all of the techniques. You can do this practice at home, whenever it’s convenient for you.

With Python Data Mastery, you can master data science in Python from the comfort of your couch or home office.