Gain the confidence to solve real-world problems by completing fun, end-to-end projects (instead of watching theory-heavy video lectures!)

Dear Prospective Student,

If you’re a developer, analyst, or aspiring data scientist trying to learn machine learning, there are probably 2 key problems you’re facing right now...

Problem #1: Too much focus on theory

Theoretical concepts are great, but there's a huge gap between "whiteboard math" and the ability to solve valuable problems…

There are plenty of great lectures available on the Internet... but the fact is that nothing can prepare you for real world datasets.

...nothing except practice, that is.

You need to practice your skills in a realistic setting to gain true mastery over data science and machine learning.

Problem #2: An overwhelming amount to learn 

The second you dive into the world of machine learning, you’re drowning in complex jargon and complicated formulas…

And that’s because there are SO many pieces that fit into the greater “puzzle” of machine learning that it’s almost impossible to know where to start — let alone how everything fits together...

That’s why you need a simple and practical framework that can tame the chaos.

In other words, you need a step-by-step system that can teach you how to apply each algorithm in context

...instead of “bursting your bubble” by listing more and more pre-requisites before you can even begin.

The #1 Most Important Tip For Mastering Applied Machine Learning…

That’s why we do things differently here at EliteDataScience...

Our team has plenty of experience in the field doing things like:

  • Training deep neural networks for a computer vision startup (that later raised seed funding at a valuation of $15 million)
  • Predictive modeling for a leading healthcare research and technology company
  • Providing big data analytics to Fortune 500 companies like Walmart and Mastercard
  • Training ML models across a wide range of domains: financial markets, adTech, corporate strategy, etc...

...There’s 1 “tip” we’ve picked up that’s more important than anything else when it comes to mastering this subject…

And it this...

The only way to master machine learning *without* feeling overwhelmed is to “learn in context”!

You see, by tackling fun and interesting projects that “force you” to learn how to apply machine learning concepts from end to end… can dramatically fast-track your learning and overall skill development.

Think about when you were a kid…

You were able to very quickly build a large vocabulary by reading books and hearing your parents speak…

And that’s because you were learning these new words in context!

Now, don’t get me wrong…

Theory IS important.

But by embracing a project-centric approach to mastering machine learning, you’ll benefit in 3 major ways:

#1 You won’t burn out or get bored - This is the biggest hidden pitfall when it comes to self-study programs. When you’re learning by working on a fun project, you’re excited to continue and dive into the next task.

#2 You’ll pick up theory easier - This is a simple one. With practical skills in hand, it’s much easier to understand theoretical concepts. Not even the world’s best textbook can compare to the value of rolling up your sleeves and testing things for yourself.

#3 You’ll learn new skills much faster - When you’re practicing everything that you learn as soon as you learn it, you learn new skills much faster than by “front-loading” with theory and then trying to work out the application part later.

Here’s the bottom line:

If you want to *master* machine learning without feeling overwhelmed, you’ve got to learn in context

You’ll gain confidence, develop practical skills, and build an impressive portfolio, all at the same time.

The Machine Learning Workflow

Applied machine learning emphasizes efficiency and effectiveness because the fact is that results can be quantified…

That means that if you want to become a data scientist or leverage machine learning in your work…

...then you need to learn how to apply the right algorithms in the right place at the right time.

Simple, right?

That’s why we created The Machine Learning Masterclass

Introducing: The Machine Learning Masterclass...

The Machine Learning Masterclass is the comprehensive course on practical machine learning and data science you’ve been waiting for…

Here’s how to know if it’s for you:

→ You want to become a data scientist or apply machine learning models in your work

→ You want to gain real-world skills that are in high demand and command a high-paying salary

→ You want to learn through fun, hands-on projects instead of boring theoretical lectures

Now here’s what you’ll gain in The Machine Learning Masterclass:

Course Overview: Here's What You'll Learn...

Learn how to build professional-grade machine learning models.

Our masterclass is laser-focused on building effective models. We will teach you the entire machine learning workflow, and you'll get to implement it on multiple real-world datasets.

This course is self-paced and can be completed in about 20-40 hours. You will have lifetime access to the content, so you'll never feel rushed.

Reliable and Valid Results
Interactive Machine Learning Projects

Enjoy 4 interactive, portfolio-ready projects.

This course features 4 epic, hands-on projects that you'll complete through interactive Jupyter Notebooks. This approach is more fun, and you'll learn in context. Plus, these projects look very impressive in your portfolio (yes, we cover data visualization, too).

Each of these projects would be considered "capstone projects" in other courses.

Gain valuable skills that can accelerate your career.

Practice tackling real business challenges. You'll get to see how ML can help in e-commerce, HR analytics, and even real-estate valuation.

Whether you're an aspiring data scientist or you just want to apply machine learning in your current work, this course will provide you the right skills.

Machine Learning Salary
Learn from real data scientists

Get practical advice from data scientists, not from professors.

Get down-to-earth guidance straight from professional data scientists. We exclusively focus on actionable advice and industry best practices.

By the end of the course, you will be self-sufficient thanks to carefully designed progression and mentorship.

Here Are The 4 Projects You'll Complete...

Project 1: Meet the Quartermaster

Project 1: Meet the Quartermaster

If you've watched any of the classic James Bond films, you'll know that every successful mission requires at least two elements:

  1. A witty action star.
  2. Cool gadgets, sexy cars, and reliable tools (provided by Q, the quartermaster).

So who's the action star in this course? It's you, of course! 

And you guessed it... this first project is all about equipping the best tools for the mission.

Think of this as an "orientation project on steroids." We'll introduce the big picture concepts and the libraries that will help us throughout the course.


  • A comprehensive & beginner-friendly Python programming course.
  • The best tools and libraries for machine learning.
  • The big picture concepts every practitioner must understand.
  • How to plan an efficient machine learning workflow.
  • Exactly where all the moving pieces fit in.
  • And much more...
Project 2: Real-Estate Tycoon

Project 2: Real-Estate Tycoon

What does it take to become a real-estate tycoon? A huge bank account? Shark-like negotiation skills? Connections in every corner of the town?

Well, those certainly help (a lot!)... But what you definitely need is the ability to value houses accurately for spotting good deals...

And that's what we'll tackle in our second project... We'll apply machine learning to create a pricing model using data from thousands of homes.

After Project #2, you'll find that so many previously confusing concepts will just "click" because you'll get to see the entire ML process from start to finish, with special emphasis on the algorithms used for Supervised Learning: Regression.

Concepts Include:

  • Practical comparison of regression algorithms.
  • How to perform exploratory analysis like a pro.
  • Exactly when to apply different data preprocessing steps.
  • How to sample and split your data the right way.
  • The #1 guideline for choosing the best model for the problem.
  • And much more...
Project 3: Employee Retention

Project 3: Employee Retention

Data science and machine learning are revolutionizing many fields in exciting ways. One of the hottest uses for machine learning right now is in human resources (HR) analytics.

For many companies, their most challenging task is finding, training, and keeping talented employees. Therefore, it's in their best interest to identify employees likely to leave and then bribe them with a pay raise proactively address their concerns.

In this project, you'll build ML models for predicting employees likely to quit based on factors such as the average number of hours worked per week and the time since their last promotion.

In Project #3, you'll take your skills to the next level by stepping into the driver's seat and learning more advanced concepts, with emphasis on algorithms for Supervised Learning: Classification.

Concepts Include:

  • Practical comparison of classification models.
  • How to perform feature engineering like a pro.
  • The easiest way to avoid overfitting your model.
  • How to evaluate your model using different error metrics.
  • Smart shortcuts that can save you hours of work.
  • And much more...
Project 4: Customer Segments

Project 4: Customer Segments

Successful businesses use ML to create win-win situations for themselves and their customers. One way is to use clustering algorithms to create better customer segments.

This allows companies to provide better support, cut marketing waste, and offer more relevant products. Companies save money. Customers save more time to watch cat videos on YouTube. Win. Win.

In this project, you'll use unsupervised learning to create customer segments from a cool online retail dataset. This project is especially relevant for e-commerce and digital marketing.

Project #4 will round out your machine learning skillset. Plus, you'll learn how apply Unsupervised Learning algorithms to solve meaningful business problems... That is a true badge of honor, even among ML professionals!

Concepts Include:

  • Practical comparison of clustering models.
  • How to perform dimensionality reduction like a pro.
  • Easy, yet effective ways to visualize your data.
  • How to create business value from your data.
  • Advanced techniques for data wrangling.
  • And much more...

Plus, You'll Get These Extras…

Bonus #1: Quickstart Setup

First, you'll get the most stress-free way of getting started with machine learning, thanks to...

  1. Step-by-step guide to setting up your data science workstation.
  2. Companion Workbooks for each project, where you can write all your code.
  3. All datasets included.

You'll spend less time setting up and more time learning.

Bonus Quickstart Guide
Machine Learning Masterclass Companion Guide

Bonus #2: Companion E-Book

Plus, review will be a breeze with our companion e-book rich with notes, code, and images.

You'll have all the key concepts and code snippets all in one place, so you can focus on enjoying the course instead of taking notes.

Bonus #3: On-Demand Mentorship

Next, you'll get access to a priority support channel. Enjoy ultra-fast turnaround times on any questions that arise, big or small.

Think of this like "on-demand office hours."

Unlike other self-paced courses that dump a bunch of videos into your lap and say 'good luck,' we are fully committed to helping you succeed.

Premium Support
Lifetime Access and Updates

Bonus #4: Lifetime Access & Updates

Finally, unlike bootcamps where you only have access to the material for a limited time, you'll get lifetime access to the course dashboard, including all future updates.

Machine learning is a rapidly evolving field, and a great machine learning course should evolve as well.

This course will never be outdated, and you're warmly welcomed back at any time.

Here’s What Students Are Saying…

Zachary Washam Investment Banking Analyst, USA

"Differentiator in my day job"

The course has been great. Very well put together, easy to follow, and I feel like I'm learning effectively. I like that it's very interactive - learn by doing rather than lectures. The course has exposed me to things I would not learn in my job but are highly relevant to the analysis I do every day. The things I've learned in this course have been a differentiator for me in my day job.

Kash Nouroozi Software Developer, Canada

"I fell right into the driver's seat"

I've been let down by online courses before, and I was weary of sinking money into something else. I'd tried MOOC Machine Learning classes before, but they focused on algorithms too much. I fell right into the driver's seat — the seat where you LEARN! — with your course. I found it very hard to lose gumption through the course because the topics built upon each other well. Now, I'm no longer totally opaque about the machine learning space, and the course reinvigorated my motivation for learning.

Julie Truong Marketing Analytics, UK

"Thank you for being human and old school"

I appreciated that 'me' is the most important subject here, as opposed to trying to sell me something all the time e.g. extra resources. I miss the world where companies would go above and beyond to help individuals succeed and let word of mouth do its job, and not try to get a few extra dollars for something really beneficial. Thank you for being human and old school!

Will McLaurin Analyst, USA

"I've gotten a lot better at Python"

I was concerned whether the course would be accessible. But I found that it is very well thought out and the teaching strategy fit well with my learning style. I've gotten a lot better at Python and I now know how to apply Machine Learning to business problems. I believe anyone interested in learning Machine Learning could definitely use this course as a door to accomplishing that.

Kurt Berg Freelance Developer, Canada

"You guys put a lot of thought into its design"

I very much enjoyed the course. You guys put a lot of thought into its design and that was evident with the little details. This course had a few features that I haven't seen in other courses that really add to the experience. The priority support (that you actually answer quickly) was the biggest one. That was very helpful and made the course more intimate.

Roxana Villafañe PhD Student, Argentina

"Build my first data science portfolio"

The course made the concepts a lot easier to understand and build my first data science portfolio. The concepts are presented in a clear and direct way to fully understand the topic. I have done a lot of online courses, but think that this is undoubtedly the most clear and direct to proceed.

Yunbum Choi Nuclear Engineer, South Korea

"I learned how to solve problems in an efficient way"

I just wanted to learn the best contents and not waste my time. I am familiar with Javascript and R, but seldomly use python.

With your course, I like that I can learn stuff in a humorous way. It keeps me studying and I never lose interest. After taking your course, I learned how to solve problems in an efficient way. It's good for Data science and learning python, and it is time saving!

Ben Wilson BI Analyst, USA

"I'm confident to take on predictive analytics projects at the office"

This is at least my 5th pass at learning this material (Thinkful bootcamp, Andrew Ng Course, Data Camp, and a multitude of books). You've given me a rock solid framework. Walking through the full process from data exploration to proper test splits and hyperparameter search to fit the best model was so valuable. A lot of other programs just focus on the algorithm implementation. It's easy when you are starting with the ABT. Now I'm confident to take on predictive analytics projects at the office that no one has had the expertise to tackle before.

These Skills Will Command a High-Paying Salary Anywhere…

The simple fact is that data science and machine learning skills are in high demand, and can easily help you land a high-paying job anywhere in the world…

And there’s no better way to develop these incredibly valuable skills than by “learning in context.”

So click the button below to enroll in The Machine Learning Masterclass now, and let's do this together:

Enroll Today for $295
Course Access
Python & Programming
Programming Basics
Git / Github
Supplemental Theory
Big Picture Concepts
Descriptive Statistics
Inferential Statistics
Applied Machine Learning
Exploratory Analysis
Data Wrangling
Data Cleaning
Feature Engineering
Time Series
Dimensionality Reduction
Model Validation
Special Features
1:1 Video Calls
Accessible Without Math Expertise
Interview Review
End-to-End Projects
Money-Back Guarantee

$295 One Time

Machine Learning Masterclass

  • Course AccessLifetime
  • Self-Study
  • Python & Programming
  • Programming Basics
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Scikit-Learn
  • Git / Github
  • Supplemental Theory
  • Big Picture Concepts
  • Descriptive Statistics
  • Inferential Statistics
  • Applied Machine Learning
  • Exploratory Analysis
  • Data Wrangling
  • Data Cleaning
  • Feature Engineering
  • Regression
  • Classification
  • Clustering
  • Time Series
  • Dimensionality Reduction
  • N.L.P.
  • Model Validation
  • Special Features
  • 1:1 Video Calls
  • Accessible Without Math Expertise
  • Interview Review
  • End-to-End Projects
  • Money-Back Guarantee30-Day

$499 / mo. Per Month

Data Science Intensive

  • Course AccessMonthly
  • Self-Study
  • Python & Programming
  • Programming Basics
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Scikit-Learn
  • Git / Github
  • Supplemental Theory
  • Big Picture Concepts
  • Descriptive Statistics
  • Inferential Statistics
  • Applied Machine Learning
  • Exploratory Analysis
  • Data Wrangling
  • Data Cleaning
  • Feature Engineering
  • Regression
  • Classification
  • Clustering
  • Time Series
  • Dimensionality Reduction
  • N.L.P.
  • Model Validation
  • Special Features
  • 1:1 Video Calls30 minutes / week
  • Accessible Without Math Expertise
  • Interview Review
  • End-to-End Projects
  • Money-Back Guarantee7-Day

$4,950 One Time

Part-Time Data Course

  • Course Access10 Weeks
  • Self-Study
  • Python & Programming
  • Programming Basics
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Scikit-Learn
  • Git / Github
  • Supplemental Theory
  • Big Picture Concepts
  • Descriptive Statistics
  • Inferential Statistics
  • Applied Machine Learning
  • Exploratory Analysis
  • Data Wrangling
  • Data Cleaning
  • Feature Engineering
  • Regression
  • Classification
  • Clustering
  • Time Series
  • Dimensionality Reduction
  • N.L.P.
  • Model Validation
  • Special Features
  • 1:1 Video Calls
  • Accessible Without Math Expertise
  • Interview Review
  • End-to-End Projects
  • Money-Back Guarantee

Our 30-Day "Triple Factor" Guarantee

If, at any time within the first 30 days after you join…

  1. You’re not satisfied with the projects you’re working on
  2. You don’t feel like you’re learning useful skills
  3. You simply don’t like the font we use

...then we’ll refund your tuition in full. No questions, no nonsense. We will happily shoulder your risk because we believe in this product.

Click the button below to enroll in The Machine Learning Masterclass now:

Enroll Today for $295
Saeed Adam Advertising, Zambia

"You've made light of the dark arts"

The course was engaging and very interesting. I especially love the wicked sense of humour of the content's tone and the random jokes and pop culture references (Bowser, the final Boss, heheh). Specifically, I like the extreme practicality, zero BS focus (ie not too much theory) of the course. You've made light of the dark arts. Data Science is now accessible to Muggles! Rejoice! But seriously, the course simplifies a difficult subject by focusing on practical application. I have already recommended this course to a few people. I hope they buy and support you in producing great content.

Parth Kapoor Financial Engineer, USA

"Your course has given me more confidence"

My favorite part of the course was its breadth/practical application. Most tutorials will teach Python/Data Science packages but it's really hard to retain the information. Your course has given me more confidence to look for data projects and want to look for ways to be better at visualizations.

Ammar Khwaira Data Architect, Jordan

"The course made my thoughts clear"

The course made my thoughts made clear about how to begin the machine learning process. I had taken so many courses, but i just did not know how the first steps work (to clean the data and dealing with outliers). Also, this course compares different models (like regression models) to choose one. This is not introduced in other courses like Datacamp or Udemy. All I heard about on those was only "linear or multiple regression" and not how to use other models.

Michael Thomas Electronics Engineer, UK

"It is all sinking in"

Your course is very enjoyable and informative. I was using DataCamp and it is very good but they throw things at you in chunks and it is hard to take it all in. I like the way you set things out and the use of Jupyter Notebooks.

So far I am still working my way through it, but slowly it is all sinking in. 🙂

Jeffrey Stilwell Startup Founder, USA

"LOVE the practical approach"

LOVE the practical approach vs. spending a ton of time on theory... and I gained a solid understanding of ML and how it could be applied to my business. Your practical approach is a great way to learn these complex concepts.

Jess Stahl Professor, USA

"The really valuable skill in the near future"

ML is generally presented as though advanced level math is required. Yet, I knew IT and CS professionals who used tools to engage in ML that did not have an extremely advanced math background. This type of course is helpful for those with IT/analyst background who are not looking to invest several years in math courses, but would like to engage in ML. Soon, I think there will be many tools that perform the math so that the really valuable skill in the near future will actually be understanding the process and the results for informed decisions/conclusions/recommendations.

Owusu Sarpong Researcher, Ghana

"Using Jupyter notebook makes it exciting to follow"

I am amazed with the well-explained instruction and guidance through the course. Using Jupyter notebook for teaching the course makes it exciting to follow because you don't have to jump here and there - i.e. read the course in lets say pdf document, and then switch to a console/command prompt to practice the code. Thanks for the work that you (the team at Elite Data Science) do for nurturing the skills for future in us. God bless you all, and strengthen you take this work to new heights!

Rafael Paim Financial Analyst, Portugal

"Link between the concepts and the real steps of a data science job"

I was looking for the link between the concepts and the real steps of a data science job. The way you approach the models/techniques is a far better way than long and exhaustive statistical explanations. I feel motivated to keep learning more detailed and complex models. This is the "easy and soft" way we can learn and start understanding and apply data science in our day to day problems. I'm very pleased and you fulfill 100% the objective.

Frequently Asked Questions (FAQ)

Do I need to know Python to take this course?

No. In fact, some of our students do not even have prior coding experience.

Our comprehensive Python Crash Course teaches the essentials needed for machine learning. It starts with programming fundamentals (which you can skip if you have prior experience) and then covers Python syntax, libraries, best practices, and examples.

How does this compare to Andrew Ng's machine learning course (at Stanford)?

We think Andrew Ng’s machine learning course is fantastic. However, it’s heavy on theory and very light on practice. Andrew’s course will give you a good understanding of the math, but applying those algorithms the right way is a whole ‘nother beast.

This course is the missing link between academic theory and the real-world best practices professionals are actually using. It’s also beginner-friendly, as we cover all the essential concepts.

How much time investment is required?

The course is designed to take about 20-40 hours to complete, depending on your background. Most students finish the course in 1-3 months, part time. The course is self-paced, and you get lifetime access, so you can find the best pace for you.

Can I list these projects on my resume/LinkedIn profile?

Yes, absolutely. We want you to learn the skills and walk away with some shiny trophies to show for it.

What if I don't like the course?

Our philosophy is very simple: if you don’t learn, we don’t earn. If you’re unhappy with the course for any reason, simply email us within 30 days, and we’ll give you a full refund, no questions asked.

Will this help me become a data scientist or ML engineer?

Short answer: Yes, very much.

Long answer: This course was created to help anyone in any industry apply machine learning to get professional-grade results. Companies want to see if you can deliver value, so these business-oriented projects are 100x more impressive than academic ones.

Is this course compatible with Python 3?

Yes, this course is compatible with both Python 2.7+ and Python 3. In fact, our bonus Quickstart Guide will help you painlessly get set up with either version of Python and all of the required libraries.

What if I have another question?

Send us an email, and we’ll be happy to answer it! You can reach us at support [at] elitedatascience [dot] com.

"Often courses will skip over what the instructor thinks is obvious"

I was worried about receiving similar content to other courses like Udemy or Andrew Ng's YouTube series. But after enrolling, I found that the steps were very detailed which i like because often courses will skip over what the instructor thinks is obvious but not to the student. I'd recommend this course to others. Great price value. Learn a lot. Get hands on experience.

Terry Zhang Student, Canada

"I just came out of a data scientist interview"

You provided the projects, the code, and the answers. Sometimes i forget how to do stuff, and i have taken previous courses and simply abandoned them because they force you to research the answer. Who has time for that. Maybe if I was in my 20s again, back in university, sure. But i am in my 40s, trying to change careers, fast, and this course has the right ingredients to do that. Thx!

The machine learning material is great! It is the best machine learning stuff i have seen to date, and you make it easy to understand. The machine learning material is great! It is the best machine learning stuff i have seen to date, and you make it easy to understand. I just came out of a data scientist interview the other day. They don't care about the math, only that i can explain it in no nonsense way, and i did, and it got me to the next round of interviews thanks to your materials.. They don't care about the math, only that i can explain it in no nonsense way, and i did, and it got me to the next round of interviews thanks to your materials.

Stephen Rimac Data Analyst, Canada

"I was very impressed with the Python course"

I am not too experienced with Python and was unsure to what extent it would be covered in the course. But I was very impressed with the Python course. It is very helpful to follow the examples in the Jupyter notebook, as it helps solidify the topics. I am learning a lot about Python as well as Pandas and NumPy. Most importantly, it makes understanding the concepts easy due to the language used and accompanying examples.

Ricardo C. Analyst, Canada

"The 'hands-on' approach is the best I have ever seen."

I found this course to have an excellent layout and approach in comparison to traditional 'bootcamps'. The "hands-on" approach with excellent explanations on academics where needed is the best I have ever seen. Your course helped someone who has limited knowledge on statistics and primarily with a software development background learn ML techniques. The course delivers. This one of the best I have ever seen in terms of teaching (including other areas outside of Data Science). I can see that a lot of effort and heart went into creating this course.

Mike R. Software Developer (Cloud native apps), USA

"It's project-based learning, not just straight theory"

Before enrolling, I was concerned about the cost, but your course exceeded my expectations for 4 reasons:

1) Step-by-step instructions - I never felt like I was getting lost.

2) Explanations - you give insight about why certain things are done. That knowledge and intuition is extremely valuable in helping to build a solid understanding.

3) Comprehensive - we go through the entire data science process, not just a single part of it, so we can see how everything ties together.

4) Jupyter - the interactive notebooks are great, and you also teach us to use things currently being used in the industry.

I recommend this course to others because it's project based learning, not just straight theory, which really differentiates you guys. Things are comprehensive, clearly-explained, and overall, a really high quality class.

Annie T. Software Developer, USA

"Template I can use in projects as work"

Your course exceeded my expectations. The projects provided me with a template I can use in projects at work. I developed a workflow for DS projects and solidified some Python skills. My favorite part was how the course was project oriented. Less hand-holding as course went on. I felt like I was actually implementing skills rather than just copying or running code.

Sharon K. BI Specialist, USA