The Enjoyable (and Insanely Fast) Way to Learn Machine Learning
Skip the dense math and learn how to solve real-world problems with machine learning through fun projects instead of tedious lectures.
100% Focus on Practical Skills
Gain professional-level DS & ML skills as quickly as possible through fun projects and skip any unnecessary math and theory.
Recommended By 98% Of Students
Over 98% of our past students recommend The Machine Learning Accelerator to anyone looking to learn practical DS & ML skills.
Lifetime Access & All Future Updates
Work through the course material at your own pace without having to worry about losing access or paying a monthly fee.
Dear Prospective Student,
Let's face it... there's a good chance you're here today because you feel confused or overwhelmed.
You want to learn data science so you can excel in your work, gain badass skills, or level up your career...
...but the moment you dove into this field, you were blasted with jargon, math formulas, and hundreds of different concepts.
And as a result, you simply don't know where to start, or how to bring it all together into a coherent skill.
Maybe you've tried watching lectures on YouTube... and now you know some neat theory, but you're still unsure how to apply each algorithm in practice.
Or, maybe you've browsed online forums for advice, only to discover that you have a wall of pre-requisites ahead of you: Linear Algebra this... Statistics that...
We totally get it and we want you to know that what you're feeling is normal.
Think of it like this...
You've basically opened up a jigsaw puzzle and poured all 500 of the jumbled pieces onto your table.
It's a confusing mess that makes no sense.
Trying to piece it all together on your own is possible, but it will take you a very long time.
Thousands of other students who dive into this world feel the exact same sense of confusion and overwhelm that you might feel. In fact, many of those students eventually give up.
As practitioners who use ML every day, it pained us to see students give up because we know it's not as complicated as it seems.
It Doesn't Have to Be Overwhelming
That’s why we do things differently here at EliteDataScience... We were determined to be part of the solution, instead of adding to the problem.
Since launching EliteDataScience.com in 2016, we've already helped over 3000 students learn this exciting skill and supercharge their careers.
And today we have only one goal... To serve as your guide.
To help you bring everything together, to give you clarity, and to help you systematically master data science and applied machine learning.
If you want to gain professional-level DS & ML skills, we'd like to share with you the #1 most important lesson we've learned over the years...
Our #1 Tip for Mastering DS & ML Without Feeling Overwhelmed:
→ → → Learn in Context ← ← ←
Our number 1 tip for mastering applied machine learning without feeling overwhelmed is to learn in context by tackling interesting projects.
You see, when we were young children, we were able to build very large vocabularies by reading books and learning new words in context. Yet, for some reason, machine learning is often taught in a silo'd and piecemeal way...
Mastering a hard skill like machine learning can hugely benefit from contextual learning.
Yes, some theory is important. Yes, you need to know about various algorithms. And yes, you need basic programming chops to get started.
But by jumping into projects sooner (rather than later), you'll benefit in 3 major ways:
- First, you won't burn out or get bored as easily. This is a hidden pitfall that's often overlooked in self-study programs. If you don't feel excited to continue, then nothing else matters...
- Second, your practical skills make picking up theory easier. The best textbook in the world can't compete with rolling up your sleeves and testing the concepts for yourself...
- Finally, you'll learn much faster... When you get to practice each step within the big picture, you'll be learning in context.
Instead of watching additional lectures, which basically dump even more puzzle pieces into your lap, it's much easier to learn by doing.
It's what will allow you to gain confidence, and it's what will allow you to develop a tangible, valuable skill.
The moment you complete an entire project from start to finish, everything will begin to make sense for you...
At the end of the day, unless you wish to become a researcher who dives into individual algorithms hoping to find undiscovered nuances, you'll achieve more by building strong, practical intuition...
Applied machine learning emphasizes efficiency and effectiveness because results can be quantified.
Therefore, if your goal is to use ML in your work or to become a data scientist, then the best advice we can give you is to learn how to apply the right algorithms, the right place, and in the right way.
You can pick up the essential theory and concepts along the way, as long as your projects are comprehensive and have a carefully planned progression.
You Can Gain Professional-Level DS & ML Skills in Just 6 Weeks Part Time
(Even If You Have Zero Prior Experience)
Through dozens of iterations, we've lovingly crafted the ultimate beginner course on practical machine learning and data science.
- If you want to learn ML skills quickly and efficiently...
- If you're tired of feeling overwhelmed and want a streamlined path...
- If you want in-demand skills that will supercharge your career...
- And if you want to learn through fun, hands-on projects...
Then we sincerely believe you'll enjoy our course.
The Machine Learning Accelerator
Gain professional-level DS & ML skills in just 6 weeks, even if you're a complete beginner. No math background or prior programming experience required.
Become deadly with machine learning.
Good ML courses should empower you to apply ML in your work and projects. Unfortunately, many courses fail to deliver on this one simple promise. Their lessons are too piecemeal, they spend too much time on individual algorithms, and they never weave everything together.
Our program 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 30-40 hours. You will have lifetime access to the content, so you'll never feel rushed.
Enjoy 6 interactive, portfolio-ready projects.
Skip the long lectures and boring textbooks. Machine learning is an applied field, and it should be taught in a hands-on, "play-and-learn" way.
This course features 6 fun, hands-on projects that you'll complete through interactive Jupyter Notebooks. Students love this approach not only because it's more fun, but also because it improves retention.
Plus, these projects look very impressive in your portfolio or resume (yes, we cover data visualization, too).
Each of these comprehensive projects would be considered "capstone projects in other courses.
Supercharge your career with in-demand skills.
You will tackle real business challenges. Want to see how ML can help in e-commerce, HR analytics, or even real-estate valuation? Now you can, with hands-on practice.
Machine learning is one of the most in-demand skills on the job market right now. And through this course, you'll get to practice the same machine learning tasks used by Fortune 500 companies and exciting startups.
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.
Learn from data scientists, not from academics.
Get down-to-earth guidance straight from professional data scientists. We exclusively focus on the best modern tools and industry best practices.
In fact, we specifically modeled this course after over-the-shoulder, on-the-job mentorship for new data scientists.
By the end of the course, you will be self-sufficient thanks to carefully designed progression and mentorship.
The Machine Learning Accelerator features 100% project-based learning. By learning each concept and skill in context, you will master them much faster, have much more fun, and keep up the momentum to continue.
Project 1: Python for Data Science
If you've watched any of the classic James Bond films, you'll know that every successful mission requires at least two elements:
- A witty action star.
- Cool gadgets, sexy cars, and reliable tools.
So who's the action star? It's you, of course!
And you guessed it... this first project is all about equipping the best tools for the mission.
Key concepts include:
- Essential big picture concepts before you begin
- The best tools and libraries for machine learning.
- Programming basics for complete beginners
- How to use Python for calculations
- Simple building block data structures
- How to use flow control and functions
- Heavy duty number crunching with NumPy
- Data analysis and management with Pandas
Project 2: How the World Works
If they use the exact same tools and have access to the exact same data, what's separates an amateur and a professional data scientist who gets paid?
The answer is: Results.
Can you build high performing models with those same machine learning tools at your disposal?
In this project, we'll arm you the foundational concepts and skills needed to succeed in the data science field.
Key concepts include:
- What it takes to train professional-level models
- Why model complexity lies at the heart of applied machine learning
- How to use simulations to cut your learning curve
- Demo of model fit from simple to complex
- Adding complexity through model parameters
- How to tune models to improve fit
- How to determine which model performs best
Project 3: 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 valuate houses accurately and spot good deals!
In this project, we'll apply machine learning to create a pricing model using data from thousands of homes.
Key concepts include:
- How to plan an efficient ML workflow
- Practical comparison of regression algorithms
- How to perform exploratory analysis like a pro
- 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 of course: review of previous concepts!
Project 4: Chief People Officer
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.
Key concepts include:
- How to apply supervised learning to solve valuable business problems
- Practical comparison of classification models
- How to perform feature engineering like a pro
- The easiest way to avoid overfitting your model
- How to evaluate models with error metrics
- Smart shortcuts that can save you hours of work
- And of course: review of previous concepts!
Project 5: Unsupervised Customers
Successful businesses create win-win situations with their customers. One way is to create better customer segments, which allow them 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 find customer segments from an online retail dataset.
Key concepts include:
- How to apply unsupervised learning to solve valuable business problems
- Practical comparison of clustering models
- How to perform dimensionality reduction
- Easy, yet effective ways to visualize your data
- How to extract business insights from your data
- Advanced techniques for data wrangling
- And of course: review of previous concepts!
Project 6: To the Stars!
Once you've gotten to this final project, you will be fully equipped with professional-level data science skills. It's time to take full command of the ship and soar as high as you wish while adding an impressive and unique project to your portfolio.
From here on, the sky's the limit.
In. this final capstone project, we will help you design, create, and then showcase your own project.
Key concepts include:
- How to use a project planning funnel to scope out your very own project
- Where to find awesome open datasets to use
- A complete execution checklist that will guarantee a fruitful project
- How to host your project on Github and add it to your resume or portfolio
- All of the possibilities that lie ahead and what you can do to supercharge your career
Earn a unique digital certificate you can print, frame, add to LinkedIn, or your other online profiles. These certificates use bank-level encryption and are recorded on the blockchain, making them impossible to fake.
Our 30-Day "Snail Shell" Guarantee
In 2003, a new species of snail was discovered near the hostile hydro-thermal vents of the Indian Ocean. These snails have unique 3-layer "super shells" that protect them from ocean predators and from their harsh habitat.
We offer you a similar 3-layer "super shell" guarantee!
Within 30 days of purchase...
- If you are disappointed with the projects...
- If you don't feel like you're learning useful skills...
- Or even if you just hate the font we use in the course materials...
Simply email us for a full refund, no questions asked.
Who Would Love This Course?
This course is designed for busy people who want a No B.S. way to learn in-demand DS & ML skills to supercharge their career.
See how machine learning applications directly translate to business value.
Skip the math and jump straight to the best tools and industry best practices.
Tackle real-world problems and build an impressive portfolio that will open doors.
Most importantly, this is for self-starters who prefer to "learn by doing." You will gain real DS & ML skills in the shortest time possible, period.
Let's recap why you'll love this course:
#1. You won't waste your time — Skip the math and discover how to get results in the shortest time possible. You'll learn the practical intuition needed to apply ML in your work.
#2. You'll accelerate your career — Every project is from the real business world. The skills you learn will allow you to open more doors and command a higher salary.
#3. You'll have a ton of fun — You’ll “play and learn” at the same time with these interactive Jupyter Notebooks. Don’t settle for dense textbooks or long lectures.
#4. You'll complete 6 awesome projects — Hands-on learning is the best way to master machine learning. Plus, these projects are perfect for your portfolio and resume.
#5. You'll learn from real professionals — This course is direct, opinionated, and down-to-earth. Skip the vague ponderings of academics and learn how to get results.
#6. You'll gain top-notch skills — This course is laser focused on practical skills. There’s no better way to learn practical, applied machine learning in the shortest time possible.
Frequently Asked Questions
Do I need to know Python or have coding experience to take this course?
Do I need a math or computer science background to take this course?
How much time is required to complete this course?
How does this course compare to other options out there?
What if I don't like the course?
Will this course help me become a data scientist or ML engineer?
Here's What Students Are Saying
98% of past students would recommend the Machine Learning Accelerator to others looking to gain practical machine learning and data science skills.
"Differentiator for me 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.
Investment Banking Analyst, USA
"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.
Software Developer, Canada
"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!
Marketing Analytics, UK
"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.
Business Analyst, USA
"I learned how to solve problems in an efficient way"
Nuclear Engineer, South Korea
"This is at least my 5th pass at learning this material"
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.
BI Analyst, 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.
University Professor, USA
"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.
Freelance Developer, Canada
"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.
PhD Student, Argentina
"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.
Financial Analyst, Portugal
"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.
"More confidence to look for data projects"
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.
Financial Engineer, USA
"This is not introduced in other courses like Datacamp or Udemy"
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.
Data Architect, Jordan
"Slowly 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. 🙂
Electronics Engineer, UK
"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!