The Machine Learning A-Z Bundle
With Jeff Li and Ken Jee
What’s Included in the Bundle?
The heavy lifting of an ML model includes the end-to-end process. In this course series, Jeff Li and Ken Jee walk you step by step from algorithm to productionization and beyond, so you can successfully take your next project from start to finish. You’ll learn everything you need to set up your projects for success. Gain a deeper understanding of machine learning and when you should and shouldn’t use this powerful tool.
Machine Learning Training Designed with Your Practical Needs in MindLearn the practical skills you need when working on ML models in a real-world environment. This bundle of structured courses prepares you for the world of data science and supplements your learning with links to additional resources and flashcards to help you retain the information in the long term.
The Machine Learning Process A-Z
There is so much more to data science than just model tuning. This course covers the entire end-to-end machine learning process—from scoping the problem all the way to its productionization.
- 01 Course Introduction 12 Lessons
- 02 Intro to Machine Learning 10 Lessons
- 03 The Modeling Process 07 Lessons
- 04 Data Collection 06 Lessons
- 05 Data Preprocessing 13 Lessons
- 06 Exploratory Data Analysis for ML 15 Lessons
- 07 Feature Engineering 27 Lessons
- 08 Cross Validation 12 Lessons
- 09 Feature Selection 06 Lessons
- 10 Dealing with Imbalanced Data 09 Lessons
- 11 Modeling 07 Lessons
- 12 Model evaluation 17 Lessons
- 13 Productionization 03 Lessons
- 14 Conclusion 01 Lessons
Machine Learning Deep Dive: Business Applications and Coding Walkthroughs
Practical Machine Learning: From Basic Algorithms to Advanced Real-World Applications
- 01 ML Business Use Cases 09 Lessons
- 02 Coding Walkthroughs 25 Lessons
The Machine Learning Algorithms A-Z
Learn the intuition behind the most popular ML algorithms, understand the pros and cons of each, and choose the best one for the problems you need to solve.
- 01 Course Introduction 05 Lessons
- 02 Linear Regression 17 Lessons
- 03 Ridge, Lasso, Elastic Net 12 Lessons
- 04 Logistic Regression 14 Lessons
- 05 Gradient Descent 09 Lessons
- 06 Decision Trees 14 Lessons
- 07 Random Forest 14 Lessons
- 08 Gradient Boosted Trees 13 Lessons
- 09 XGBoost 08 Lessons
- 10 K Nearest Neighbors 09 Lessons
- 11 K-Means Clustering 12 Lessons
- 12 Hierarchical Clustering 09 Lessons
- 13 Support Vector Machines 14 Lessons
- 14 Artificial Neural Nets 13 Lessons
- 15 Collaborative Filtering - Non-Negative Matrix Factorization 15 Lessons
- 16 Naïve Bayes 10 Lessons
- 17 Practical projects 02 Lessons
Who Can Benefit from This Bundle?
These courses are the perfect learning tool for machine learning students and aspiring data scientists and a helpful additional resource for practitioners who work on ML models.
This Course Gives You Lifetime Access to
Certificate of AchievementPass the exam, showcase your skills, and bolster your data science credentials.
Self-Paced LearningEnjoy maximum flexibility and forget about cramming against the clock.
Q&A HubNo need to do it alone – our community of learners and instructors is there for you.
Resume BuilderWrite a sharp and professional resume in minutes and impress employers.
User DashboardLearn with a sense of purpose. Track your progress, set daily goals, and make success a routine.
Course MaterialsGet unlimited access to all course materials, downloadable resources, and content updates.
What You’ll Learn
Many courses jump right into the algorithms, but Jeff and Ken teach you the essential skills needed to leverage machine learning into actual results. They code all algorithms from scratch to show you the inner workings of building an ML model and how to perform data preprocessing, engineer your model’s features, and productionize your project.
- The end-to-end ML process
- Feature engineering
- Data preprocessing techniques
- Data exploration and analysis framing
- Model tuning and productionization
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Enjoy Lifetime Access.
One-time payment. Lifetime access to all course materials and updates.
16,231 Students Have Joined the Course!
Frequently Asked Questions
What does ‘billed once’ mean for this course?
Unlike a Premium subscription to our platform (billed monthly or annually), acquiring individual courses requires a one-time payment. The course is hosted by 365 Data Science and comes with extra perks like a resume builder, user dashboard, Q&A hub, and gamified features.
Can I access other courses on the platform when I buy this one?
Our limited-time offer covers individual course purchases only. If you’re interested in the entire curriculum on our platform or want to enroll in a more extensive career track, consider continuing your data science journey with one of our subscription plans.
Do I have a time limit for completing the course?
Purchasing this course makes it yours forever. There is no time requirement for completing the modules or assignments. All perks and materials are accessible indefinitely—even after you complete the course. The only timed component is the exam. Whether you pass or fail, you can retake it limitless times. But you must watch at least 30 minutes of video content before each attempt.
How do I get a Course Certificate?
All enrolled students have access to the course exams—no matter how many lessons they’ve watched. You receive a Course Certificate if you get an exam score of 60% or above. Your certificate of achievement is generated automatically once you pass the exam; you can download, view, and share it anytime.
How long will my certificate be valid?
Your Course Certificate has no expiration date. Once you pass the exam, it’s yours forever. You’ll never need to worry about validity issues or retaking the course (unless you wish to refresh your knowledge).
Do I need prior experience or an academic degree to take the course?
No, there are no prerequisites for enrolling. Everything you need to know is included in the course. Unlike other platforms which usually consider mathematics and statistics as prerequisites, we offer beginner-friendly content. We explain it all step by step, including how to download and install the necessary software, e.g., Anaconda, Jupyter Notebook, Python, R, MySQL, Tableau Public, etc.