The future of data science is changing at a breakneck pace, so we’re working hard to deliver fundamental knowledge to help you navigate this AI-driven world. That’s why we created a bundle of three machine learning courses that prepare you for the future work landscape.
The Machine Learning A-Z Bundle by Ken Jee and Jeff Li is your ultimate navigational chart through this rapidly evolving field. This training isn't just about writing proofs and coding implementations from scratch; it's about defining problems, designing high-level ML solutions, and knowing when (and when not) to use specific algorithms.
Who Is the Machine Learning Course Bundle For?
The bundle is ideal if you’re familiar with machine learning fundamentals and wish to improve your practical skills. The courses are the perfect machine learning training for ML students and aspiring data scientists and a helpful additional resource for practitioners who work on ML models.
You’ll gain valuable insights into the ML process, from scoping the problem to productionization. You’ll learn to apply your coding skills to real-world issues and when and how to use machine learning in business.
What Will You Learn?
These machine learning courses teach you the essential skills to leverage ML into actual results. They prepare you for a real working environment and supplement your learning with links to additional resources and flashcards to help you retain the information in the long term.
The first machine learning course (The Machine Learning Process A-Z) offers a 180-degree overview of the end-to-end ML process. It provides a quick introduction to machine learning and covers topics like:
- Problem framing and data collection
- Data exploration and analysis framing
- Cross-validation
- Data preprocessing
- Feature engineering
- Model tuning and productionization
In the following course (The Machine Learning Algorithms A-Z), Ken and Jeff explain the intuition behind the following ML algorithms and techniques:
- Linear regression
- Ridge, Lasso, Elastic Net
- Logistic regression
- Decision trees
- Random forests
- Gradient boosted trees
- XGBoost
- K-nearest neighbors
- K-means clustering
- Hierarchical clustering
- Support vector machines
- Artificial neural nets
- Collaborative filtering
- Naïve Bayes
The instructors help you understand each algorithm’s assumptions, pros and cons, and the problems they’re suitable for.
In Machine Learning Deep Dive, Ken and Jeff leverage their rich experience and walk you through the practical coding aspects of building ML models and their real-world business applications.
Who Are the Instructors?
This bundle allows you to learn machine learning from versed data science experts.
Ken Jee
Ken has held data science positions in companies of all sizes—from startups to Fortune 100 organizations. In 2021, he also served as an adjunct professor at DePaul University, teaching Advanced Topics in Human-Centered Design. He’s a senior data scientist with people management and recruitment expertise. Thanks to his friendly delivery style and willingness to share knowledge, Ken Jee’s YouTube channel has gained over 245K subscribers—helping individuals worldwide start a career in data science. If you’re into learning and sharing your progress with others, you can also check out Ken’s #66DaysOfData hashtag on LinkedIn.
Jeff Lee
Jeff Li is a senior data scientist passionate about learning new skills and teaching data science. His vast practical experience makes him the perfect teacher for those who want to know how the ML process works. Jeff is a data science manager at a large music streaming platform and is responsible for quarterly planning, opportunity sizing, prioritization, and OKR planning for his team. His team focuses on rebuilding the methodology of a podcast ad inventory model.
Next Steps
With this three-course bundle, we're arming you with today’s in-demand knowledge and skills and preparing you to excel in the future data science world.
You can get this power-packed bundle of machine learning courses for just $79 (a whopping 68% off) until June 29.
And if you wish to acquire other data science and analytics skills, enroll in our learning platform. Sign up for 365 Data Science and try the program for free.
