Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026]
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DevelopmentMachine Learning

Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026]

4.5
(1,171,398 students)
42h 30m

>_ What You'll Learn

  • Master Machine Learning on Python & R
  • Have a great intuition of many Machine Learning models
  • Make accurate predictions
  • Make powerful analysis
  • Make robust Machine Learning models
  • Create strong added value to your business
  • Use Machine Learning for personal purpose
  • Handle specific topics like Reinforcement Learning, NLP and Deep Learning
  • Handle advanced techniques like Dimensionality Reduction
  • Know which Machine Learning model to choose for each type of problem
  • Build an army of powerful Machine Learning models and know how to combine them to solve any problem

>_ Requirements

  • Just some high school mathematics level.

/ Course Details & Curriculum

Interested in the field of Machine Learning? Then this course is for you! This **Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026] course** has been designed by a Data Scientist and a Machine Learning expert so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way. Over 1 Million students world-wide trust this course. We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This *Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026] course* can be completed by either doing either the Python tutorials, or R tutorials, or both - Python & R. Pick the programming language that you need for your career. This course is fun and exciting, and at the same time, we dive deep into Machine Learning. It is structured the following way: Part 1 - Data Preprocessing Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification Part 4 - Clustering: K-Means, Hierarchical Clustering Part 5 - Association Rule Learning: Apriori, Eclat Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost Each section inside each part is independent. So you can either take the whole course from start to finish or you can jump right into any specific section and learn what you need for your career right now. Moreover, the `Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026] course` is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models. And last but not least, this course includes both Python and R code templates which you can download and use on your own projects.

Author and Instructor

K

Kirill Eremenko, Hadelin de Ponteves, Ligency​, SuperDataScience Team

Expert at Udemy

With years of hands-on experience in Development, Kirill Eremenko, Hadelin de Ponteves, Ligency​, SuperDataScience Team has dedicated thousands of hours to teaching and mentorship. This course is the culmination of industry best practices and a proven curriculum that has helped thousands of students transition into professional roles.

Community Feedback

M

Michael Chen

Verified Enrollment

"This Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2026] course was exactly what I needed. The instructor explains complex Development concepts clearly. Highly recommended!"

S

Sarah Johnson

Verified Enrollment

"I've taken many Udemy courses on Python programming & back-end development, but this one stands out. The practical examples helped me land a job."

D

David Smith

Verified Enrollment

"Great value for money. The section on Machine Learning was particularly helpful."

E

Emily Davis

Verified Enrollment

"Excellent structure and pacing. I went from zero to hero in Development thanks to this course. Lifetime access is a huge plus."

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