Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & R

The Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & R course from Udemy teaches you to build, train, and deploy models across Machine Learning (ML), Deep Learning (DL), and Artificial Intelligence (AI). This course focuses on practical application using AWS, Python, and R programming languages. You will learn to implement various models, including Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Regression (SVR), Decision Tree Regression, and Random Forest Regression.

The curriculum also covers Classification models such as Logistic Regression, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Kernel SVM, and Naive Bayes. Beyond supervised learning, the course explores unsupervised learning techniques like Clustering with K-Means and Hierarchical Clustering. You also delve into Association Rule Learning, specifically Data Mining for Market Basket Analysis and Affinity Analysis, and Reinforcement Learning, covering Upper Confidence Bound and Thompson Sampling for CTR Optimization. Data Preprocessing in both Python and R forms a foundational part of the training.

Upon completing this 43-hour self-paced course, you will be able to make powerful analyses and accurate predictions using robust Machine Learning models. The course helps you develop a strong intuition for many Machine Learning models, preparing you to build and deploy them effectively with AWS, Python, and R. It provides code templates to support hands-on learning, guided by instructor Kirill Eremenko from SuperDataScience.

This "All Levels" course is suitable for anyone looking to gain practical skills in Machine Learning, from beginners to those with some experience. If your primary interest lies solely in advanced deep learning concepts, you might also consider the Deep Learning Specialization from Coursera. For a broader introduction to the field of data analysis before specializing in ML, the Google Data Analytics Professional Certificate could be a good starting point. For more options, explore our main Data Science courses hub.