Description
Machine Learning A-Z: AI, Python & R is one of the most popular machine-learning courses globally, designed by expert data scientists to teach ML models, concepts, and coding in a simple and practical way. With hands-on tutorials in both Python and R, the course walks you through preprocessing, regression, classification, clustering, reinforcement learning, NLP, deep learning, dimensionality reduction, and model selection. Each section is independent, letting you learn linearly or jump directly into the topics you need. Real case studies, downloadable templates, and step-by-step guidance help you build real-world ML models confidently.
What You’ll Learn
- Build machine learning models in Python and R
- Develop strong intuition for a wide range of ML algorithms
- Make accurate predictions and perform robust data analysis
- Apply ML techniques to real business cases
- Work with regression, classification, clustering & association models
- Implement reinforcement learning, NLP & deep learning
- Use dimensionality reduction (PCA, LDA, Kernel PCA)
- Perform model selection, cross-validation & XGBoost
- Learn how to choose the best model for each problem
- Build and combine multiple ML models for advanced solutions
Who This Course Is For
- Anyone interested in learning machine learning
- Students with basic high-school math looking to start in ML
- Beginners who know a little ML and want to expand
- Learners uncomfortable with coding but eager to apply ML
- College students preparing for data science careers
- Data analysts wanting to advance into ML
- Professionals aiming to bring ML solutions into their business
Course Specifications
Publisher: Udemy
Teachers: Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Ligency Team
Language: English
Level: All Levels
Lectures: 386
Duration: 42 hours and 44 minutes
Prerequisites
- High-school level mathematics
File Size: 8.8 GB