Machine Learning Bootcamp: Build ML models using GenAI

About this course

If you’re an aspiring data scientist, analyst, or AI enthusiast looking to break into one of the most in-demand fields of the decade, imagine having a hands-on guide that teaches you not only the theory—but also how to code, implement, and fine-tune models—without getting lost in complexity. What if you could accelerate your learning curve by having an AI partner (ChatGPT) that helps you write cleaner code, debug faster, and understand concepts more intuitively?In this immersive, practical bootcamp, you’ll gain the technical skills, problem-solving mindset, and project experience needed to work confidently with real-world machine learning applications. Whether you’re building predictive models, classifying data, or tuning advanced algorithms, this course equips you to move from “learning about ML” to “building with ML” in record time.In this hands-on course, you will:Master the full ML workflow – from data import, exploration, and preprocessing to model building, evaluation, and optimization.Understand the math and logic behind key algorithms like Linear & Logistic Regression, Decision Trees, Random Forests, KNN, SVM, Boosting methods, and more.Learn with ChatGPT-assisted coding – using AI to generate, optimize, and debug Python code for faster, more accurate implementation.Work with Python’s top ML libraries like NumPy, Pandas, Seaborn, Scikit-learn, and XGBoost.Build both regression and classification models and understand when to apply each.Gain experience in advanced topics like model tuning with Grid Search, feature engineering, ensemble methods, and kernel-based SVMs.Throughout the course, you’ll:Use ChatGPT to write and refine Python code for ML tasks.Explore side-by-side the theory of an algorithm and its real Python implementation.

Course objectives

• equip students with the ability to build predictive and classification models
• teach advanced techniques like model tuning and feature engineering