- Introduction to Machine Learning: Learn the fundamentals of machine learning, its applications, and how it’s transforming industries. Understand key concepts such as supervised and unsupervised learning, and the machine learning workflow.
- Data Pre-processing in ML: Master the techniques of preparing data for machine learning models, including data cleaning, normalization, and feature engineering. Explore methods for handling missing data, outliers, and transforming data for optimal performance.
- Machine Learning Algorithms: Dive deep into various machine learning algorithms, including regression, classification, clustering, and more. Understand how algorithms like linear regression, decision trees, k-nearest neighbors, and support vector machines work.
