Understanding Data Types and Structures in Python
Master Python data types and structures for AI projects. Learn integers, floats, strings, lists, dictionaries, sets, tuples with practical machine learning examples and best practices.
Data Cleaning and Preprocessing Fundamentals
Master data cleaning for machine learning. Learn to handle missing values, remove duplicates, fix data types, detect outliers, and prepare clean datasets with Python and Pandas.
Reading and Writing Data: CSV, JSON, and Beyond
Master data input/output for machine learning. Learn to read and write CSV, JSON, Excel, SQL databases, Parquet, and other formats with Python, Pandas, and best practices.
Version Control for AI Projects: Git and GitHub Essentials
Master Git and GitHub for AI and machine learning projects. Learn version control fundamentals, branching, collaboration, and best practices for data science workflows with practical examples.
Introduction to Jupyter Notebooks for AI Experimentation
Master Git and GitHub for AI and machine learning projects. Learn version control fundamentals, branching, collaboration, best practices, and how to manage ML code, data, and models effectively.
