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.
Working with Pandas: Data Manipulation for AI Projects
Master Pandas for AI and machine learning projects. Learn DataFrames, data cleaning, filtering, grouping, merging, and feature engineering with comprehensive examples and explanations.
Essential Python Libraries for Machine Learning: A Complete Overview
Discover the essential Python libraries for machine learning including NumPy, Pandas, Scikit-learn, Matplotlib, and TensorFlow. Learn what each library does and when to use it with practical examples.
