“Python for Data Science” is a comprehensive course designed to equip learners with the essential tools and techniques needed in the field. The first session introduces Python, covering basic syntax, data types, control flow, functions, and error handling. It also guides through the setup and usage of Jupyter Notebooks and VS Code, emphasizing their importance in data science workflows. Additionally, the session delves into NumPy, teaching array manipulation, basic operations, and its applications in linear algebra and statistics. Subsequent sessions build on this foundation, covering advanced topics like feature engineering, data visualization with Matplotlib and Plotly, dimensionality reduction techniques like PCA and t-SNE, and the fundamentals of neural networks using PyTorch. The course progresses to specialized topics, including computer vision, deep learning for image and video processing, and working with large language models such as OpenAI’s GPT and Meta’s LLaMA. By the end of the course, participants will have a solid grounding in Python for data science, equipped to handle various data-centric tasks and challenges.