This lecture covers the basics of Python programming, including data types, variables, and control structures. It also includes a guide on setting up Anaconda and Jupyter Notebook, essential tools for data analysis and machine learning.
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Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
