Module 1

Python Basics

    Data types, variables, control structures, functions, modules.
    File input/output operations.
    Exception handling
Module 2

Data Science Libraries

    NumPy:Numerical computing
    Pandas: Data manipulation and analysis
    Matplotlib: Data visualization
    Scikit-learn: Machine learning
Module 3

Data Visualization

    Plots, charts, graphs, heatmaps
    Customization options.
    Interactive visualizations
Module 4

Machine Learning

    Supervised, unsupervised, reinforcement learning
    Regression, classification, clustering, decision trees
    Model evaluation metrics
Module 5

Data Preprocessing

    Data cleaning, feature scaling, normalization
    Handling missing values
    Data transformation
Module 6

Data Analysis

    Data manipulation, filtering, grouping, sorting
    Data merging, joining, reshaping
    Data summarization, aggregation