Course Description

This comprehensive course will equip you with the essential Python skills needed for data science and machine learning. You’ll learn about key libraries and techniques used for data manipulation, analysis, and building predictive models.

Course Outcome:

Module 1: Python Fundamentals

• Python syntax and basic data structures (variables, data types, control flow)
• Functions and modules
• Object-oriented programming

Module 2: NumPy and Pandas

• NumPy for numerical operations and arrays
• Pandas for data manipulation and analysis
• Data structures (Series, DataFrames)
• Data cleaning and preprocessing

Module 3: Data Visualization

• Matplotlib for creating plots and charts
• Seaborn for statistical visualizations
• Interactive visualizations with Plotly

Module 4: Machine Learning with Scikit-learn

• Introduction to machine learning
• Supervised learning (regression, classification)
• Unsupervised learning (clustering, dimensionality reduction)  
• Model evaluation and selection

Module 5: Natural Language Processing (NLP)

• Text preprocessing
• Text classification
• Sentiment analysis
• Natural language generation

Module 6: Time Series Analysis

• Time series forecasting
• ARIMA models
• Seasonal decomposition
• Time series visualization

Course Projects:

• Analyse a real-world dataset using Python libraries
• Build a machine learning model for a specific problem
• Create data visualizations to communicate insights