Python for Web Development and Problem Solving

Week 1: Advanced Functions and Lambda Expressions

• Understanding higher-order functions and lambda expressions
• Applying functions in data processing
• Activity: Write a program that filters a list of numbers using a lambda function.

Week 2: Working with Files and Directories

• Reading, writing, and managing files and directories
• Practical use of file handling in real projects
• Mini Project: Create a program that organizes files into folders based on file type.

Week 3: Introduction to Data Structures

• Understanding sets, dictionaries, and other complex structures
• Using data structures for efficient storage and retrieval
• Activity: Build a program that tracks a library’s book collection.

Week 4: Milestone Project

• Project: Create an address book application that saves and loads contacts to/from files.

Week 5: Introduction to Data Science Libraries

• Working with pandas for data analysis
• Basic data manipulation
• Activity: Analyze a sample dataset to find key insights.

Week 6: Data Visualization with matplotlib

• Creating graphs and visualizations
• Practical applications of data visualization
• Mini Project: Create a program that visualizes a dataset with bar charts and line graphs.

Week 7: Introduction to APIs

• Fetching data from public APIs (e.g., weather, news)
• Using JSON format to work with external data
• Activity: Build a program that fetches and displays weather data for a selected location.

Week 8: Milestone Project

• Project: Create a “Personal Dashboard” app that shows weather, news, and other information fetched from APIs.

Week 9: Basics of Machine Learning

• Introduction to supervised learning and regression
• Using scikit-learn to create simple models
• Activity: Build a model that predicts a numerical outcome based on a small dataset.

Week 10: Building and Evaluating Models

• Training and testing models
• Evaluating model accuracy and performance
• Mini Project: Create a model that predicts house prices based on given data.

Week 11: Neural Networks and AI Basics

• Basics of neural networks and deep learning
• Using a simple neural network for classification
• Activity: Train a small neural network to classify data.

Week 12: Final Project and Showcase

• Final Project: Develop a machine learning project, such as a model that categorizes images or analyzes text.
• Presentation: Students showcase their AI models,