Python Training Course for Learners

Python Course: 10-Week Plan

Overview: A Python course, with one module per week and two sessions each. The first session covers concepts and the second is hands-on practice. Each session runs about 90 minutes (10 min recap, 20 min concept walkthrough with live coding, 20 min guided exercises, 10 min weekly assignment). The tools are VS Code and Django.

Week 1: Setup and Environment

• Session 1: How code runs, what Python is used for, installation and PATH.
• Session 2: Set up VS Code or IDLE, run the first program, troubleshoot installation problems.
• Deliverable: “Hello, World!” running on the learner’s machine.

Week 2: Core Fundamentals

• Session 1: Variables, naming rules, data types.
• Session 2: input(), output, operators.
• Deliverable: A simple calculator, such as a bill splitter or tip calculator.

Week 3: Control Flow and Logic

• Session 1: if/elif/else, comparison and logical operators.
• Session 2: for and while loops, break and continue.
• Deliverable: A number guessing game.

Week 4: Core Data Structures

• Session 1: Lists and tuples.
• Session 2: Dictionaries and sets.
• Deliverable: A contact book or to-do list.
• Checkpoint: A short quiz on fundamentals and data structures.

Week 5: Functions and Modularity

• Session 1: def, parameters, return values.
• Session 2: Scope, and refactoring earlier programs into functions.
• Deliverable: The Week 2 to 4 projects rewritten using functions.

Week 6: Object-Oriented Programming

• Session 1: Classes, objects, attributes, methods, __init__, self.
• Session 2: The four pillars of OOP, with small examples.
• Deliverable: A bank account or library system.

Week 7: Error Handling and File I/O

• Session 1: Reading stack traces, try/except/finally.
• Session 2: Reading and writing .txt and .csv files.
• Deliverable: An expense tracker that saves to a file.
• Checkpoint: A mini-assessment combining functions, OOP and file handling.

Week 8: Data Science Basics (Part 1)

• Session 1: Core concepts: what data science is and how data is structured.
• Session 2: Pandas DataFrames and basic statistics.
• Deliverable: Load a small CSV and summarize it.

Week 9: Data Science Basics (Part 2)

• Session 1: Charts and visualization basics.
• Session 2: Guided analysis: clean a small CSV and plot a trend.
• Deliverable: Analyze a small CSV and plot one trend.

Week 10: Web Development with Django and VS Code

• Session 1: Django basics: project, app, URLs, views and templates.
• Session 2: Build the Home and About pages and run the site locally in VS Code.
• Deliverable (capstone): A working two-page Django site.
• Checkpoint: Capstone demo, with the learner presenting their site.