Python Programming
Build real-world Python applications while mastering data structures, file handling, algorithms, modular programming, and error handling.
Course At a Glance
Category
Programming
Level
Intermediate
Age Group
13–16 years
Prerequisite
Python Fundamentals
Duration
25 Hours
Modules
4 Modules
Program Outcomes
By the end of this course, students will be able to:
- 1
Build complex applications using lists, tuples, and dictionaries to manage structured data.
- 2
Implement file input/output operations and introduce exception handling for robust, error-tolerant code.
- 3
Apply modular design and functional decomposition to build a capstone project.
Data Structures: Lists & Dictionaries
Students move beyond scalar variables into compound data types. They master list operations, methods, slicing, and explore key-value mappings using dictionaries.
| # | Lesson Title | What Students Learn | Activity / Project | Key Concepts / Syntax |
|---|---|---|---|---|
| 1.1 | Lists & Indexing | Create, index, and slice lists. Understand zero-based indexing, negative indices, and list length with len(). | Build: 'Shopping List Manager' — add, view, and count items using list operations. | [], list.append(), len(), slicing [:] |
| 1.2 | List Methods & Operations | Use list methods: append(), insert(), remove(), pop(), sort(), reverse(). Understand mutable vs. immutable data. | Build: 'Leaderboard System' — add scores, sort in descending order, and display the top 3 players. | sort(), reverse(), insert(), remove() |
| 1.3 | Iterating Through Lists | Loop over lists using for item in list and for i in range(len(list)). Combine loops with conditions to search and filter data. | Build: 'Grade Analyzer' — loop through a list of test scores, calculate average, highest, lowest, and count passing grades. | for item in list, sum(), max(), min() |
| 1.4 | Introduction to Dictionaries | Understand key-value pairs. Create dictionaries, access values by key, add/update entries, and check if a key exists using in. | Build: 'Contact Book' — store name: phone pairs. Add, lookup, update, and delete contacts. | {}, dict[key], dict.get(), in |
| 1.5 | Dictionary Methods & Looping | Loop over keys, values, and items using .keys(), .values(), .items(). Work with dictionaries containing nested data. | Build: 'Inventory Tracker' — store item name, quantity, and price. Calculate total inventory value. | dict.keys(), dict.values(), dict.items() |
| 1.6 | Lists of Dictionaries | Combine data structures: store multiple dictionary records in a list. Perform search, filter, and display operations on structured records. | Build: 'Mini Student Database' — list of student dictionaries. Search student by ID and update their grade. | list of dicts, search algorithms |
Advanced Logic & String Manipulations
Students explore advanced string methods, formatting techniques, text parsing, and complex multi-condition logic required for real software applications.
| # | Lesson Title | What Students Learn | Activity / Project | Key Concepts / Syntax |
|---|---|---|---|---|
| 2.1 | String Methods & Formatting | Master string manipulation: .upper(), .lower(), .strip(), .replace(), .split(), .join(). Use f-strings with precision formatting. | Build: 'Text Cleaner & Formatter' — clean messy user input, strip whitespace, and format title case. | str.split(), str.join(), f-strings |
| 2.2 | String Parsing & Analysis | Search text using in, .find(), .count(), .startswith(), .endswith(). Count word frequencies and analyze text length. | Build: 'Word Counter & Analyzer' — count total words, specific keywords, and character distribution in a paragraph. | str.find(), str.count(), str.startswith() |
| 2.3 | Tuples & Sets | Understand immutable tuples () and unique collection sets {}. Learn when to use tuples vs. lists and sets for deduplication. | Build: 'Unique Tag Generator' — clean duplicate tags from a user input list using set operations. | tuple (), set {}, set.add(), set.intersection() |
| 2.4 | Advanced Loop Patterns | Use enumerate() to get index and value simultaneously. Use zip() to iterate over two lists in parallel. | Build: 'Quiz Answer Key Grader' — compare student answers with correct answers using zip() and enumerate(). | enumerate(), zip() |
| 2.5 | Nested Structures & Algorithms | Work with 2D lists (grids/matrices) and nested loops. Understand matrix row/column traversal. | Build: 'Tic-Tac-Toe Board Generator' — create, update, and display a 3x3 game grid using a 2D list. | 2D lists matrix[row][col] |
| 2.6 | List Comprehensions | Write concise list transformations using list comprehensions: [x for x in list if condition]. Compare readable loops vs. comprehensions. | Build: 'Data Filter Utility' — extract even numbers, square values, and filter names starting with 'A' using single-line comprehensions. | [expr for item in list if cond] |
File I/O & Exception Handling
Students connect Python programs to external files. They learn to read and write files safely on disk and handle potential runtime errors using try/except.
| # | Lesson Title | What Students Learn | Activity / Project | Key Concepts / Syntax |
|---|---|---|---|---|
| 3.1 | Reading Text Files | Open files using open() in 'r' mode. Read content with .read(), .readline(), and .readlines(). Use the with open(...) statement for automatic closing. | Build: 'Story Reader' — load an external text file, print lines with line numbers, and count total paragraphs. | with open('file.txt', 'r') as f: |
| 3.2 | Writing & Appending Files | Open files in 'w' (overwrite) and 'a' (append) modes. Write formatted text strings and lists of lines using .write() and .writelines(). | Build: 'Daily Journal App' — prompt user for entry, prepend date/time, and append to journal.txt. | open(..., 'w'), open(..., 'a'), f.write() |
| 3.3 | Working with Structured Data (CSV) | Understand CSV format. Parse comma-separated strings using .split(',') and use Python's built-in csv module. | Build: 'High Scores Saver' — read player names and scores from a CSV file, sort scores, and update the file. | import csv, csv.reader(), csv.writer() |
| 3.4 | Introduction to Exception Handling | Understand runtime errors (FileNotFoundError, ValueError, ZeroDivisionError). Use try and except blocks to prevent program crashes. | Build: 'Crash-Proof Calculator' — handle division by zero and invalid non-numeric user inputs gracefully. | try, except, ValueError, ZeroDivisionError |
| 3.5 | Advanced Try-Except-Else-Finally | Use else (runs if no exception) and finally (always runs). Raise custom exceptions using raise ValueError(...). | Build: 'Robust Input Validator' — function that enforces password criteria and raises descriptive errors on failure. | try, except, else, finally, raise |
| 3.6 | Modules & Standard Library | Organize code into multiple .py files. Import built-in modules: math, random, datetime, os. Create and import your own custom Python module. | Build: 'System Helper Tool' — use os module to check if files exist, datetime to timestamp logs, and custom helper module for math. | import module, from module import func |
Capstone Application Project
Students apply all data structures, file handling, modular functions, and exception handling to design, build, test, and present a complete Python software application.
| # | Lesson Title | What Students Learn | Activity / Project | Key Concepts / Syntax |
|---|---|---|---|---|
| 4.1 | Project Architecture & Specs | Choose a capstone project (Expense Tracker, File Quiz App, or Student Report System). Define data schemas, function hierarchy, and file storage structure. | Design Workshop: Create system diagram, define file storage formats (.txt/.csv), and outline function signatures. | Software Architecture & Design |
| 4.2 | Data Storage & Helper Module | Build data management module: functions to load records from disk, save updates, and validate file integrity with try/except. | Build Session: Complete storage.py helper module with full file persistence and error handling. | File I/O + Exception Handling |
| 4.3 | Core Application Logic | Build business logic functions: search, add, update, calculate statistics, and delete records from memory data structures. | Build Session: Implement core logic functions. Test with unit data samples. | Data Structures + Algorithms |
| 4.4 | User Interface & Menu Loop | Design interactive console CLI menu loop. Connect menu options to core functions with clean validation and feedback. | Build Session: Assemble main.py with interactive menu, formatted output tables, and graceful exit. | CLI Menu Loop + Functions |
| 4.5 | Testing, Refactoring & Edge Cases | Conduct stress testing: invalid inputs, missing data files, edge values. Refactor repetitive code into clean functions. | Refactoring Lab: Perform peer code review, fix all edge-case bugs, and add docstrings/comments. | Code Review & Refactoring |
| 4.6 | Capstone Presentation & Demo Day | Present completed application to class and parents. Demonstrate live file saving, features, and answer technical questions. | Demo Day: 3-minute live software demo + Q&A. Receive verified TeacherColab course certificate. | Portfolio Project Showcase |
Teaching Notes & Tips
Pacing Guidance
Each lesson is designed for 50–60 minutes. Module 2 is the most content-dense — allow extra time for Lesson 2.5 (nested structures). Module 4 lessons run as extended project sessions; flexibility is key.
Differentiation
Advanced students can explore list comprehensions, lambda functions, CSV file handling with the csv module, or basic OOP concepts. Students who need more support should focus on completing core activities before extensions.
Assessment
Each module concludes with a project. Assess on: functionality (does it work?), code structure (functions, meaningful names, comments), error handling (does it crash on bad input?), and presentation clarity.
Tools & Environment
Recommended: VS Code with Python extension (desktop) or Replit (browser-based). Python 3.8+ required for f-strings and walrus operator support. File handling lessons require local file system access — use VS Code or IDLE for these.
Project Options (Module 4)
Option A — Personal Expense Tracker: Add/view/categorise expenses; save to file; show totals by category. Option B — Quiz App with File-Based Questions: Load questions from a .txt file; score the user; save results. Option C — Student Report System: Store, retrieve, and report on student data from a file.
Prior Knowledge Expected
Students should be comfortable with: print(), input(), variables and data types, if/elif/else, for and while loops, basic function definitions with parameters and return values (Python Fundamentals course).
Frequently Asked Questions
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Python Programming · Intermediate · Ages 13–16 · © Course Curriculum