Python Data Representations course Syllabus

Overview (80-120 words) describing structure and time commitment.

Module 1: Strings and Text Processing

Estimated time: 6 hours

• Work with string methods and slicing
• Extract and clean textual data
• Use regular expressions for pattern matching basics

Module 2: Lists and Dictionaries

Estimated time: 9 hours

• Understand list operations and iteration
• Use dictionaries for key-value data storage
• Apply data structures to organize information efficiently

Module 3: File Handling and Data Parsing

Estimated time: 9 hours

• Read and process data from text files
• Parse structured data formats
• Extract meaningful insights from raw data

Module 4: Practical Applications

Estimated time: 6 hours

• Solve data-related programming problems
• Apply structured thinking to manipulate datasets
• Strengthen readiness for data science and web scraping tasks

Module 5: Final Project

Estimated time: 8 hours

• Design a data processing script using core data structures
• Parse and clean a real-world dataset from a text file
• Generate summary output demonstrating data manipulation skills

Prerequisites

• Familiarity with basic Python syntax and control structures
• Understanding of variables, loops, and conditionals in Python
• Prior exposure to functions and basic data types

What You'll Be Able to Do After

• Understand how data is represented and stored in Python
• Work with strings, lists, dictionaries, and tuples effectively
• Parse and manipulate text data
• Read and process structured data files
• Apply Python data structures to solve real-world problems