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CapacityBay-Python-Cohort-2

Master Repository to Manage Learning and Assignment for the CapacityBay Cohort 2 Online Course

About the Course

Python Basic Cohort 2, consists of free and finely curated python introductory lessons, that are built and structure to be as useful to all scopes of learners; from people with previous programming background to people completely new to programming and computer technology.

Course Outline:

Module 1: Introduction to Python Programming
  • Overview of Python and its history
  • Setting up the development environment
  • Writing and running your first Python program
  • Understanding Python's syntax and basic data types
  • Working with variables and operators
Module 2: Data Structures
  • Lists, tuples, and dictionaries
  • Accessing and manipulating elements in data structures
  • List comprehensions and generator expressions
  • Sets and their operations
  • Working with files and input/output operations
Module 3: Control Flow and Functions
  • Conditional statements (if, elif, else)
  • Looping structures (for, while)
  • Writing and calling functions
  • Understanding scope and local vs. global variables
  • Recursion and recursive functions
Module 3b: Understanding Filesystem/Directory Operations:
  • Reading and writing to files with python
  • Understanding system directories, filename an file path
  • Changing system directories with the terminal
Module 4: Modules and Packages
  • Introduction to modules and their benefits
  • Creating and importing modules
  • Working with built-in and third-party modules
  • Package management with pip
  • Developing and distributing your own packages
Module 5: Object-Oriented Programming
  • Introduction to object-oriented programming (OOP)
  • Classes and objects
  • Inheritance and polymorphism
  • Encapsulation and data hiding
  • Advanced OOP concepts (abstract classes, interfaces)
Module 6: Exception Handling and Debugging
  • Understanding and handling exceptions
  • Exception handling using try-except blocks
  • Raising and catching exceptions
  • Debugging techniques and tools
  • Logging and error handling strategies
Module 7: File Handling and Data Persistence
  • Reading from and writing to files
  • Working with different file formats (text, CSV, JSON)
  • Serialization and deserialization of objects
  • Database connectivity and basic SQL operations
  • Using SQLite with Python
Module 8: Web Scraping and Automation
  • Introduction to web scraping
  • Parsing HTML and XML documents
  • Extracting data from websites using libraries like BeautifulSoup
  • Automating tasks with Python
  • Interacting with web APIs
Module 9: Introduction to Data Science with Python
  • Overview of data science and its applications
  • Introduction to popular data science libraries (NumPy, Pandas, Matplotlib)
  • Data manipulation and analysis using Pandas
  • Data visualization with Matplotlib
  • Introduction to machine learning with scikit-learn
Module 10: Project Development
  • Collaborative project development
  • Applying Python concepts to a real-world problem
  • Implementing a complete project using Python
  • Best practices for code organization and documentation
  • Project presentation and demonstration

Maintainer

Brian Obot [email protected]