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

• 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

• 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

• Conditional statements (if, elif, else)
• Looping structures (for, while)
• Writing and calling functions
• Understanding scope and local vs. global variables
• Recursion and recursive functions

• Reading and writing to files with python
• Understanding system directories, filename an file path
• Changing system directories with the terminal

• 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

• Introduction to object-oriented programming (OOP)
• Classes and objects
• Inheritance and polymorphism
• Encapsulation and data hiding
• Advanced OOP concepts (abstract classes, interfaces)

• Understanding and handling exceptions
• Exception handling using try-except blocks
• Raising and catching exceptions
• Debugging techniques and tools
• Logging and error handling strategies

• 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

• 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

• 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

• 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

Brian Obot [email protected]