Course Overview
This comprehensive course is designed to introduce participants to the Python programming language and equip them with the essential skills to write efficient and effective Python code. Through a combination of theoretical concepts and practical exercises, participants will gain a solid understanding of Python’s syntax, data structures, control flow, functions, and object-oriented programming.
Course Objectives
1. Proficiency in Core Python Programming
Outcome: Students will be able to write efficient Python code using variables, operators, control flow statements (loops and conditionals), and functions.
Skills: Python syntax, conditional logic, loops, modular programming.
2. Mastery of Data Structures and Algorithms
Outcome: Students will be proficient in Python’s built-in data structures like lists, tuples, dictionaries, and sets, and will understand how to apply them to solve complex problems.
Skills: Data manipulation, data storage, problem-solving with data structures.
3. Advanced Object-Oriented Programming (OOP) Skills
Outcome: Students will be able to design and implement object-oriented programs, using classes, inheritance, encapsulation, and polymorphism to build modular, maintainable applications.
Skills: Object-oriented design, inheritance, encapsulation, method overriding.
4. Strong Problem-Solving and Debugging Capabilities
Outcome: Students will effectively handle and debug errors, manage exceptions, and write robust Python code that can handle different types of runtime errors.
Skills: Exception handling, error debugging, writing robust code, using Python debugging tools.
5. Experience with Python’s Advanced Features
Outcome: Students will gain hands-on experience with advanced Python features such as decorators, generators, context managers, multithreading, and regular expressions.
Skills: Writing efficient and reusable code, concurrent programming, handling large data sets, pattern matching with regular expressions.
6. Ability to Build and Deploy Python Applications
Outcome: By the end of the course, students will be able to design, develop, and implement fully functional Python applications, applying all learned concepts in a real-world capstone project.
Skills: Application development, project structuring, debugging, testing, and deployment.
Course Outline
| Module | Topic | Subtopics |
|---|---|---|
| 1 | Introduction to Python | Python installation, IDE setup (Anaconda, Jupyter, PyCharm), basic syntax, variables, data types, input/output |
| 2 | Operators and Expressions | Arithmetic, comparison, logical, bitwise operators, precedence |
| 3 | Control Flow | Conditional statements (if, else, elif), loops (for, while), break, continue, pass, nested conditionals |
| 4 | Functions | Defining and calling functions, parameters, return values, default and keyword arguments, scope and lifetime of variables, problem-solving |
| 5 | Modules and Packages | Importing built-in modules (math, os, random), creating custom modules, understanding Python packages, installing external packages with pip, problem-solving |
| 6 | Data Structures | Lists, tuples, dictionaries, sets, operations, methods, list comprehensions, nested data structures |
| 7 | String Manipulation | String operations and methods, string slicing and formatting, string functions and escape sequences, problem-solving |
| 8 | Regular Expressions | Introduction to regular expressions, searching and matching patterns, character classes, quantifiers, metacharacters, grouping, substitution, splitting strings, problem-solving |
| 9 | File Handling | Reading and writing text files, file modes (r, w, a), working with CSV files, using context managers (with statement), problem-solving |
| 10 | Error and Exception Handling | Understanding try, except, finally blocks, raising and handling custom exceptions, using assert statements, debugging techniques, best practices, problem-solving |
| 11 | Object-Oriented Programming (OOP) – Part 1 | Classes and objects, instance variables and methods, understanding init and self, problem-solving |
| 12 | Object-Oriented Programming (OOP) – Part 2 | Inheritance and method overriding, encapsulation and data hiding, polymorphism, class and static methods, problem-solving |
| 13 | Advanced Functions | Lambda functions, higher-order functions (map(), filter(), reduce()), closures, problem-solving |
| 14 | Iterators and Generators | Understanding iterators and iter(), using next() in loops, introduction to generators (yield), generator expressions |
| 15 | Decorators and Context Managers | Introduction to decorators, creating custom decorators, using and creating context managers, practical use cases for both concepts |
| 16 | Working with Dates and Times | Using the datetime module, formatting dates and times, time arithmetic, working with time zones |
| 17 | Multithreading and Multiprocessing | Introduction to threads and processes, using the threading and multiprocessing modules, synchronizing threads (Lock, Event), parallel processing for performance optimization |
| 18 | Capstone Project | Planning and designing the project, structuring the application, implementing features using Python concepts (OOP, functions, error handling), debugging, testing, and optimizing the code |