Diamond IT Course | Mastering Python: From Beginner to Intermediate

Mastering Python: From Beginner to Intermediate

Course Overview:

This course will teach you Python programming from the ground up. Whether you're a complete beginner or have some experience with coding, this course will help you understand Python's syntax, key concepts, and how to build real-world applications. By the end of the course, you will be proficient in Python and able to tackle a variety of programming challenges.

Target Audience:

• Beginners who want to learn Python programming
• Intermediate learners aiming to strengthen their Python skills
• Developers looking to expand their knowledge in Python

Module 1: Introduction to Python

• Lesson 1.1: What is Python?
  • History and evolution of Python
  • Python’s strengths and use cases
  • Setting up Python on your machine (installation and IDE setup)
• Lesson 1.2: First Steps in Python
  • Running Python scripts
  • Basic syntax and structure
  • Understanding Python’s interactive shell (REPL)
• Lesson 1.3: Variables and Data Types
  • Numbers, Strings, and Booleans
  • Type conversion
  • Basic arithmetic operations
• Lesson 1.4: Control Flow
  • Conditional statements (if, elif, else)
  • Loops (for, while)
  • Breaking out of loops and using continue

Module 2: Working with Data

• Lesson 2.1: Lists and Tuples
  • Creating, indexing, and slicing lists and tuples
  • Common list methods
  • List comprehensions
• Lesson 2.2: Dictionaries and Sets
  • Creating dictionaries and sets
  • Dictionary methods and operations
  • Set operations and their applications
• Lesson 2.3: Strings and String Manipulation
  • String methods and formatting
  • Regular expressions basics
  • String interpolation (f-strings)

Module 3: Functions and Modules

• Lesson 3.1: Functions in Python
  • Defining functions and passing arguments
  • Return values
  • Variable scope (local vs global)
• Lesson 3.2: Advanced Function Concepts
  • Lambda functions
  • Higher-order functions (map, filter, reduce)
  • Recursion in Python
• Lesson 3.3: Modules and Packages
  • Importing standard libraries
  • Creating your own modules
  • Understanding the Python Package Index (PyPI)

Module 4: Object-Oriented Programming (OOP)

• Lesson 4.1: Introduction to OOP

  • Understanding classes and objects
  • Creating classes and defining methods
  • Constructors (__init__)

• Lesson 4.2: Inheritance and Polymorphism

  • Creating subclasses
  • Overriding methods
  • Using super() function

• Lesson 4.3: Encapsulation and Abstraction

  • Private and public members
  • Getters and setters
  • Abstract classes and interfaces

Module 5: File Handling and Error Management

• Lesson 5.1: Reading and Writing Files
  • Opening and closing files
  • Reading from and writing to text files
  • Working with file paths
• Lesson 5.2: Exception Handling
  • try, except, finally blocks
  • Raising exceptions
  • Custom exceptions

Module 6: Advanced Python Topics

• Lesson 6.1: List Comprehensions and Generators
  • Understanding list comprehensions
  • Generator expressions
  • Iterators and the yield keyword
• Lesson 6.2: Decorators and Context Managers
  • What are decorators?
  • Using @staticmethod, @classmethod, and custom decorators
  • Context managers and the with statement
• Lesson 6.3: Multithreading and Multiprocessing
  • The Global Interpreter Lock (GIL)
  • Threading vs Multiprocessing
  • Working with threading and multiprocessing modules

Module 7: Python for Data Science (Optional Advanced Track)

• Lesson 7.1: Introduction to Data Science
  • Python libraries for data science: NumPy, Pandas
  • Data structures for analysis: DataFrames, Series
• Lesson 7.2: Data Visualization with Matplotlib
  • Creating plots and graphs
  • Customizing plots (titles, labels, legends)
• Lesson 7.3: Machine Learning Basics
  • Introduction to scikit-learn
  • Training a simple model (classification, regression)
  • Evaluating model performance

Module 8: Final Project and Next Steps

• Lesson 8.1: Building Your First Python Project
  • Planning and designing your project
  • Coding the project step by step
  • Testing and debugging
• Lesson 8.2: Code Optimization and Best Practices
  • Writing clean and efficient Python code
  • Refactoring and improving performance
• Lesson 8.3: Preparing for Job Interviews
  • Common Python interview questions
  • Problem-solving strategies

Course Features:

• Interactive Quizzes: Test your understanding after each module.
• Coding Exercises: Hands-on coding challenges to solidify learning.
• Final Project: A real-world Python project to showcase your skills.
• Certificate of Completion: Earn a certificate after finishing the course.

This structure ensures a comprehensive understanding of Python, from the basics to more advanced concepts, and prepares students for real-world applications or further specialization in fields like data science or web development.