Course Overview
Introduction: This Python programming course is designed to provide participants with a comprehensive understanding of Python, covering the essentials from basic syntax and structure to advanced concepts and real-world applications.
Course Objectives:
- Understand the fundamentals of Python syntax and structure.
- Master essential programming concepts using Python.
- Develop the ability to write, compile, and debug Python programs.
- Learn and apply industry standards and best practices in Python programming.
- Gain skills to integrate Python with other languages and libraries.
Target Audience:
- Programmers and developers with basic knowledge of any programming language.
- IT professionals seeking to enhance their programming skills.
- Students pursuing a career in software development.
Prerequisites: Basic knowledge of any programming language.
Duration: 8 Weeks (Self-paced)
Delivery Method: Self-paced Online Course
Course Code: PYTHON_COURSE_2024
Course Cost: Recommended cost per delegate: $2000 for the entire course. This cost includes all training materials, lab access, and certification.
Week 1: Introduction to Python
Theory:
- Introduction to Python
- Why Program
- What are programs
- What is the importance of programs
- What type of programs should you expect to create
- Hardware Architecture
- Hardware requirements
- Hardware optimizations
- Pros and cons of hardware specs
- Hardware limitations
- Python as a Language
- What is Python
- What is an interpreter
- What is object-oriented programming
- What is a dynamically typed language
- Elements of Python
- What makes Python different
- What are the pros and cons of Python
Practical Lab Exercises:
- Setting Up Python Environment
- Writing and Running Your First Python Program
Q&A and Review
Interactive session to address questions and review key concepts.
Week 2: Variables and Expressions
Theory:
- Variables
- How to create variables
- Variable types
- Variable scopes
- Expressions and Statements
- Standard expression syntax
- Standard statement syntax
- Intermediate expression syntax
Practical Lab Exercises:
- Creating and Using Variables
- Writing Expressions and Statements
Q&A and Review
Interactive session to address questions and review key concepts.
Week 3: Conditional Executions
Theory:
- Control Structures
- What is a conditional structure
- Scopes of conditional structures
- Conditional execution
- If Statements
- What is an if statement
- When to use an if statement
- Scope and syntax
- Switch Statements
- What is a switch statement
- When to use a switch statement
- Scope and syntax
Practical Lab Exercises:
- Implementing If Statements
- Using Switch Statements
Q&A and Review
Interactive session to address questions and review key concepts.
Week 4: Functions
Theory:
- Functions
- What is a function
- Creating functions
- Other function types
- Scope and applicability of functions
- Best practices
Practical Lab Exercises:
- Developing Functions
- Applying Best Practices in Function Development
Q&A and Review
Interactive session to address questions and review key concepts.
Week 5: Loops and Iterations
Theory:
- Loops and Iterations
- What is a loop
- What is an iteration
- Use cases of loops and iterations
- For Loops
- What is a for loop
- Where it applies
- Use cases and syntax
- While Loops
- What is a while loop
- Differences between for and while loops
- Where it applies
- Syntax, break, and continue
- Iterators
- What is an iterator
- Iter and next methods
- Where they apply
- Syntax
Practical Lab Exercises:
- Implementing For Loops
- Creating While Loops
- Using Iterators
Q&A and Review
Interactive session to address questions and review key concepts.
Week 6: Strings and File Handling
Theory:
- Strings
- What are strings
- Mutable vs immutable strings
- Concatenating strings
- String types and operators
- String methods
- File Handling
- Overview of file handling
- Reading files
- Writing to files
- Closing files
- Other file types
Practical Lab Exercises:
- Manipulating Strings
- Reading and Writing Files
Q&A and Review
Interactive session to address questions and review key concepts.
Week 7: Data Structures
Theory:
- Lists
- What is a Python list
- How lists work
- Lists and data types
- Dictionaries
- What is a Python dictionary
- How to use a dictionary
- Popular dictionaries and their applications
- Tuples
- What are tuples
- How to create tuples
- Applications of tuples
- Modifying and organizing tuples
Practical Lab Exercises:
- Working with Lists
- Implementing Dictionaries
- Creating and Using Tuples
Q&A and Review
Interactive session to address questions and review key concepts.
Week 8: Capstone Project
Theory:
- Project Planning
- Defining the project scope and objectives
- Choosing tools and technologies
Practical Lab Exercises:
- Developing the Project
- Applying Learned Concepts
Presentation:
- Presenting the Project
- Peer Review and Feedback
Q&A and Review
Final interactive session to address questions and review key concepts.
Week 9: Debugging and Testing
Theory:
- Debugging Techniques
- Common debugging methods
- Using debuggers in Python
- Testing
- Unit testing
- Integration testing
- Test-driven development
Practical Lab Exercises:
- Debugging Python code
- Writing and running tests
Q&A and Review
Interactive session to address questions and review key concepts.
Week 10: Advanced Topics
Theory:
- Concurrency and Parallelism
- Introduction to concurrency
- Using threads and multiprocessing in Python
- Data Science with Python
- Overview of data science tools
- Using pandas and NumPy
- Introduction to machine learning
Practical Lab Exercises:
- Implementing concurrency in Python
- Data manipulation with pandas
- Basic machine learning tasks
Q&A and Review
Final interactive session to address questions and review key concepts.
Assessment and Certification
Assessment Overview: Description of assessment methods.
- Assignments: 40%
- Quizzes: 20%
- Capstone Project: 40%
Certification: Criteria for course completion and awarding of certificates.