Python Fundamentals: Building a Solid Foundation for Modern Programming

5 days

Python Fundamentals: Building a Solid Foundation for Modern Programming

Welcome to our comprehensive Python Fundamentals course! This course is designed to give you a strong foundation in Python programming, equipping you with the skills and knowledge to write efficient, readable, and powerful Python code.

Python has emerged as one of the most popular and versatile programming languages in the world. Its simplicity, readability, and vast ecosystem of libraries make it an excellent choice for beginners and experienced programmers alike.

Python’s importance in today’s technology landscape cannot be overstated. Python excels as a general-purpose language, suitable for web development, automation, scripting, and software development. Its simplicity makes it ideal for automating repetitive tasks and system administration, saving time and reducing errors in various industries.

Python has also become the de facto language for data science. Libraries like NumPy, pandas, and matplotlib provide powerful tools for data manipulation, analysis, and visualisation.

With libraries such as TensorFlow, PyTorch, and scikit-learn, Python is at the forefront of machine learning and artificial intelligence development. From simple regression models to complex neural networks, Python provides the tools needed for cutting-edge AI research and applications.

Python’s numerical computing capabilities, coupled with libraries like SciPy, make it an excellent choice for scientific computing and research across various fields, from physics to bioinformatics.

Frameworks like Django and Flask have made Python a popular choice for backend web development, allowing for rapid development of robust web applications.

By learning Python, you’re not just learning a programming language; you’re gaining access to a vast world of possibilities in software development, data analysis, artificial intelligence, and more. This course will provide you with the fundamental skills needed to start your journey in any of these exciting fields.

Your Instructor

Your instructor for this course is Peter Munro, a seasoned IT trainer and software developer with over 30 years of experience in the field. Peter’s extensive background spans multiple programming languages and paradigms, but he has a particular passion for Python and its applications in modern software development.

Throughout his career, Peter has helped countless individuals and teams harness the power of Python to solve complex problems and build robust applications. His teaching style combines deep technical knowledge with practical, real-world examples, ensuring that you not only learn the syntax but also understand how to apply Python effectively in various scenarios.

Peter’s goal is to empower you with the skills and confidence to write Python code that makes a difference in your projects or organisation. With his guidance, you’ll learn not just the ‘how’ but also the ‘why’ behind Python programming practices, setting you up for long-term success in your programming journey.

Course Outline

Module 1: Introduction to Python and Setup

Understanding Python’s philosophy and its role in modern software development
Setting up Python development environment (Python interpreter, IDEs, virtual environments)
Writing and running your first Python program
Basic syntax, indentation, and code structure
Using Python’s interactive mode for quick experimentation

Module 2: Python Basics

Variables, data types, and basic operations
Input and output operations
Conditional statements (if, elif, else)
Basic string manipulation

Module 3: Loops in Python

For loops and their applications
While loops and when to use them
Loop control statements (break, continue, pass)
Nested loops and loop else clause

Module 4: Functions in Python

Defining and calling functions
Function parameters and return values
Default arguments and keyword arguments
Variable scope and namespaces
Lambda functions and their uses

Module 5: Error Handling in Python

Understanding exceptions and their role
Using try-except blocks for error handling
Handling multiple exceptions
The finally clause and its importance
Raising exceptions and creating custom exceptions

Module 6: Python Modules and Packages

Understanding modules and their importance
Creating and importing modules
The Python Module Search Path
Creating and using packages
Important built-in modules (os, sys, datetime)

Module 7: Data Structures

Lists and list comprehensions
Tuples and their applications
Dictionaries and sets
Working with strings and string methods
Choosing the right data structure for your needs

Module 8: File Handling and Basic I/O

Reading from and writing to files
Working with CSV files
Basic exception handling in file operations
Context managers and the ‘with’ statement

Module 9: Object-Oriented Programming in Python

Understanding classes and objects
Creating and using methods
Inheritance and polymorphism
Encapsulation and abstraction
Magic methods and operator overloading

Module 10: Introduction to Jupyter Notebooks

Understanding Jupyter Notebooks and their advantages
Setting up and running Jupyter Notebooks
Basic features: code cells, markdown cells, and output
Best practices for using Jupyter Notebooks in data analysis and exploration
Integrating visualisations in Jupyter Notebooks

Module 11: Python Standard Library

Overview of the Python Standard Library
Working with dates and times
Regular expressions for pattern matching
Random number generation and basic statistics
Command-line arguments with argparse

Module 12: Introduction to External Libraries

Installing external libraries with pip
Overview of popular libraries (e.g., requests, pandas)
Reading documentation and using help() function
Creating and managing virtual environments

Module 13: Basic Testing and Debugging

Writing and running unit tests with unittest
Debugging techniques and using Python’s debugger (pdb)
Best practices for code organisation and documentation
Introduction to logging

Module 14: Introduction to Python for Data Analysis

Basic data manipulation with pandas
Simple data visualisation with matplotlib
Reading and writing various data formats (CSV, JSON, Excel)

Module 15: Final Project

Design and implement a small Python application
Apply concepts learned throughout the course
Code review and best practices discussion
Presentation of projects and peer feedback

Conclusion

By the end of this course, you’ll have a solid foundation in Python programming, enabling you to write efficient and effective Python code. You’ll be well-prepared to tackle more advanced topics in Python and start applying your skills to real-world problems in various domains, including software development, data analysis, and machine learning.

Remember, learning to program is a journey, and this course is just the beginning. Keep practicing, exploring, and building projects to reinforce your skills. Happy coding!