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Programming with Python

This “Python Programming Course” is designed to provide participants with a comprehensive understanding of the Python programming language, covering both the fundamentals and advanced concepts. Such a course is suitable for beginners as well as individuals with some programming experience looking to enhance their skills with Python.   Certificate All GMN courses are easy to […]

Instructor OLAKUNLE BELLO
Updated March 26, 2024

About Course

This “Python Programming Course” is designed to provide participants with a comprehensive understanding of the Python programming language, covering both the fundamentals and advanced concepts. Such a course is suitable for beginners as well as individuals with some programming experience looking to enhance their skills with Python.

 

Certificate
All GMN courses are easy to enrol, study, and complete. To successfully complete this Diploma course and become a GMN Academy Graduate, you need to achieve 75% or higher in each course assessment. Once you have completed this Diploma course, you have the option to acquire an official Diploma which is a great way to share your achievement with the world.

Your GMN Academy Diploma is/can:
Ideal for sharing with potential employers.
Be included in your CV, professional social media profiles and job applications.
An indication of your commitment to continuously learn, upskill & achieve high results.
An incentive for you to continue empowering yourself through lifelong learning.

GMN Academy offers 3 types of Diplomas for completed Diploma courses:
Digital Certificate: a downloadable Certificate in PDF format immediately available to you when you complete your purchase.

Certificate: a physical version of your officially branded and security-marked Certificate, posted to you at a shipping cost.

Framed Certificate: a physical version of your officially branded and security marked Certificate in a stylish frame, posted to you at a shipping cost.

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What Will You Learn?

  • Module 1: Introduction to Python
  • i. Overview of Python: History, features, and applications
  • ii. Installing Python: Setting up Python environment (Anaconda, Python IDEs)
  • iii. Python Basics: Syntax, variables, data types, operators, and basic input/output
  • Module 2: Control Structures
  • i. Conditional Statements: if, elif, else
  • ii. Looping Constructs: for loop, while loop
  • iii. Iteration and Control Flow: break, continue, pass
  • iv. Error Handling: try, except, finally
  • Module 3: Data Structures in Python
  • i. Lists: Creating, accessing, modifying, and slicing lists
  • ii. Tuples: Creating, accessing, and immutable nature
  • iii. Dictionaries: Creating, accessing, modifying, and iterating through dictionaries
  • iv. Sets: Creating, accessing, modifying, and set operations
  • Module 4: Functions and Modules
  • i. Introduction to Functions: Defining and calling functions
  • ii. Function Parameters: Positional parameters, keyword parameters,
  • iii. default parameters, and variable-length parameters
  • iv. Scope and Lifetime of Variables: Global vs. Local variables
  • Modules: Creating and importing modules, organizing code into multiple files
  • Module 5: Object-Oriented Programming (OOP)
  • i. Introduction to OOP: Classes and objects
  • ii. Attributes and Methods: Instance attributes, class attributes, instance iii. methods, class methods, and static methods
  • iv. Inheritance: Creating subclasses, method overriding, and super() function
  • v. Encapsulation: Access specifiers, getter and setter methods
  • Module 6: File Handling and Exception Handling
  • i. File Operations: Opening, reading, writing, and closing files
  • ii. Handling File Exceptions: try-except blocks, finally block
  • iii. Context Managers: with statement for file handling
  • iv. Exception Handling: Handling common exceptions, raising exceptions
  • Module 7: Introduction to Data Science with Python
  • i. Introduction to Data Science: What is data science, its importance, and applications
  • ii. Libraries for Data Science: NumPy, pandas, Matplotlib, and scikit-learn
  • iii. Basic Data Manipulation: Loading data, exploring data, and data cleaning
  • iv. Data Visualization: Plotting graphs, histograms, and scatter plots
  • Module 8: Final Project
  • i. Designing and implementing a Python project from scratch
  • ii. Applying concepts learned throughout the course to solve a real-world problem
  • iii. Project presentation and demonstration

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