Python For Everyone

Python For Everyone

Learn Python and data analytics from the ground up with 37 practical lessons, pandas, Matplotlib, support, and a certificate.
126 Students
37 Lectures
Maxwell Yaw Twum
Maxwell Yaw Twum

Instructors

Content 37

About This Course

Python For Everyone

Python For Everyone is a practical online Python and data analytics course for beginners across Africa and beyond. It is designed for learners who want to start coding with confidence and use data to answer real questions. No previous programming experience is required.

Begin with the foundations: variables, data types, lists, conditions, loops, functions, user input, and error handling. Each topic is explained step by step, then reinforced with guided exercises so you can practise while you learn.

As your confidence grows, move into real-world data work with pandas and Matplotlib. Learn how to import, organise, clean, analyse, and visualise datasets, including examples drawn from FIFA, employee, and wine data. You will build skills that help you turn raw information into clear insights and useful charts.

The course is self-paced, so you can learn around work, study, or other commitments. It currently includes 37 lessons and approximately 7 hours 30 minutes of learning, alongside downloadable resources, instructor support, a course forum, and a completion certificate.

Use Jupyter Notebook or Anaconda for the practical exercises. By the end, you will be able to write basic Python programs, work with datasets using pandas, and present findings with Matplotlib. The course provides a strong foundation for continued study in data analytics, machine learning, and related digital skills.

You will also learn to approach coding problems methodically: break a task into smaller steps, test your work, read errors, and improve your solutions. This practical mindset is useful whether you are exploring data for study, work, research, or a small business.

Start at your own pace, apply each lesson, and build practical work you can continue developing after the course.

Throughout the course, you will work with examples and exercises that make each concept easier to apply. The aim is steady progress: understand the principle, try it yourself, review the result, and move forward with more confidence.

What you will learn

Build useful tools with Python.

6 Sections - 37 Lessons
01

Write clear Python fundamentals

Apply each concept by building useful programs for real-world problems.

02

Work with data and automate repeatable tasks

Use Python to organise information and automate repeatable tasks.

03

Build useful Python projects

Apply each concept by building useful programs for real-world problems.

Curriculum Overview

This course includes 6 modules, 37 lessons, and 0 hours of materials.

MODULE 1 - GETTING STARTED
5 Parts
Intro Video - Python For Everyone
Free
Volume -
Lesson 1 _ Introduction and Overview of the Course
Volume -
Lesson 2_ Installing Anaconda and Accessing the Jupyter Notebook
Volume -
Slides 1
Volume 2.04 MB
Slides 2
Volume 0.54 MB
MODULE 2 - PYTHON BASICS
7 Parts
Lesson 1 - What are variables?
Volume -
Lesson 2 - Writing our first code
Volume -
Lesson 3 -Data types (integers, floats, strings)
Volume -
Lesson 4 - Data Types - Lists
Volume -
Lesson 5 - More data types (Boolean, Tuples vs lists)
Volume -
Lesson 6 - Arithmetic Operators in Python
Volume -
Lesson 7 - Comparison Operators
Volume -
MODULE 3 - LIST FUNCTIONS
12 Parts
0 - How to Solve Assignments

This video explains the step-by-step processes involved in solving assignments in your Jupyter notebooks.
It talks about, downloading the file, opening it up in your Jupyter and solving it.

Volume -
Lesson 1 - Common Lists Functions - Part 1
Volume -
Lesson 2 - Common list functions - Part 2
Volume -
2.1 - Assignment - Common list functions

This is our first assignment. It is a Jupyter notebook so you have to download and open it in Jupyter.



Please refer to "Lesson 0 - How to Solve Assignments" in this module on a detailed explanation on how to go about Assignments.

Volume 0.005 MB
Lesson 3 - Practical Exercise on Lists
Volume -
Lesson 4 - Indexing
Volume -
Lesson 5 - Commenting
Volume -
Lesson 6 - Slicing
Volume -
Lesson 7 - Using steps in slicing
Volume -
Lesson 8 - Applications of Slicing
Volume -
Slicing for Cropping - Practicals

This is an optional practical of using Slicing for cropping images. If you want to go a step further and explore using slicing for cropping, then you can go ahead. If not you can move on to the next module.



This link contains a video that explains how to go about this step-by-step. After watching it, you can download the Jupyter notebook containing the assignment / exercise and the picture to crop ("lady.jpg")

Volume -
Slicing for Cropping - Data

This is the sample data used i n the slicing for cropping practical session

Volume 0.02 MB
MODULE 4 - CONDITIONAL STATEMENTS
7 Parts
Lesson 1 - Introduction to Conditional Statements
Volume 75 MB
Lesson 2 - More on conditional statements
Volume -
Lesson 3 - Accepting user inputs
Volume -
Lesson 4 - Exercises on conditional statements
Volume -
Lesson 5 - Application - E-Levy Calculator Project
Volume -
Lesson 6 - E-Levy Calculator PT 2
Volume -
Assignment - Grading System

This assignment is for you to apply conditional statements to create an Exam Grading System.



Download the Jupyter Notebook and try your hands on it. All the instructions are in the notebook.

Volume 0.01 MB
MODULE 5 - LOOPS
6 Parts
Lesson 1 - Using the random() function
Volume -
Lesson 2 - Introduction to loops
Volume -
Lesson 3 - Loops - PT 2
Volume -
Lesson 4 - Trial exercises on Loops
Volume -
Lesson 5 - Using the range() function
Volume -
Assignment on Loops
Volume 0.004 MB
Certificates
1 Parts
Course Certificate
Course Certificate
If you pass all the lessons in this course, you will receive this certificate.
Type Course Certificate

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Maxwell Yaw Twum
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1 Courses
6 Students
Maxwell Yaw Twum

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This Course Includes

Downloadable Content
Official Certificate
Instructor Support
Course Forum

Course Specifications

Sections
6
Lessons
37
Capacity
500 Students
Duration
7:30 Hours
Students
126
Created Date
3 Mar 2025
Updated Date
17 Aug 2026

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