Data Storytelling
By the end of this course, learners should be able to explain Lesson 1: Set up Python for data work
Embark on your learning journey with Data Storytelling. This course is designed to be accessible to beginners while providing enough depth to challenge experienced learners.
You'll gain hands-on experience through interactive coding exercises, quizzes, and real-world projects. Our community forum provides support whenever you need it.
Invest in your future today and join the next generation of African tech leaders.
What you will learn
- By the end of this course, learners should be able to explain Lesson 1: Set up Python for data work
- By the end of this course, learners should be able to explain Lesson 2: Jupyter notebooks and workflows
- By the end of this course, learners should be able to explain Lesson 3: NumPy arrays and vectorization
- By the end of this course, learners should be able to explain Lesson 4: Load datasets with Pandas
- By the end of this course, learners should be able to explain Lesson 5: Explore data with summary statistics
Skills you will develop
Data storytelling
Skills you’ll develop
Course completion demonstrates these skills. Verification requires assessment or reviewed challenge work.
What you will build and prove
- Practice: Practice: Lesson 1: Set up Python for data work
- Project: Apply Data Storytelling
- Quiz: Lesson 1: Set up Python for data work check (pass 70%)
- Final assessment: Data Storytelling — course assessment (pass 70%)
Course journey
How this free course is structured — watch, practise, and progress module by module.
- Introduction & Setup
- Core Concepts
- Hands-On Practice
- Intermediate Techniques
Practice
1 optional practice exercise — apply what you learned. Practice is not required to complete the course.
Assessment
- Lesson 1: Set up Python for data work check · pass mark 70%
- Data Storytelling — course assessment · pass mark 70%
Prove
Course completion means finishing required lessons , and the course assessment . That grants a certificate of completion — not a professional certification. Optional practice does not block completion.
Curriculum
Week 1: Introduction & Setup
- Lesson 1: Set up Python for data work Preview Practice 15min
- Lesson 2: Jupyter notebooks and workflows Preview 17min
- Lesson 3: NumPy arrays and vectorization 25min
- Lesson 4: Load datasets with Pandas 15min
- Lesson 5: Explore data with summary statistics 10min
Week 2: Core Concepts
- Lesson 1: Data science project workflow 16min
- Lesson 2: Visualize insights with charts 24min
- Lesson 3: Feature engineering basics 21min
- Lesson 4: Train a simple predictive model 8min
Week 3: Hands-On Practice
- Lesson 1: Data science project workflow 10min
- Lesson 2: Visualize insights with charts 15min
- Lesson 3: Feature engineering basics 22min
- Lesson 4: Train a simple predictive model 16min
- Lesson 5: Evaluate model quality 19min
- Lesson 6: Communicate findings clearly 21min
Week 4: Intermediate Techniques
- Lesson 1: Data science project workflow 17min
- Lesson 2: Visualize insights with charts 12min
- Lesson 3: Feature engineering basics 21min
- Lesson 4: Train a simple predictive model 8min
Free to enroll — no purchase required.
Instructor: Africoders
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