Prompt Engineering Mastery
By the end of this course, learners should be able to explain Lesson 1: AI and ML landscape overview
Master Prompt Engineering Mastery with this in-depth training program designed for the African tech community. Whether you're just starting out or looking to level up your skills, this course provides everything you need.
You'll work on practical exercises that mirror real-world challenges faced by developers and tech professionals. Our step-by-step approach ensures you understand not just the 'how' but also the 'why'.
Join thousands of students who have transformed their careers through our courses.
What you will learn
- By the end of this course, learners should be able to explain Lesson 1: AI and ML landscape overview
- By the end of this course, learners should be able to explain Lesson 2: Supervised vs unsupervised learning
- By the end of this course, learners should be able to explain Lesson 3: Prepare training data
- By the end of this course, learners should be able to explain Lesson 4: Train a baseline model
- By the end of this course, learners should be able to explain Lesson 5: Evaluate accuracy and bias
Skills you will develop
AI literacy · Generative AI · Prompt design
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: AI and ML landscape overview
- Project: Apply Prompt Engineering Mastery
- Quiz: Lesson 1: AI and ML landscape overview check (pass 70%)
- Final assessment: Prompt Engineering Mastery — course assessment (pass 70%)
Course journey
How this free course is structured — watch, practise, and progress module by module.
- Introduction to AI Concepts
- Data Preparation & Cleaning
- Building Your First Model
- Training & Evaluation
- Advanced Algorithms
- Neural Networks
Practice
1 optional practice exercise — apply what you learned. Practice is not required to complete the course.
Assessment
- Lesson 1: AI and ML landscape overview check · pass mark 70%
- Prompt Engineering Mastery — 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 to AI Concepts
- Lesson 1: AI and ML landscape overview Preview Practice 11min
- Lesson 2: Supervised vs unsupervised learning Preview 21min
- Lesson 3: Prepare training data 25min
- Lesson 4: Train a baseline model 13min
- Lesson 5: Evaluate accuracy and bias 16min
Week 2: Data Preparation & Cleaning
- Lesson 1: Feature engineering practice 13min
- Lesson 2: Neural network intuition 10min
- Lesson 3: Work with pretrained models 11min
- Lesson 4: Prompting and LLM basics 20min
- Lesson 5: Guardrails and evaluation 21min
Week 3: Building Your First Model
- Lesson 1: Feature engineering practice 8min
- Lesson 2: Neural network intuition 13min
- Lesson 3: Work with pretrained models 20min
Week 4: Training & Evaluation
- Lesson 1: Feature engineering practice 14min
- Lesson 2: Neural network intuition 23min
- Lesson 3: Work with pretrained models 11min
- Lesson 4: Prompting and LLM basics 20min
- Lesson 5: Guardrails and evaluation 8min
Week 5: Advanced Algorithms
- Lesson 1: Feature engineering practice 23min
- Lesson 2: Neural network intuition 16min
- Lesson 3: Work with pretrained models 17min
- Lesson 4: Prompting and LLM basics 17min
- Lesson 5: Guardrails and evaluation 17min
- Lesson 6: Build a small AI project 18min
Week 6: Neural Networks
- Lesson 1: Feature engineering practice 21min
- Lesson 2: Neural network intuition 21min
- Lesson 3: Work with pretrained models 9min
- Lesson 4: Prompting and LLM basics 19min
- Lesson 5: Guardrails and evaluation 8min
Free to enroll — no purchase required.
Instructor: Africoders
Start learning Already have an account? Sign in Course forum →