Artificial Intelligence Course Curriculum



Paul Adeyemi
AI Engineer / Data Scientist

Afolabi Faruq
AI Expert / Programmer
12 Review


  • Modules 6
  • Topics 40
  • Duration 80 hours
  • Skill level Advance
  • Language English
  • Students 4
  • Assessments Yes
  • Hybrid class Yes
  • Certification Yes
Course Description

This course teaches what every student should know about Artificial Intelligence. AI is a fast-moving technology with impacts and implications for both our individual lives and society as a whole. In this course, students will get a basic introduction to the building blocks and components of artificial intelligence, learning about concepts like algorithms, machine learning, and neural networks. Students will also explore how AI is already being used, and evaluate problem areas of AI, such as bias. The course also contains a balanced look at AI’s impact on existing jobs, as well as its potential to create new and exciting career fields in the future. Students will leave the course with a solid understanding of what AI is, how it works, areas of caution, and what they can do with the technology.


You'll earn a diploma certification based on your ability to develop a autoresponding machines that can carry out task by itself without human interferance. The certificate will portraite you as a professional AI engineer.

Learning Outcomes
  • Describe what is AI, its applications, use cases, and how it is transforming our lives
  • Describe several issues and ethical concerns surrounding AI
  • Explain terms like Machine Learning, Deep Learning and Neural Networks
  • Articulate advice from experts about learning and starting a career in AI s
Skills You'll Gain
  • Artificial Intelligence (AI)
  • Data Science
  • Machine Learning
  • Deep Learning

Course Curriculum

  •   Introduction to Artificial Intelligence

    •         What is AI? History, types, and applications
    •         Basic concepts: decision making, search, knowledge representation, reasoning
    •         Ethical considerations and societal impact of AI
  •   Foundations of Machine Learning

    •         Supervised learning (regression, classification): algorithms, evaluation metrics
    •         Unsupervised learning (clustering, dimensionality reduction): algorithms, applications
    •         Ensemble methods and advanced topics (boosting, bagging)
  •   Python Programming for AI

    •         Introduction to Python: syntax, data structures, control flow
    •         Libraries for AI: NumPy, Pandas, Scikit-learn, TensorFlow
    •         Practical coding exercises with real-world datasets


Paul Adeyemi
Data Scientist/AI Engineer (Lead Tutor)

Paul Adeyemi is an AI engineer and a Data Scientist who practice what he does best at VOKS Technologies since 2018

Faruq Afolabi
Programmer/AI Expert

Afolabi Faruq is a programmer and a AI expert who practice what he does best at VOKS Technologies since 2018



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