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AI (Artificial Intelligence) · All levels · English

Machine Learning training Karu/Bwari, Abuja

12 lessons · about 140 hours · certificate on completion · updated 14/04/2026

What you'll learn

  • To understand the fundamental principles of Machine Learning for data-driven insights
  • Learn how to prepare and engineer features for machine learning models
  • Understand supervised and unsupervised learning algorithms
  • Learn how to evaluate and tune machine-learning models
  • Understand advanced topics in machine learning, including neural networks and deep learning
  • Apply machine learning concepts and algorithms to real-world problems

Course content

  • Week 1: Introduction to Machine Learning
  • Week 2: Introduction to Machine Learning (Continued)
  • Week 3: Data Preparation and Feature Engineering
  • Week 4: Data Preparation and Feature Engineering (Continued)
  • Week 5: Supervised Learning Algorithms
  • Week 6: Supervised Learning Algorithms (Continued)
  • Week 7: Supervised Learning Algorithms (Continued)
  • Week 8: Unsupervised Learning Algorithms
  • Week 9: Unsupervised Learning Algorithms (Continued)
  • Week 10: Model Evaluation and Tuning
  • week 11: Natural language processing
  • Week 12: Advanced Topics in Machine Learning

Requirements

  • Basic understanding of Python Programming
  • Basic understanding of Statistics

Description

Course Description:

This 12-week course provides a comprehensive introduction to the field of machine learning, covering both theoretical and practical aspects of machine learning. Students will learn the fundamentals of machine learning, including supervised, unsupervised, and reinforcement learning, and will develop practical skills in preparing and engineering features for machine learning models.


Through a combination of lectures, assignments, and projects, students will learn about supervised learning algorithms, including linear regression, logistic regression, decision trees, and random forests, as well as unsupervised learning algorithms, including K-means clustering, hierarchical clustering, and principal component analysis (PCA). Students will also learn about model evaluation and tuning, including techniques for evaluating model performance, cross-validation, and hyperparameter tuning.


In the final weeks of the course, students will explore advanced topics in machine learning, including neural networks and deep learning. Throughout the course, students will work on practical projects and assignments to apply their knowledge and skills in machine learning, and will complete a final project that demonstrates their understanding of machine learning concepts and algorithms.


By the end of this course, students will have a comprehensive understanding of machine learning concepts and algorithms, as well as practical experience in applying them to real-world problems. This course is ideal for anyone looking to start a career in machine learning or enhance their skills in this field.


Course Outline:


Week 1-2: Introduction to Machine Learning


- Overview of machine learning concepts

- Types of machine learning (Supervised, Unsupervised, Reinforcement)

- Introduction to Python for machine learning


WHAT’S INCLUDED IN THIS MACHINE LEARNING TRAINING COURSE?

World-Class Training Sessions from Experienced Instructors

DURATION |12 WEEKS | 3 TIMES IN A WEEK | 1-2 HOURS | VIRTUAL AND PHYSICAL |KARU & BWARI ABUJA

Instructor

Peter Esiet

₦300,000.00

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