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Course 3
Supervised Machine Learning

A hands-on course on building predictive models that learn from labeled data to make accurate forecasts and decisions.
  • Level: Intermediate +
  • Prerequisite: Essentials of Data Analysis
  • Time to Complete:  2-3 Months 
  • Course Availability:  6 Months 
  • Videos (to date):  46 / 110
  • Assessments:  60
  • PPT Slides: 1000 
  • Author: Eng. Walid Semaan

What's The Course About

  • Overview

    Supervised Machine Learning Models introduces learners to the core algorithms used for prediction and classification using labeled data.

    The course covers simple and multiple logistic regression, discriminant analysis, decision trees, Naive Bayes, support vector machines, and k-nearest neighbors, while also teaching training and testing methodologies, model evaluation metrics, and complete AI prompt workflows that allow participants to apply machine learning independently.

  • Topics Covered

    1. Supervised learning basics
    2. Train-test methodology
    3. Logistic regression
    4. Discriminant analysis
    5. Decision trees
    6. Naive Bayes
    7. SVM and KNN
    8. Model evaluation

Course Lessons

Instructor

Eng. Walid Semaan

    Walid Semaan is an MIT-certified data scientist and AI business strategist with four verified certificates in Data Science and Machine Learning, Machine Learning with Python, Artificial Intelligence for Business Strategy, and Natural Language Processing. He is the founder and president of Matrix TRC’s Data Science and AI Academy, developed two extensive university programs in partnership with American University of Science and Technology and the Lebanese American University, where he co-leads the executive diploma in Data Science, Deep Learning, and AI Solutions in partnership with SAS.
    Walid holds degrees in engineering (ESIB), finance and marketing (ESCP), and an MBA from Paris-Dauphine–Sorbonne. He is the creator of the award-winning Triple One Analytics AI platform, recognized as Best Innovative ICT Project at the Arab Golden Chip Awards in 2011. With more than 100 international executive training missions and thousands of teaching hours across master’s programs and Ph.D. research.
     He has trained and advised leading institutions worldwide, including the Central Bank of Lebanon, PwC (Dubai), SCAD (Abu Dhabi), Smart Dubai, OXY Petroleum (Oman), Sanofi–Merck Group (Amsterdam), and the Ministry of Health (KSA), among many others. His passion lies in equipping professionals and organizations with advanced Data Science and AI tools to drive innovation and impact.