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Course 4: Unsupervised Machine Learning

A course on extracting hidden patterns, structures, and groupings from unlabeled data.
  • Level: Intermediate +
  • Prerequisite: Essentials of Data Analysis
  • Time to Complete: 2-3 Months 
  • Course Availability: 6 Months 
  • Videos (to date): 0 / 88
  • Assessments: 0/60
  • PPT Slides: 760
  • Author: Eng. Walid Semaan

What's The Course About

  • Overview

    Unsupervised Machine Learning helps learners discover hidden structures, patterns, and segments within unlabeled data.

    The course covers algebra foundations, principal component analysis, matrix factorization, multidimensional scaling, t-SNE, recommender systems, simple correspondence analysis, and clustering techniques including agglomerative clustering, k-means, k-medoids, and Gaussian mixture models.

  • Topics Covered

    1. Essentials of Algebra
    2. Principal Component Analysis
    3. Matrix factorization
    4. Multidimensional scaling
    5. t-distributed Stochastic Neighbor Embedding (t-SNE)
    6. Recommender systems
    7. Correspondence analysis
    8. Clustering methods

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.