Fundamentals of Machine Learning
A beginner friendly, hands on course that introduces the fundamentals of Machine Learning using Python. Learners will build essential programming and data handling skills, explore core ML concepts, and practice preparing data, training models, and evaluating their performance using Google Colab.
- Istabraq Sameer
- Beginner
- ~30h
- Arabic & English
- Updated Oct 2026
What you'll learn
- Python fundamentals
- data handling and preprocessing
- exploratory data analysis
- essential machine learning libraries
- supervised learning concepts
- regression and classification
- model training
- model evaluation
- working with real datasets
- building predictive models
- applying the complete machine learning workflow using Google Colab
About this course
(Fundamentals of Machine Learning) is a practical beginner friendly course designed to build a strong foundation in Machine Learning using Python. The course introduces learners to essential Python concepts, data handling and preprocessing, core Machine Learning principles, supervised learning, model training, prediction, and performance evaluation. Through hands-on practice using Google Colab, learners will work with real datasets, explore key Python libraries, and apply a complete Machine Learning workflow from preparing data to building and evaluating predictive models. The course is designed to bridge theory and practice and prepare learners for more advanced topics in Machine Learning and Artificial Intelligence.
Curriculum
0 modules · 0 lessons · ~30h total
Requirements
- No prior programming or machine learning experience required
- basic computer literacy
- willingness to learn Python and work with data
- access to a Google account for Google Colab
Who this course is for
- University students
- programmers who want to enter the ML field
- anyone interested in learning how to work with data and build predictive models using Python
Your instructor
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