About this course
Objectives
Understanding the fundamental concepts, algorithms, and applications of machine learning, and acquiring the knowledge and skills needed to build and deploy basic machine learning models.
Course Outcomes
1. Master fundamental machine learning concepts and terminology.
2. Build and evaluate regression and classification models.
3. Apply clustering techniques through hands-on projects.
4. Enhance critical thinking for problem-solving in diverse scenarios.
5. Demonstrate practical implementation skills in a major project, developing a real-time ads recommendation system.
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Python Fundamentals and Data Structures
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- 0:00 Hr
Introduction to Machine Learning and Regression Models
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Classification Techniques and Project 1
1 Parts
- 0:00 Hr
ID3 Decision Tree Example
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Clustering Techniques and Project 2
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- 0:00 Hr
Introduction to Deep Learning and Major Project
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- 0:00 Hr
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