MACHINE LEARNING AND AI – Beginners

Unlock the world of Artificial Intelligence and Machine Learning with this beginner-friendly course! Whether you’re a student, aspiring data scientist, or tech enthusiast, this course gives you a solid foundation in AI, ML, and Data Science—with zero fluff and full clarity.

You’ll start with the basics of AI, including what AI is, its various subsets (Machine Learning, Deep Learning, Computer Vision, Reinforcement Learning), and how they relate to each other. From there, we dive deep into the role of Data Science in modern AI applications.

This course simplifies complex topics like:

• Linear and Multiple Linear Regression
• Cost Functions & Gradient Descent
• Polynomial Regression
• Support Vector Machines (SVM)
• Decision Tree Regression
• Random Forest Algorithm
• K-Means Clustering

All with real-world examples, visual explanations, and formula breakdowns to ensure practical understanding.

No prior coding experience or math-heavy background is needed. This course is designed to make concepts intuitive and actionable—so you not only understand the theory but know how to use it.

What You’ll Learn:

• What is AI and its key subsets (ML, DL, CV, RL)
• Supervised vs Unsupervised Learning
• Real-world applications of AI/ML
• How data science powers machine learning
• Build and understand linear & multiple linear regression models
• How cost functions and gradient descent work
• Decision Trees, Random Forests & SVMs explained simply
• Basics of clustering with K-Means