- Chapter 1 – Introduction to ML: Learn what machine learning is, along with its real-world applications and impact. Start drawing the line between hype and reality when it comes to ML.
- Chapter 2 – Types of Machine Learning: Discover the different types of learning – supervised, unsupervised, semi-supervised and reinforcement learning. Explore where and why we use each type.
- Chapter 3 – Data Preprocessing: Understand how ML algorithms learn from data. Learn about data cleaning, data transformation, and data splitting for training and testing.
- Chapter 4 – Supervised Learning Algorithms: Journey into the world of popular supervised learning algorithms. Explore regression, decision trees, and k-nearest neighbours methods.
- Chapter 5 – Unsupervised Learning Algorithms: Learn about popular unsupervised learning algorithms. Dive into clustering, dimensionality reduction, and association rule learning.
- Chapter 6 – Introduction to Neural Networks: Get a beginner-friendly intro into neural networks and their role in ML. Touch on the basics of deep learning.
By the end of this course, you’ll trade in your fear of ML for a newfound excitement, ready to dive deeper into this compelling field. Let’s start making machines smarter!