Introduction to Machine Learning Concepts
Understand the fundamental principles of machine learning, including supervised, unsupervised, and reinforcement learning.
Supervised Learning Algorithms
Master popular algorithms like Linear Regression, Logistic Regression, Support Vector Machines (SVM), and Decision Trees.
Unsupervised Learning Techniques
Explore clustering (K-Means) and dimensionality reduction (PCA) to find hidden patterns in your data.
Introduction to Deep Learning
An overview of neural networks, their architectures, and how they power modern AI advancements.
Essential Machine Learning Tools & Libraries
Get hands-on with Python libraries like Scikit-learn, TensorFlow, and PyTorch for building ML models.