This course offers a comprehensive introduction to Machine Learning (ML) using Python. Learn the core concepts, algorithms, and techniques to build predictive models and solve real-world problems with data. Gain hands-on experience with popular libraries and tools like scikit-learn, Pandas, NumPy, and Matplotlib.
Key Topics:
Introduction to Machine Learning concepts
Data preprocessing and visualization
Supervised learning algorithms (regression, classification)
Unsupervised learning algorithms (clustering, dimensionality reduction)
Model evaluation and performance metrics
Advanced ML topics and real-world case studies
By the end of the course, you'll be equipped with the skills to build, evaluate, and deploy machine learning models using Python.