Machine Learning in Python (SciKit-Learn)

Discover how machine learning is transforming the way businesses and organizations make decisions.

This course will help you understand the principles of machine learning, how to implement models in Python using Scikit-Learn, and how to apply these models to real-world data for predictive insights.

You will explore practical examples, learn best practices for model building and evaluation, and understand how to leverage machine learning to solve complex problems.

Key topics include:
Fundamentals of machine learning: supervised and unsupervised learning
Data preprocessing and feature engineering
Building and evaluating models with Scikit-Learn
Algorithms: regression, classification, clustering, and more
Model optimization and cross-validation
Applying machine learning to real-world datasets

Requirements / Prerequisites:
Basic knowledge of Python programming
Understanding of basic statistics and mathematics
Curiosity about data-driven solutions and predictive modeling