This full course is designed for beginners who want to start their journey in Data Science. The course begins with an introduction to Python programming, covering essential libraries such as NumPy, Pandas, and Matplotlib, which are critical for data manipulation and visualization.

Learners are introduced to fundamental concepts in statistics and probability, which provide the backbone for making data-driven decisions. Through practical examples, you will learn how to clean, analyze, and visualize datasets effectively.

The course also covers the basics of machine learning, including supervised learning techniques like regression and classification, and unsupervised learning methods such as clustering. Each concept is explained with real-world examples and hands-on exercises to reinforce learning.

By the end of the course, participants will have a solid understanding of Data Science fundamentals and practical skills to analyze datasets, visualize insights, and apply basic machine learning models. This course is ideal for students, beginners, and professionals looking to start a career in data analytics, business intelligence, or AI.