This 10-hour Data Scientist course is designed for beginners who want a strong foundation in Data Science and practical skills to work on real-world projects. The course begins with Python programming fundamentals and essential libraries like NumPy, Pandas, Matplotlib, and Seaborn for data manipulation, analysis, and visualization.

Learners explore key concepts in statistics and probability, which are critical for interpreting data and making data-driven decisions. The course emphasizes hands-on practice, enabling students to clean, analyze, and visualize datasets effectively.

The course introduces foundational machine learning concepts, including supervised learning algorithms such as regression and classification, as well as unsupervised learning techniques like clustering and dimensionality reduction. Real-world examples demonstrate how these methods are applied in business and research contexts.

By the end of the course, participants will have practical experience in Python-based data analysis, data visualization, and basic machine learning, equipping them with the skills to pursue a career as a Data Scientist. This course is ideal for students, professionals, and AI enthusiasts who want a structured, hands-on introduction to Data Science and AI.