This 27-hour Data Science course is designed for absolute beginners and provides a deep dive into the field of Data Science and AI. The course starts with Python programming fundamentals, introducing essential libraries such as Pandas, NumPy, Matplotlib, and Seaborn, which are critical for data manipulation, analysis, and visualization.

Students then explore foundational concepts in statistics, probability, and data exploration to develop a strong understanding of data-driven decision-making. Hands-on exercises and projects are emphasized throughout the course, allowing learners to practice working with real-world datasets, performing data cleaning, transformation, and visualization.

The program also covers machine learning, including supervised learning (regression and classification), unsupervised learning (clustering, dimensionality reduction), and introductory deep learning concepts. Learners gain practical experience building predictive models and applying them to solve real-world problems.

By the end of this extensive course, participants will have the skills to analyze complex datasets, create meaningful visualizations, build machine learning models, and apply Data Science techniques to business and research scenarios. This course is ideal for beginners, students, and professionals seeking a comprehensive foundation in Data Science and AI.