About This Course

This course provides a comprehensive introduction to the foundational concepts, tools, and data science techniques. It explores the data science lifecycle, from problem formulation and data collection to modeling, evaluation, and deployment. Students will learn about data types, data cleaning and preparation, and the critical role of exploratory data analysis (EDA) in uncovering insights.

The course emphasizes hands-on experience with essential tools like Python, R, Pandas, and visualization libraries, enabling students to analyze and communicate data effectively. Key topics include descriptive statistics, probability, machine learning basics, and the ethical implications of data science in modern society.

Through real-world case studies and interactive projects, students will develop problem-solving skills and gain insights into practical applications across healthcare, finance, and marketing domains. By the end of the course, students will be well-prepared for advanced data science courses and professional roles in this dynamic field.