Course description

ABOUT THE COURSE: This curriculum is developed to help participants appreciate data science and train them to perform data science activities Intended audience: B.Com, B.Sc. graduates, B.Tech/B.E graduates, management studies and working professionals Pre-requisites: Some exposure to high school mathematics and knowledge of programming basics (preferred) Learning Objectives: • Introduce Python as a programming language for data science • Introduce the statistical foundations required for data science • Introduce data visualization techniques • Introduce machine learning algorithms Learning Outcomes: • Describe a flow process for data science problems (Remembering) • Classify data science problems into standard typology (Comprehension) • Develop Python codes for data science solutions (Application) • Correlate results to the solution approach followed (Analysis) • Assess the solution approach (Evaluation) Components of the course: • Videos will be released on a weekly basis • Online live discussions addressing the participants’ doubts, will be held at regular intervals • Each module will have an assignment that must be completed to proceed with other modules • Participants can post their queries on a question and answer forum • Final exam: Participants will be assessed through a combination of command-based Python questions, theoretical, interpretation aspects of the course and solving practical capstone case study using Python