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