1. What is analytics & Data Science?
2. Common Terms in Analytics
3. Analytics vs. Data warehousing, OLAP, MIS Reporting
4. Relevance in industry and need of the hour
5. Types of problems and business objectives in various industries
6. Overview of analytics tools & their popularity
7. List of steps in Analytics projects
8. Identify the most appropriate solution design for the given problem statement
9. Project plan for Analytics project & key milestones based on effort estimates
10. Build Resource plan for analytics project
11. Why R and Python for data science?