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Schedule

Day 1

Session 0 (0830 - 0930)

  • Installation

Session 1 (0930 - 1115)

  • Overview of Data Science
  • Data Science Process
  • How to use Jupyter Notebook
  • Intro to Data Structures in R

Session 2 (1135 - 1300)

  • Case 1: Peeling the Onion
  • Exploring Onion Price and Quantity

Session 3 (1400 - 1530)

  • Fun visualization exercise
  • Modelling the Onion data
  • Communicating the Onion Insights

##3 Session 4 (1550 - 1730)

  • Acquiring the Onion data (Web Scraping)
  • Refining the Onion Data

Optional Advanced Session (1730 - 1830)

  • Working with SQL to Acquire and Refine Data
  • Real life Scraping
  • Office Hours

Day2

Session 5 (0930 - 1115)

  • Reflections
  • Intro to Machine Learning
  • Case 2: Kitna Deti Hain
  • Linear Regression

Session 6 (1135 - 1300)

  • Case 2: Continued

Session 7 (1400 - 1530)

  • Fun Demo : Music Visualization
  • Case 5: Bank Marketing
  • Decision Trees for Classification
  • Logistic Regression for Classification

Session 8 (1550 - 1730)

  • Bank Marketing (contd.)
  • Recap and Way Forward
  • Feedback

Food and Hydration

0830 - 0930: Breakfast

1115 - 1135: Tea Break

1300 - 1400: Lunch

1530 - 1550: Tea Break