Schedule

Day 1

Session 0: Installation (0830 - 0930)

Session 1: (0930 - 1115) - Amit

Overview of Data Science
Industry Examples
Introduction to Hypothesis Driven Approach
Problem Solving Framework: Frame - Acquire - Refine - Explore - Model - Insight

Session 2: (1145 - 1300) - Amit

Case 1: Peeling the Onion
How to use Jupyter Notebook
Hypothesis: Blah Blah Blah

Session 3: (1400 - 1530) - Nischal

Fun visualisation exercise
Case 2: Hard Disk Data
Descriptive Analytics

Session 4: (1600 - 1730) - Raghottam

Case 2: Hard Disk Data
Predictive Analytics

Optional - Office Hours 1 (1730 - 1830)

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Day 2

Optional - Office Hours 2 (0830 - 0930)

Session 5 (0930 - 1115) - Mr.Rags

Case 2: Hard disk data , predictive analytics

Session 6 (1145 - 1300) - Mr.Barg

Case 3: Twitter descriptive analysis

Session 7 (1400 - 1530) - Mr.Kaps & Mr.Barg

Fun Demo : Music Visualization
Machine Learning - Kaggle BNP Paribas

Session 8 (1600 - 1730) - Mr.Barg

Kaggle
Recap and Way Forward
Techniques (ML, Big Data, Optimization, Deep Learning)
Medium (Text, Network, Image, Big Data, Sensor Data)
Feedback

Food and Hydration

0830 - 0930: Breakfast
1115 - 1145: Tea Break
1300 - 1400: Lunch
1530 - 1600: Tea Break