The 'academic' component of the EE Program covers multiple pillars of the GenWise Curriculum. These curricular elements will be covered over 2 weeks (4-5 hrs/ day), as follows:
Week 1: Mathematics, Science, Design and Technology (STEM Focus)
Week 2: Nature, Society &Individual; Tools for Thinking & Communication (Humanities Focus)
Please click on each week to know (MUCH) more...
While children are free to pick either week, we strongly recommend a balanced exposure to the content over both weeks.
Data, Visualization, and Statistics for Citizens
Given that the world is awash with data, understand the tools available for analysis and visualization, and the nuances around signal-noise ratio, errors to avoid, from the perspective of a citizen data scientist!
For Ei ATS Scholars; for students in Grades 8/9/10 in 2022-23
Here are couple of relevant quotes from one of the pioneers of the turnaround of the Japanese auto industry, Dr W Edwards Deming, through a philosophy of collecting, and analysing relevant data, and taking decisions based on the conclusions.
- "Without data, you are just another person with an opinion"
- "In God we trust; all others must bring data"
The world is today awash with data. Data Scientist roles are unfilled in every part of the world. While business has moved ahead, governments and civil society have to catch up and keep pace. India has made strides by making available thousands of datasets from its various ministries, open to analysis and visualisations - from health, to education, social justice, agriculture, natural resources, and more. See here.
An informed citizen data scientist not only helps analyze the raw data, supplemented with visualisations, but also is able to better intrepret such analyses/ visualizations presented to him/ her.
This course covers the following:
- Set the context for what is possible using available data
- An overview of the statistical concepts/ tools that underly data and analysis
- Interpreting the quality of the conclusions (signal/noise ratio, possible errors we need to seek to avoid, reliability, etc.), which is at the heart of all statistical analysis
The format for interaction will be a mix of in-class lectures, hands-on assignments, and DIY projects.