# Young Data Scientist Book: Inspiration for the future

Focussing on ages 14 to 17, this book uses the space exploration for Data Science. Ultimate initiative of this book is to create an open curriculum to teach Data Science in schools.

### Introduction

How can we give every student a head-start for future Data science jobs?

How can we inspire students today to take up Data Science?

‘Data Scientist’ is one of the most important future STEM jobs. Yet, Data Science is not an easy discipline to get started in – especially for students.

Focussing on ages 14 to 17, Young Data Scientist inspires learners to take up Data Science – giving them a head start to future careers and jobs.

Created as a Crowd funding initiative, the project will be delivered as code, book, community and videos.

### Approach of Book

• In essence, Data Science involves solving problems using data. Students need inspiring problems.
• We believe space exploration is a great problem domain to teach Data Science.
• Space unites humanity. Space related problems are inspiring and provide a great context for learning Data Science
• The book is inspired by conversations (arguments!) which my 11 year old has with ‘Siri’ i.e. what if you could introduce these concepts (i.e. learning Data Science) as a conversation between a person and a Deep learning computer?
• The problem is ‘understanding and predicting the weather on Mars’ based on data from the Nasa Phoenix mission which you can see HERE
• The dataset corresponds roughly to a Martian day, contains unprocessed values of pressure and temperature data, and was collected continuously at a data rate of 2 sec. We’ll visualize how temperatures change periodically, convert it from Kelvin to Celsius, and try to find a relation between temperature and pressure according to the law of Physics. Since there are values without a physical meaning we have to clean the data, find minimum and maximum values for temperature and pressure, plot the cleaned data and evaluate our ‘weather’ prediction.
• Currently being developed using Python based code using libraries (Pandas, scikit-learn etc)

The book has three parts

Part One:  A dialogue between the student and the Deep learning Computer. This will be based on real engagement with students.

Part Two: Implementation (code, Design etc)

Part Three: Advice from Data scientists based on interviews with Data Scientists.

Print Book \$19.99 + postage
ebook:  \$9.99
Video : \$49.99
Course with certificate \$99.99

### Wider vision

Ultimately, the Young Data Scientist initiative aims to create an open curriculum to teach Data Science in schools.

The wider vision is to create an ongoing, open source based curriculum – as a foundation. Thus, any teacher – anywhere in the world – could download, adapt and translate the content. The big picture: A child in rural Africa gets access to the content in her own language – masters it – and grows up to join Google, Microsoft etc. i.e. the ability to truly transform lives.

Bio: Ajit Jaokar (@AjitJaokar) work spans research, entrepreneurship and academia relating to IoT, predictive analytics and Mobility. His current research focus is on applying data science algorithms to IoT applications. This includes Time series, sensor fusion and deep learning. This research underpins his teaching at Oxford University (Data Science for Internet of Things) and the City sciences program at the Technical University of Madrid (UPM).

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