Amazon India Announces Second Edition of Machine Learning Summer School: Application and Further Details


Amazon India has launched the second edition of Machine Learning (ML) Summer School; a program aimed at giving students the opportunity to learn key ML technologies from scientists at Amazon to prepare them for a career in academia in industry.
What is the duration and the main topics to be covered in the course?
The course, conducted over four weekends in July, offers students the opportunity to gain knowledge of key ML topics including: Supervised Learning, Deep Neural Networks, Sequential Models, Dimensionality Reduction, Unsupervised Learning and two new modules, Reinforcement Learning and causal inference. Attendees also have access to the Amazon Research Days (ARD) conference – an engagement program that takes place every November. ARD connects the scientific community at Amazon, industry leaders and academic researchers in the field of AI around the world.
Amazon will also host the ML Challenge in August, its flagship ML competition, where students can work on an Amazon dataset, bring fresh ideas, and create innovative solutions to a real-world problem. Winning teams will receive pre-placement interviews (PPIs) for ML roles on Amazon along with cash prizes, prizes in kind, and certificates.
How to apply to Amazon Machine Learning Summer School
ML summer school is open to students in the penultimate or final year of their Bachelors/Masters/Integrated Masters/PhD degree enrolled at any campus in India. Eligible students must complete an online assessment that focuses on fundamental ML concepts and math foundations on subjects such as probability, statistics, and linear algebra. The top 3000 students will then be enrolled in the ML Summer School, which will take part in eight virtual classroom sessions over four weekends, with each session followed by live Q&A with scientists on Amazon. ML Summer School attendees can also take the Amazon ML Challenge to practice applying skills and insights gained in modules to solving a real-world problem, the company said.


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