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Amazon India launches machine learning programme to push tech skills

The programme is open to engineering students in their pre-final/final year of Bachelors, Masters or PhD studies across select tech campuses in 2021

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In a move to push Machine Learning (ML) skills among students, Amazon India, a fully-owned subsidiary of US-based e-commerce giant Amazon, has announced the launch of ML Summer .

According to Amazon India, a batch of students from select tech campuses in India will be presented with the opportunity to engage through virtual classroom tutorials followed by interactive Q&A sessions with scientists at Amazon.

For students with prior exposure to certain areas of ML, the programme can act as a refresher course, while additionally providing a practical perspective on ML applications in industry, the company said in a statement.

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“With the pace of advancements in ML, we are proactively helping students to learn about the latest trends in the field of ML and apply them to solve real-world problems,” Rajeev Rastogi, VP, at Amazon said.

“Our aim is to prepare students for science roles — this will help to reduce the gap between the growing demand for ML roles across companies and the talent pool with applied ML skills,” he added.

The programme ML Summer School is open to students in their pre-final/final year of Bachelors, Masters or PhD studies across select tech campuses in 2021. Participants of ML Summer School will be identified through an online assessment.

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They will also have access to the Amazon Research Days (ARD) conference where they can learn about technology trends in the industry through presentations from renowned ML leaders around the world.

The curriculum of ML Summer School will cover the fundamental concepts in ML while linking them to practical industry applications through an immersive three-day course.

Students will get to learn first-hand how advanced ML techniques such as Deep Learning and Probabilistic Graphical Models can be leveraged to solve specific business problems in the e-commerce domain such as demand forecasting, catalogue quality, product recommendations, search ranking and online advertising.

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