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In this episode, our host Arnav Gupta is in talks with Srikanth Varma Chekuri who is the co-founder of Applied AI and Applied Roots. He is a highly accomplished professional with over 13 years of experience in the field of AI and Machine Learning. Currently, he leads the DS/ML vertical at Scaler and is dedicated to empowering every student with the best results.
0:30 Day in the life of Srikanth
03:55 His journey, college and Gate AIR 2
08:37 Getting into Yahoo and his early startup
11:52 Experiences and learnings at Amazon as a Machine learning Scientist
17:07 Starting ed-tech startup Applied Roots
22:45 What is the daily job of a Data Scientist?
28:49 Understanding the need for Data and Problem-Solving Approach
31:21 Arnav's story about a Data Scientist
37:01 Case studies and practical-based learning
40:47 Possible roles in the Data Science field explained
48:39 Different domains of work in DS/ML
51:37 Interview Process for DS, ML jobs
55:21 Tools required for getting started in DSML
58:57 Understanding the Math part of Data Science
1:07:18 Can someone from Non-tech transition and scope ahead in DS, ML
1:08:50 Advice for upcoming Data Science Startups
1:15:07 His take on the future of AI, ChatGPT, and ML
1:22:36 Outro
By Scaler AcademyIn this episode, our host Arnav Gupta is in talks with Srikanth Varma Chekuri who is the co-founder of Applied AI and Applied Roots. He is a highly accomplished professional with over 13 years of experience in the field of AI and Machine Learning. Currently, he leads the DS/ML vertical at Scaler and is dedicated to empowering every student with the best results.
0:30 Day in the life of Srikanth
03:55 His journey, college and Gate AIR 2
08:37 Getting into Yahoo and his early startup
11:52 Experiences and learnings at Amazon as a Machine learning Scientist
17:07 Starting ed-tech startup Applied Roots
22:45 What is the daily job of a Data Scientist?
28:49 Understanding the need for Data and Problem-Solving Approach
31:21 Arnav's story about a Data Scientist
37:01 Case studies and practical-based learning
40:47 Possible roles in the Data Science field explained
48:39 Different domains of work in DS/ML
51:37 Interview Process for DS, ML jobs
55:21 Tools required for getting started in DSML
58:57 Understanding the Math part of Data Science
1:07:18 Can someone from Non-tech transition and scope ahead in DS, ML
1:08:50 Advice for upcoming Data Science Startups
1:15:07 His take on the future of AI, ChatGPT, and ML
1:22:36 Outro

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