Workshop on

Cracking Data Science Interviews
Jan
22
22nd Jan, 6:30 AM - 7:30 AM (GMT+00:00)

By Sundeep Teki, PhD

This event ended 4 months ago.

By Sundeep Teki, PhD

About the workshop

★ In this Ask Me Anything workshop, I will shed light on the various types of data science interviews at the big tech companies and startups and how they evaluate and score candidates' performance for each interview:

  • Coding (Python/SQL)

  • Coding (ML)

  • ML Depth & Breadth

  • ML Systems Design

  • Product Sense

  • Behavioural

★ I'll share tips from my experience coaching 50+ data scientists who received job offers at FAANG (US) at companies like Apple, Facebook, Amazon, LinkedIn, Twitter, Pinterest.

★ I'll introduce my new cohort-based course, Data Science Career Accelerator, aimed at empowering candidates to crack data science interviews at FAANG and top tech startups.

This workshop is for:

Seeking your first job in Data Science? You could be a software engineer, recent STEM graduate, or a data professional transitioning to Data Science.

Seeking the top jobs in Data Science? You could be current data scientists, managers or ML engineers aiming to crack interviews at FAANG and top tech startups

What you’ll learn:
  • Evaluate the various types of data science interviews
  • Evaluate whether you are ready to crack these interviews
  • Learn how top tech companies evaluate interview performance
  • Meet your host

    Sundeep Teki, PhD

    Sundeep is a leader in AI & Neuroscience with 14+ years of experience across Big Tech (Amazon Alexa AI, USA), Startups (Swiggy, India), & Academia (Oxford & UCL, UK). He has built AI-powered products; hired and interviewed multiple data scientists; successfully coached 50+ data science candidates who got jobs at FAANG companies in the US; published ~75 papers & blogs; advised tech startups on AI & Data; mentored 100+ candidates.

    Workshop on
    Cracking Data Science Interviews

    Going live at

    22nd Jan, 6:30 AM - 7:30 AM (GMT+00:00)

    This event ended 4 months ago.

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