Data Workshop: No Code AI for Data Engineers and Operators (In Boston and Online)


Jul 27, 02:00PM PST(09:00PM GMT).
  • Virtual Ikigai Labs
  • Free 61 Attendees
Description
Speaker

We are excited to partner with Ikigai labs to host the in-person meetup in MIT campus in Boston and Online

Data professionals (analysts, scientists, operators, …) utilize data to extract insights from it and subsequently make decisions that impact day-to-day operations as well as long-term strategy for organizations. The process of going from data to insights and using decisions typically involves (a) extracting data from varied structured and unstructured sources; (b) normalizing, cleaning, and stitching such varied data sources to obtain “ground truth”; (c) extracting structure within data, interacting with it, visualizing it to obtain insights; (d) predicting, optimization, doing scenario analysis to make decisions, and (e) automating all of the above while allowing for human in the loop intervention.

In this hands-on workshop, we shall discuss all of these with the help of illustrative datasets in a low-code / no-code AI environment.

Agenda:

  • 5PM~5:30PM EST: check in, networking with food/drink (in-person)
  • 5:30PM~7:30PM: Tech talks/workshops (in-person & online)
  • 7:30PM~8PM: Q&A and mingle
  • Attend options:
    - In person at MIT campus: register on Meetup for venue details
    - Online: click RSVP to receive zoom joining link.

    Devavrat Shah

    Devavrat Shah is an Andrew (1956) and Erna Viterbi professor of Computer Science and AI at MIT since 2005 where he founded MIT Statistics and Data Science Center and currently directs Deshpande Center for Tech Innovation. Currently, he serves as the CTO of Ikigai Labs which he co-founded in 2019, with the mission of building self-driving organization by empowering data business operators to make data-driven decisions with ease of spreadsheets
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