DataHour: Data to Insightful Actions with No Code AI

DataHour Recording

About the DataHour:

The process of going from data to insights and decisions using AI involves multiple stages

Including:

(a) Connecting to various first and third party data sources.

(b) Prepping, cleaning and stitching them to produce a ground truth.

(c) Interactively visualizing to obtain insights

(d) Advanced analytics for extracting information from unstructured data like text-and-images, predicting, and identifying anomalies.

(e) Scenario analysis to understand various tradeoffs.

(f) Performing action, connecting to downstream systems, alerts and automation. 

Currently, this involves a team of data engineers, scientists, analysts, and business users along with a large number of enterprise tools to make it possible.

In this DataHour, Devarat will discuss how all of these above mentioned stages can be achieved by a business user without requiring a team of data engineers, scientists, or analysts, with no code AI platforms, such as that built by Ikigai Labs, with spreadsheet skills. He will also illustrate the steps involved through a real life example of inventory planning in retail and supply chain.

Prerequisites: Zeal of learning Data Science and Artificial Intelligence

Who is this DataHour for?

• Students & Freshers who want to build a career in the Data-tech domain.
• Working professionals who want to transition to the Data-tech domain.
• Data science professionals who want to accelerate their career growth

Speaker:

Devavrat Shah

Andrew (1956) and Erna Viterbi Professor at MIT

Devavrat Shah is an Andrew (1956) and Erna Viterbi professor of Computer Science and AI at MIT since 2005 where he founded MIT’s Statistics and Data Science Center and currently directs Deshpande Center for Tech Innovation. Previously, he co-founded Celect, focused on inventory optimization using AI (acquired by Nike in 2019). 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. He received his B.Tech. degree from IIT Bombay and his Ph.D. degree from Stanford University, both in Computer Science. He is a Kavli Fellow of National Academy of Science. He has received paper awards from INFORMS Applied Probability Society, INFORMS Management Science and Operations Management, NeurIPS, ACM Sigmetrics and IEEE Infocom. He has received the Erlang Prize from INFORMS Applied Probability Society and Rising Star Award from ACM Sigmetrics. He has received multiple Test of Time paper awards from ACM Sigmetrics. He is a distinguished alumni of his alma mater IIT Bombay.

Connect with Devarat on Linkedin and Website.