22-25 April 2026 
Data Science and Analytics: Real-World Experience from Diverse voices in the field
2022TL; DR
In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.
Session Details
In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.
Join this lively and interactive session to hear from the speakers to learn practical examples on how to be a more successful data scientist. Bring your questions for discussion!
Feedback Link - https://sqlb.it/?7023
Join this lively and interactive session to hear from the speakers to learn practical examples on how to be a more successful data scientist. Bring your questions for discussion!
Feedback Link - https://sqlb.it/?7023
3 things you'll get out of this session
Speakers
Gavita Regunath
medium.com/@gavi.sr
Gavita Regunath's other proposed sessions for 2026
AgentBricks vs Mosaic AI - 2026
Gavita Regunath's previous sessions
Automated Machine Learning on Azure
AutoML which stands for Automated Machine Learning empowers data teams to quickly build and deploy machine learning models. It aims to reduce the time and expertise required to generate a machine learning model by automating the heavy lifting of preprocessing, feature engineering, model creation, tuning and evaluation.
When it comes to machine learning in Microsoft Azure, there are two main options for running your AutoML: (1) Azure Machine Learning Service and (2) Azure Databricks. This session will aim to introduce how to develop ML models using AutoML on both platforms, as well as the features of each and why you would choose one over the other.
How to get started with Computer Vision AutoML in Azure
In this talk, we will be leveraging Azure computer vision. The Azure Computer Vision is part of Azure Cognitive Services that provides pre-built, advanced algorithms that process and analyse images.
If you want to get started with computer vision but do not know where to start, then this talk will give you a good starting point to jumpstart your computer vision journey. You will leave this talk with an understanding of how to build and deploy your own computer vision models using Azure computer vision.
Keynote by The Community
Ben and Rob have found some wonderful folk to actually do the important parts of the community keynote. on the theme of
How to be a nonpassive member of the data community
AutoML: An Introduction To Get You Started
Understand how to get started with any machine learning project using Databricks AutoML
Tori Tompkins
toritompkins.co.uk/blog
Tori Tompkins's other proposed sessions for 2026
AgentBricks vs Mosaic AI - 2026
No Code Agents with AgentBricks - 2026
Real-Time AI with Databricks Online Feature Stores: Powered by Lakebase - 2026
Unlocking the Potential of Retrieval-Augmented Generation (RAG) with Advanced Patterns - 2026
You Think Your MLOps Can Scale GenAI? Think Again. - 2026