SAS
SAS

Generative AI Using SAS | In Person Public Workshop

*S$300 per pax*
Venue: SAS Office, Singapore
Date: July 16 | Time: 1:00 PM - 5:00 PM SGT

 

About

This workshop aims to introduce the exciting new field of Generative AI. It will cover the definition of Generative AI, its place within the broader AI landscape, and the various types of Generative AI technologies along with their industry applications.

Participants will explore the fascinating world of AI creativity, from synthetic data generation and digital twin technology to large language models, including examples of Generative AI from SAS.

The workshop will highlight how generative AI orchestration and large language model (LLM) governance can accelerate productivity. Additionally, it will address the challenge of balancing the risks and rewards associated with AI.

Learn how to:

  • Explain what Gen AI is and how it fits into the broader AI landscape
  • Discuss various types of machine learning that are useful in Gen AI
  • Describe several types of Gen AI systems and technologies
  • Discuss challenges, limitations and considerations of LLMs including hallucinations
  • Explore SAS Gen AI offerings and how to accelerate productivity
  • Examine the AI challenge of balancing risk and reward

Hurry! Limited seats available.

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ABOUT THE SPEAKER


​Dr. Saxena serves as the Principal Analytical Training Consultant at SAS R&D India Pune center. A passionate Data Science enthusiast, he holds certifications as a Machine Learning Specialist and Predictive Modeler. He earned a Ph. D. in Statistics from the School of Studies in Statistics, Vikram University, Ujjain. Committed to continuous learning, he has supplemented his academic journey with short-term courses in related disciplines at the Indian Statistical Institute, Kolkata, and the Indian Institute of Management, Ahmedabad.

With over two decades of experience, Dr. Saxena's professional journey encompasses research, teaching, training, consulting, writing, and education product design. He authored the book "Tree-Based Machine Learning Methods in SAS Viya" and co-authored "Randomness and Optimal Estimation in Data Sampling," published by the American Research Press, USA. Dr. Saxena boasts a portfolio of more than 35 publications, including research papers in esteemed journals like the Journal of Statistical Planning and Inference, Communications in Statistics–Theory and Methods, Statistica, Statistical Papers, and Vikalpa to name a few.