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TRAINING
Join us for our in-person training sessions designed to help you enhance your skills in GenAI and LLMs with Ray!
Learn how to build, deploy and scale GenAI and LLM apps with Ray. Learn how to leverage leading GenAI libraries like Hugging Face transformers, LangChain, LlamaIndex and more. Level up your skills through hands-on training sessions with the builders, makers, and maintainers of Ray. Exclusive to Ray Summit attendees, we’re now offering a full day of sessions to keep you on the cutting edge of LLMs and generative AI. Space is limited!
Morning Sessions
Introduction to Ray AI Libraries With Pytorch - Build Cost Efficient and Performant Distributed ML Workflows
3 Hours
Beginner
Ray Core Masterclass: Architectures, Best Practices, Internals
3 Hours
Intermediate
RAG Applications - From Quickstart to Scalable RAG
3 Hours
Beginner
Afternoon Sessions
Scalable Generative AI with Stable Diffusion Models - From Pre-Training to Production
3 Hours
Advanced
End-to-end LLM workflows at scale - MLOps best practices meets Large Language Models
3 Hours
Intermediate
Reinventing Multi-Modal Search with LLMs and Large Scale Data Processing
3 Hours
Intermediate
Meet Our Trainers
Kamil Kaczmarek
Kamil is a Technical Training Lead at Anyscale, where he develops advanced training resources for the Ray and Anyscale communities. He co-founded neptune.ai and has extensive experience in AI consultancy. Kamil holds an M.Sc. in Cognitive Science and a B.Sc. in Computer Science. Always curious about AI, he also enjoys sports in his free time.
Marwan Sarieddine
Marwan Sarieddine is an AI engineer and a member of the Anyscale training team, where he teaches data engineering and large-scale AI. Previously, he served as the founding engineer of a supervised deep-learning startup in the financial sector and co-founded a real estate analytics startup. Marwan holds a Master of Engineering from MIT and a Bachelor of Engineering from AUB. He is passionate about running, weightlifting, and reading, continually seeking to expand his expertise and stay at the forefront of technological advancements.
Adam Breindel
Adam Breindel is a member of the Anyscale training team and he consults and teaches on large-scale data engineering and AI/machine learning. He has served as technical reviewer for numerous O'Reilly titles covering Ray, Apache Spark, and other topics. Adam's 20 years of engineering experience include numerous startups and large enterprises with projects ranging from AI/ML systems and cluster management to web, mobile, and IoT apps. He holds a BA (Mathematics) from University of Chicago and a MA (Classics) from Brown University. Adam's interests include hiking, literature, and complex adaptive systems.
Akshay Malik
Akshay Malik is an Engineering Manager at Anyscale focusing on LLMs, where he has been contributing since January 2023. Before this role, he spent over eight years at Amazon, progressing through positions from Software Development Engineer to ML Engineering Manager. Akshay holds a Bachelor of Science in Computer Engineering from the University of Illinois at Urbana-Champaign and an MBA from the University of California, Berkeley, Haas School of Business. His experience includes significant work in machine learning, software engineering, and research in advanced technologies.
Kourosh Hakhamaneshi
Dr. Kourosh Hakhamaneshi is the AI Team Lead at Anyscale, where he drives LLM and AI initiatives using Ray for deep neural network training and deployment. With a Ph.D. in Electrical Engineering and Computer Science from UC Berkeley, his expertise spans decision-making AI, RLlib development, and graph neural networks for circuit modeling. Kourosh has a strong foundation in Computer Science and extensive experience in AI and machine learning.
Shreyas Krishnaswamy
Shreyas Krishnaswamy is a seasoned software engineer at Anyscale, where he has been contributing to the development of distributed systems for machine learning since October 2021. Prior to joining Anyscale, Shreyas gained experience as a Software Development Intern at Amazon Web Services (AWS), where they worked on AWS PrivateLink. They hold both a Master of Science and a Bachelor of Science in Electrical Engineering and Computer Science (EECS) from the University of California, Berkeley.
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