MLOps and LLMOps: From Prompt to Observability - Lecture 1
Offered By: Data Science Festival via YouTube
Course Description
Overview
Explore the integration of MLOps and traditional AI observability with a focus on corporate-level AI observability through AI stores in this 42-minute talk by DarĂo Pascual from SDG Group. Delve into the objectives, challenges, and risks associated with implementing AI stores, examining real-world application examples. Gain insights into the unique demands of generative and cognitive AI technologies and learn about LLMOps as a disruptive methodology in combination with AI stores to support these new AI systems. Discover how AI stores can enhance the management and governance of AI solutions, both traditional and generative, across various organizational units, ultimately fostering innovation and operational efficiency in a rapidly evolving technological landscape. This technical practitioner-level presentation was part of the Data Science Festival MayDay event 2024 and offers valuable knowledge for data-driven professionals looking to stay at the forefront of AI observability and management practices.
Syllabus
From prompt to observability: MLOps & LLMOps - Data Science Festival
Taught by
Data Science Festival
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent