Machine learning ops (MLOps) provides a foundation for managing and maintaining your machine learning applications, but you need to know some specialized details to use large language models (LLMs) effectively. These courses take you from key programming techniques for MLOps and LLMOps through the details of establishing LLM-based applications. You'll keep your projects running smoothly through development, to testing, and then to production.
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Learn to code for MLOps and LLMOps APIs.
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Explore options for LLM fine-tuning and compression.
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Include vector databases, agents, and chains in deployments.
Courses
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1
Generative AI and LLMOps: Building Blocks and Applications1h 21mGenerative AI and LLMOps: Building Blocks and Applications
By: Soham Chatterjee
Learn the foundations of building, fine-tuning, and deploying large language models (LLMs) in real-world applications.
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2
LLMOps in Practice: A Deep Dive4h 26mLLMOps in Practice: A Deep Dive
By: Laurence Moroney
Discover the core concepts and technical skills required to build and manage an LLM-based app in production.
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3
Advanced LLMOps: Deploying and Managing LLMs in Production1h 45mAdvanced LLMOps: Deploying and Managing LLMs in Production
By: Soham Chatterjee
Learn advanced techniques and best practices for deploying and monitoring large language models in production environments.
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4
LLM Foundations: Building Effective Applications for Enterprises1h 43mLLM Foundations: Building Effective Applications for Enterprises
By: Kumaran Ponnambalam
Explore design considerations and best practices for building generative AI-powered applications at enterprise scale.
Instructors
Soham Chatterjee
Gen AI, LLMs, MLOps
Archana Vaidheeswaran
Program Director| Responsible AI| Board Director| Machine Learning Consultant|
Laurence Moroney
| Director of AI at arm | Award-winning AI Researcher | Best Selling Author | Strategy and Tactics | Fellow at the AI Fund | Advisor to many | Inspiring the world about AI | Contact me! |
Kumaran Ponnambalam
AI / ML Leader & Author