LLMs in Production
LLMs in Production is an advanced course designed to equip students with practical skills for deploying and managing large language models (LLMs) in real-world settings. The curriculum covers critical areas such as implementing performance evaluations, caching strategies for cost efficiency, establishing guardrails for consistent quality, designing user interfaces with defensive strategies, and setting up comprehensive monitoring and observability systems for LLM applications. This course is essential for anyone looking to expertly navigate the technical and operational aspects of large language model implementation.
Course taught by expert instructors
Yudhiesh Ravindranath
MLOps Engineer at MoneyLion
Yudhiesh is a seasoned Machine Learning Operations Engineer passionate about harnessing the power of machine learning to drive real business value swiftly and effortlessly. With a comprehensive understanding of the entire ML model development process, Yudhiesh excels in deploying and maintaining pipelines, centralizing experiment tracking, and leading teams to deliver impactful Machine Learning solutions.
The course
Learn and apply skills with real-world projects.
Data Scientists, Machine Learning practitioners, and Software Engineers who want to better understand what it takes to integrate LLMs into an actual product and scale it.
Familiarity with Software Development using Python and Docker Understand basic Machine Learning concepts such as Model Evaluation Experience with the ChatGPT API
Try these prep courses first
- Learn
- What are LLMs?
- Prompt Engineering
- Evaluation: Implementing evaluations to measure our LLMs' performance
- Guardrails: Setting up standards and checks to maintain consistent output quality.
Project- Leverage LLMs to prototype an SQL Code Generation application
- Evaluate LLMs on SQL Code Generation
- Setup Guardrails to ensure correct and safe SQL Code Generation
- Learn
- Caching: Strategies to reduce latency and manage costs efficiently.
- Defensive UX: Designing user interfaces that proactively handle potential issues and errors.
- Monitoring & Observability: Setting up monitoring of LLM usage and diagnostics.
- Data Flywheels: Gathering feedback to improve our LLM applications.
Project- Build a working Text2SQL Application Powered by ChatGPT
- Speed up the application using semantic caching
- Add in Defensive UX to help users understand the limitations in the application
- Setup Monitoring & Observability to trace and track LLM outputs
A course you'll actually complete. AI-powered learning that drives results.
AI-powered learning
Transform your learning programs with personalized learning. Real-time feedback, hints at just the right moment, and the support for learners when they need it, driving 15x engagement.
Live courses by leading experts
Our instructors are renowned experts in AI, data, engineering, product, and business. Deep dive through always-current live sessions and round-the-clock support.
Practice on the cutting edge
Accelerate your learning with projects that mirror the work done at industry-leading tech companies. Put your skills to the test and start applying them today.
Flexible schedule for busy professionals
We know you’re busy, so we made it flexible. Attend live events or review the materials at your own pace. Our course team and global community will support you every step of the way.
Completion certificates
Each course comes with a certificate for learners to add to their resume.
Best-in-class outcomes
15-20x engagement compared to async courses
Support & accountability
You are never alone, we provide support throughout the course.
Get reimbursed by your company
More than half of learners get their Courses and Memberships reimbursed by their company.
Hundreds of companies have dedicated L&D and education budgets that have covered the costs.
