LLM Engineer’s Handbook

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

LLM Engineer’s Handbook

Coursera · Intermediate ·🧠 Large Language Models ·3mo ago

Key Takeaways

Designs, trains, and deploys Large Language Models using MLOps practices

Original Description

In this comprehensive course, you will explore the intricate world of Large Language Models (LLMs) and gain the skills to design, train, and deploy them using cutting-edge MLOps practices. LLMs are revolutionizing the AI landscape, and understanding how to develop and manage them is essential for AI professionals. This course is designed to help you not only grasp the core concepts behind LLMs but also give you hands-on experience to build production-grade LLM systems. You'll learn how to create scalable, efficient LLM systems from scratch, focusing on real-world applications that will make you stand out in the AI industry. What sets this course apart is its combination of in-depth theoretical insights and real-world, practical applications. You'll move beyond basic knowledge to master LLM architecture, supervised fine-tuning, and deployment on cloud platforms, ensuring that you’re fully equipped to build robust, production-ready systems. This course is ideal for AI engineers, NLP professionals, and anyone looking to deepen their expertise in LLM engineering. A basic understanding of LLMs, Python, and cloud platforms like AWS is recommended for optimal learning.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
The AI Crash Test: adversarial LLM testing you can audit in the Network tab
Learn to test LLMs with adversarial examples using a browser tool, ensuring model robustness and security
Dev.to · Erik Hill
📰
[Day 17] I analyzed 33,469 of my own AI conversations to audit how I actually use AI
Analyze your AI conversations to understand how you use AI and identify areas for improvement
Dev.to · PEPPERCORN
📰
Active players looked real until we asked which sessions counted
Learn how to build a web game with LLM integration, specifically Codenames AI, and understand the challenges of defining active player sessions
Dev.to · Michael Truong
📰
Building Multimodal SuperAgents: Integrating Speech, OCR, and Translation with iFly-Skills
Learn to build multimodal SuperAgents that integrate speech, OCR, and translation using iFly-Skills, enabling AI to interact with the physical world
Dev.to AI
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →