LLM Engineering: Master AI, Large Language Models & Agents
Udemy Coupon Code for LLM Engineering: Master AI, Large Language Models & Agents Course. Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI and key theoretical concepts.
Created by Ligency Team, Ed Donner | 25.5 hours on-demand video course
LLM Engineering Course Overview
LLM Engineering: Master AI, Large Language Models & Agents
Mastering Generative AI and LLMs: An 8-Week Hands-On Journey
Accelerate your career in AI with practical, real-world projects led by industry veteran Ed Donner. Build advanced Generative AI products, experiment with over 20 groundbreaking models, and master state-of-the-art techniques like RAG, QLoRA, and Agents.
About the Instructor
I’m Ed Donner, an entrepreneur and leader in AI and technology with over 20 years of experience. I’ve co-founded and sold my own AI startup, started a second one, and led teams in top-tier financial institutions and startups around the world. I’m passionate about bringing others into this exciting field and helping them become experts at the forefront of the industry.
Projects:
- Project 1: AI-powered brochure generator that scrapes and navigates company websites intelligently.
- Project 2: Multi-modal customer support agent for an airline with UI and function-calling.
- Project 3: Tool that creates meeting minutes and action items from audio using both open- and closed-source models.
- Project 4: AI that converts Python code to optimized C++, boosting performance by 60,000x!
- Project 5: AI knowledge-worker using RAG to become an expert on all company-related matters.
- Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.
- Project 7: Capstone Part B – Fine-tuned open-source model to compete with Frontier in price prediction.
- Project 8: Capstone Part C – Autonomous agent system collaborating with models to spot deals and notify you of special bargains.
What you’ll learn
- Project 1: Make AI-powered brochure generator that scrapes and navigates company websites intelligently.
- Project 2: Build Multi-modal customer support agent for an airline with UI and function-calling.
- Project 3: Develop Tool that creates meeting minutes and action items from audio using both open- and closed-source models.
- Project 4: Make AI that converts Python code to optimized C++, boosting performance by 60,000x!
- Project 5: Build AI knowledge-worker using RAG to become an expert on all company-related matters.
- Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.
- Project 7: Capstone Part B – Execute Fine-tuned open-source model to compete with Frontier in price prediction.
- Project 8: Capstone Part C – Build Autonomous multi agent system collaborating with models to spot deals and notify you of special bargains.
- Design and develop a full solution to a given business problem by selecting, training and applying LLMs
- Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows
- Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task
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LLM Engineer AI Course Reviews
Everything You Need to Know About LLM Engineering: Master AI, Large Language Models & Agents
This course offers a comprehensive and well-structured introduction to LLM. Ed Doner, the instructor, brings a wealth of expertise in Development, making this course both informative and engaging.
The course structure is easy to follow. Each section, for example, covers a different aspect of Data Science Course, ensuring a logical progression through the material. It includes video lectures, readings, and hands-on exercises, which make complex concepts accessible and practical.
Moreover, the instructor explains each topic clearly and concisely. He supports the lessons with plenty of examples and exercises, which help students grasp the material effectively.
What I appreciated most about this course is its practical focus. For instance, the instructor emphasizes teaching skills and knowledge that are directly applicable to real-world scenarios. Additionally, students gain access to helpful resources such as templates, checklists, and cheat sheets.
Another standout feature is the platform itself. Udemy offers flexibility, allowing students to learn at their own pace and access course materials from anywhere with an internet connection. Furthermore, the multiple payment options make it easy for students to choose a plan that suits their budget.
In addition, the course community is highly active, with forums where students can ask questions and engage with peers. The instructor, consequently, is very responsive and addresses student inquiries and feedback promptly.
Overall, I highly recommend the LLM Engineering: Master AI, Large Language Models & Agents to anyone looking to learn Large Language Models (LLM) This well-organized and practical course equips you with the skills and knowledge you need to succeed in this field.
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