LLM Engineering: Master AI & Large Language Models (LLMs)
LLM Engineering: Master AI & Large Language Models (LLMs)
Master Generative AI and Large Language Models (LLMs). Explore and deploy LLM applications, learn fundamental theory.
Product Brand: Udemy
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Udemy Coupon Code for LLM Engineering: Master AI & Large Language Models (LLMs) 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 Doner | 12.5 hours on-demand video course
Large Language Models Course Overview
LLM Engineering: Master AI & Large Language Models (LLMs)
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.
What you’ll learn
- 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
- Solve problems by applying leading open-source platforms, frameworks and tools, including Hugging Face, Gradio and Weights & Biases
- State the common AI paradigms, and identify the types of business problems most suitable for each
- Define fundamental data science concepts around deep learning, including training vs inference, generalizing vs overfitting, and the key ideas behind the NN
- Describe core concepts such as Generative AI, LLMs and the Transformer Architecture, and discuss what can be achieved with state-of-the-art performance
- Explain how LLMs work in sufficient detail to be able to train and test them, apply them to new scenarios, and diagnose & fix common issues
- Implement LLM solutions in Python using frontier and open-source models with both APIs and direct inference
- Execute code to write documents, answer questions and generate images.
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