LLM Training Course with Fine-Tuning & RLHF for Production AI

Do you want to adapt powerful pre-trained language models for specific, real-world applications? This course offers you practical training in fine-tuning and reinforcement learning techniques to shape model behavior. Ultimately, you will be able to deploy safer, more reliable, and production-ready LLMs effectively.

What Will You Learn?

• How post-training fits into the LLM lifecycle and powers real-world products.

• Core techniques including Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).

• Implementation of RL algorithms like PPO and GRPO, alongside efficient fine-tuning using LoRA.

• Designing evaluations, detecting reward hacking, and red-teaming to test model robustness.

• Preparing datasets, creating synthetic data, and balancing rewards.

• Establishing production pipelines with monitoring, cost-awareness, and data feedback loops.

Course Details:

• Duration: Not Found (Self-paced, 5 Modules)

• Level: Intermediate

• Language: English

• Certificate status: Paid certificate

• Course Type: Online course

Course Features:

• Learn directly from industry experts in collaboration with AMD.

• Gain hands-on experience through graded labs powered by AMD GPUs.

• Acquire highly sought-after, hardware-agnostic skills for the growing AI market.

• Move beyond basic theory to build models capable of instruction following and advanced reasoning.

Target Audience:

• Developers, machine learning engineers, and software engineers.

• Data scientists and technical students transitioning into AI.

• Product managers and technical leaders guiding AI/LLM product teams.

• Professionals with Python programming experience and basic LLM knowledge.

Why Choose This Course?

• Master the critical post-training phase that turns raw models into valuable, safe products.

• Bridge the gap between assuming only experts can tune models and actually applying these techniques yourself.

• Upgrade your resume with cutting-edge skills in fine-tuning, RLHF, PPO, and GRPO algorithms.

• Become indispensable to any team building developer copilots, customer support agents, or internal AI assistants.

How to Register:

• Visit the official DeepLearning.AI course page using the provided link.

• Click the Enroll Now button to access the learning platform.

• Create an account or log in with your existing DeepLearning.AI credentials.

• Choose the "Audit" option to view materials for free, or subscribe to unlock graded labs and certificate eligibility.

• Begin your journey with Module 1 immediately.

FAQ:

Question: Do I need programming experience for this course?
Answer: Yes, strong familiarity with Python and a basic understanding of how LLMs work are highly recommended to succeed in the hands-on labs.
Question: Is this course hardware-specific to AMD?
Answer: No, while the hands-on labs are powered by AMD GPUs, the post-training methods and techniques you learn are entirely hardware-agnostic.
Question: Will I learn how to prevent LLM hallucinations?
Answer: Yes, the course covers techniques like Reinforcement Learning from Human Feedback and evaluation strategies to make LLMs safer, more reliable, and less prone to hallucination.

Master LLM post-training today and upgrade your AI engineering career!