Current
Intermediate
40% Off
Fine-Tuning and Optimizing Large Language Models
Coursera · DeepLearning.AI · Updated March 2026
Platform rating
4.5/5
AI Tutor Rating
8.3/10
Duration
3 weeks, 5 hours/week
Classes
28
Master advanced techniques for fine-tuning and optimizing large language models for specific domains and tasks. Learn efficiency techniques, parameter reduction, and performance optimization.
What you'll get
Implement supervised fine-tuning on custom datasets
Apply LoRA and parameter-efficient fine-tuning methods
Optimize model inference speed and memory usage
Use reinforcement learning from human feedback (RLHF)
Evaluate and benchmark fine-tuned models
Fit
Best for
Leaders
Analysts
Researchers
Decision-makers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Understanding of LLM fundamentals, Python proficiency
Pricing
Free to audit, $49 for certificate
Certification
Certificate
Growth Leverage: Completing this course positions you for advanced roles such as Machine Learning Engineer, LLM Research Scientist, or AI Product Manager. It also opens opportunities for certifications in specialized AI frameworks, enhancing your eligibility for high-demand roles in enterprise AI applications.
Skills Value: Employers pay for these skills as they dramatically enhance model performance and efficiency, directly impacting production costs. With the implementation of cutting-edge techniques, professionals can command salary premiums of $20,000 or more, reflecting the high market demand for expertise in optimizing large language models.
fine-tuning
llm
optimization
parameter-efficiency
rlhf
deep-learning