This specialization is a quick start guide to help people use and launch LLMs like GPT, Llama, T5, and BERT at scale. It presents a step-by-step approach to building and deploying LLMs, with real-world case studies to illustrate the concepts, and covers topics such as constructing agents, fine-tuning a Llama 3 model with RLHF, building recommendation engines with Siamese BERT architectures, launching an information retrieval system with OpenAI embeddings and GPT-4, and building an image captioning system with the vision transformer and GPT. This guide provides clear instructions and best practices for using LLMs and will be a valuable resource for anyone looking to use LLMs in their projects.
Quick Start Guide to Large Language Models (LLMs) Specialization
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Quick Start Guide to Large Language Models (LLMs) Specialization
Master Prompt Engineering and LLM Tools. Use and launch LLMs like GPT, Llama, T5, and BERT at scale through real-world case studies.
Instructor: Pearson
Included with 
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Master the fundamentals and advanced techniques of LLMs, including semantic search and prompt engineering.
Develop and deploy custom multimodal models, integrating text and visual data for comprehensive AI solutions.
Optimize LLMs for specific tasks using fine-tuning, quantization, and knowledge distillation for efficient performance.
Overview
Skills you'll gain
- Performance Tuning
- Artificial Intelligence
- MLOps (Machine Learning Operations)
- Deep Learning
- AI Personalization
- Generative AI Agents
- Semantic Web
- Cloud Computing
- Natural Language Processing
- Cost Management
- Artificial Intelligence and Machine Learning (AI/ML)
- Machine Learning
- Large Language Modeling
- Application Deployment
- Reinforcement Learning
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
July 2025
12 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Pearson
Specialization - 3 course series
What you'll learn
Understand the evolution and mechanics of modern NLP and LLMs.
Build and implement semantic search systems using embeddings.
Master prompt engineering for reliable and consistent LLM outputs.
Create retrieval-augmented generation systems and AI agents.
Skills you'll gain
Category: Deep Learning
Category: Natural Language Processing
Category: Large Language Modeling
Category: Prompt Engineering
Category: Semantic Web
Category: Generative AI Agents
Category: OpenAI
Category: Generative AI
Category: Artificial Intelligence
Category: ChatGPT
What you'll learn
Master fine-tuning techniques to optimize LLM performance for specific tasks.
Develop advanced prompt engineering skills for nuanced and comprehensive outputs.
Create customized embeddings and model architectures for superior AI solutions.
Understand AI alignment principles to ensure models meet human expectations.
Skills you'll gain
Category: Prompt Engineering
Category: Performance Tuning
Category: Cost Management
Category: Large Language Modeling
Category: AI Personalization
Category: Applied Machine Learning
Category: Natural Language Processing
Category: Artificial Intelligence
Category: OpenAI
Category: Generative AI
What you'll learn
Develop custom multimodal models and implement reinforcement learning for dynamic LLM refinement.
Master advanced fine-tuning techniques, optimizing open-source models for specific tasks.
Deploy LLMs to the cloud using quantization, pruning, and knowledge distillation for efficient performance.
Evaluate LLM tasks across various categories, preparing models for real-world applications.
Skills you'll gain
Category: Large Language Modeling
Category: Reinforcement Learning
Category: Application Deployment
Category: Image Analysis
Category: Cloud Computing
Category: Natural Language Processing
Category: Performance Tuning
Category: Deep Learning
Category: Computer Vision
Category: MLOps (Machine Learning Operations)
Category: Generative AI
Category: PyTorch (Machine Learning Library)
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Frequently asked questions
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
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Financial aid available,