Courses Coursera

LLM Application Engineering and Development Certification Specialization

Hands-on specialization on designing, building, fine-tuning, and evaluating Large Language Model (LLM) applications with LangChain. Learn GenAI workflows, unstructured data processing, embeddings and semantic search, LLM fine-tuning with PEFT/RLHF, and benchmarking with ROUGE, GLUE, and BIG-bench.

Beginner Level 40h 0m 3.50 (12) 🌐 EN

What you'll learn

  • Design and implement GenAI workflows using LangChain chains, agents, memory, and advanced LLMs
  • Process unstructured data with loaders, text splitters, embeddings, vector stores, and semantic search
  • Fine-tune and customize LLMs using PEFT, RLHF, supervised learning, and hyperparameter tuning
  • Evaluate and benchmark LLM applications using ROUGE, GLUE, BIG-bench and other model evaluation techniques

Skills you'll gain

  • Build GenAI workflows using LangChain, chains, agents, memory, and LLMs like Flan-T5 and Falcon-7B
  • Fine-tune LLMs with PEFT, RLHF, and hyperparameter tuning for real-world GenAI applications
  • Process unstructured data using loaders, text splitters, embeddings, vector stores, and semantic search tools
  • Evaluate model output using benchmarks like ROUGE, GLUE, and BIG-bench for reliable performance
  • Design scalable LLM workflows and deploy industry-grade GenAI applications
  • Create chatbots, summarization tools, and sentiment analysis applications with LangChain

Prerequisites

  • No prerequisites required

Who this course is for

  • Developers interested in building GenAI and LLM-powered applications
  • Data scientists working with NLP and large language models
  • AI and GenAI enthusiasts who want hands-on experience with LangChain and LLM workflows
Pricing varies
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