AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Simplilearn via Coursera Learning path or series
LLM Application Engineering and Development Certification
Overview
This specialization offers a hands-on journey into building and deploying applications powered by Large Language Models (LLMs) and LangChain. Learn to design GenAI workflows using LangChain’s architecture—including chains, memory, agents, and prompts—and integrate advanced models like Flan-T5 XXL and Falcon-7B. Process unstructured data, implement embeddings, and enable semantic retrieval for intelligent applications. Fine-tune LLMs using techniques like PEFT and RLHF, and evaluate performance using benchmarks such as ROUGE, GLUE, and BIG-bench to ensure model reliability.
By the end of this program, you will be able to:
- Design LLM Workflows: Build scalable GenAI apps using LangChain with memory and agent modules
- Process and Retrieve Data: Use loaders, vector stores, and embeddings for semantic search
- Fine-Tune and Customize Models: Apply PEFT, RLHF, and dataset structuring for optimization
- Evaluate and Scale Applications: Use standard benchmarks and deploy industry-grade LLM tools
Ideal for developers, data scientists, and GenAI enthusiasts building advanced, real-world LLM applications.
Courses in this learning path or series 4
- LangChain and Workflow Design Course
- LangChain Course for LLM Application Development
- LLM Fine-Tuning and Customization Training
- LLM Benchmarking and Evaluation Training
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- Self-paced: start any time.
- A clear syllabus (4 parts) you can see before you start.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Simplilearn is in Tier 4: commercial training companies and platform-made courses of our institution ranking (58/100).
Similar courses
Generative AI Program
-Learn more and enroll in the program: https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program Recent advancements in generative AI are reshaping industries, pushing technological boundaries, and revolutionizing creative processes. In this fast-changing landscape…
Artificial Intelligence
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Delve into the exciting world of Artificial Intelligence with insights and research from the world's top experts. This playlist offers a comprehensive journey, from foundational machine learning con…
Stanford CS229: Machine Learning led by Andrew Ng | Autumn 2018
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabili…
Large Language Models (LLMs)
Explore the cutting-edge realm of Large Language Models (LLMs) with this expertly curated YouTube playlist. Featuring insights from industry leaders, educational content, and in-depth discussions, this selection highlights the latest advancements in LLM technology.