Why enroll for Prompt Engineering with LLM Training Course?
The Global LLM Market, valued at USD 7.77 billion in 2025, is projected to reach USD 123.09 billion by 2034 - Precedence Research
2,000+ Generative AI Engineer and LLM-related job openings worldwide, reflecting strong global demand for GenAI and LLM talent โ LinkedIn.
The average annual salary for an AI Prompt Engineer in the US is US$136,000 with an average annual bonus of $37,000 - Glassdoor
Prompt Engineering with LLM Course Benefits
The global LLM market is anticipated to grow at a CAGR of 35.92% from 2025 to 2033, with 80% of enterprises adopting LLMs and prompt engineering for seamless automation and content creation. As businesses embrace these technologies, demand for experts in LLM optimization and prompt design is soaring. Our course empowers you with cutting-edge expertise to thrive in this fast-growing field at the forefront of AI innovation.
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Why Prompt Engineering with LLM Training Course from edureka
Live Interactive Learning
World-Class Instructors
Expert-Led Mentoring Sessions
Instant doubt clearing
Lifetime Access
Course Access Never Expires
Free Access to Future Updates
Unlimited Access to Course Content
24x7 Support
One-On-One Learning Assistance
Help Desk Support
Resolve Doubts in Real-time
Hands-On Project Based Learning
Industry-Relevant Projects
Course Demo Dataset & Files
Quizzes & Assignments
Industry Recognised Certification
Edureka Training Certificate
Graded Performance Certificate
Certificate of Completion
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About your Prompt Engineering with LLM Training Course
Skills Covered
Generative AI Techniques
Prompt Engineering
Retrieval-Augmented Generation
Vector Database Management
Large Language Models
GenAI Application Development
Tools Covered
Curriculum
Curriculum Designed by Experts
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Generative AI Essentials
14 Topics
Topics
What is Generative AI?
Generative AI Evolution
Differentiating Generative AI from Discriminative AI
Types of Generative AI
Generative AI Core Concepts
LLM Modelling Steps
Transformer Models: BERT, GPT, T5
Training Process of an LLM Model like ChatGPT
The Generative AI development lifecycle
Overview of Proprietary and Open Source LLMs
Overview of Popular Generative AI Tools and Platforms
Ethical considerations in Generative AI
Bias in Generative AI outputs
Safety and Responsible AI practices
Hands-on
Creating a Small Transformer using PyTorch
Explore OpenAI Playground to test text generation
Skills
Generative AI Fundamentals
Transformer Architecture
LLM Training Process
Responsible AI Practices
Prompt Engineering Essentials
10 Topics
Topics
Introduction to Prompt Engineering
Structure and Elements of Prompts
Zero-shot Prompting
One-shot Prompting
Few-shot Prompting
Instruction Tuning Basics
Prompt Testing and Evaluation
Prompt Pitfalls and Debugging
Prompts for Different NLP Tasks (Q&A, Summarization, Classification)
Understanding Model Behavior with Prompt Variations
Hands-on
Craft effective zero-shot, one-shot, and few-shot prompts
Write prompts for different NLP tasks: Q&A, summarization, classification
Debug poorly structured prompts through iterative testing
Analyze prompt performance using prompt injection examples
RAG Evaluation with RAGAS: Precision, Recall, Faithfulness
Observability in Production: Logs, Metrics, Tracing LLM Workflows
Using LangSmith for Chain/Agent Tracing, Feedback, and Dataset Runs
Integrating TruLens for Human + Automated Feedback Collection
Inference Cost Estimation and Optimization Techniques
Budgeting Strategies for Token Usage, API Calls, and Resource Allocation
Production Best Practices: Deploying With Guardrails and Evaluation Loops
Hands-on
Fine-tune a small LLM using LoRA with the PEFT library on Google Colab
Apply QLoRA to a quantized model using Hugging Face + Colab setup
Implement adapter tuning on a pre-trained model for a classification task
Compare output quality before and after finetuning using evaluation prompts
Skills
Finetuning LLMs with LoRA, QLoRA, and Adapters
Selecting optimal finetuning techniques for different scenarios
Setting up and running parameter-efficient finetuning workflows using Hugging Face
Bonus Module: LLMOps and Evaluation (Self-paced)
12 Topics
Topics
Introduction to Model Finetuning: When Prompt Engineering Isnโt Enough
Overview of Parameter-Efficient Finetuning (PEFT)
LoRA (Low-Rank Adaptation): Concept and Architecture
QLoRA: Quantized LoRA for Finetuning Large Models Efficiently
Adapter Tuning: Modular and Lightweight Finetuning
Comparing Finetuning Techniques: Full vs. LoRA vs. QLoRA vs. Adapters
Selecting the Right Finetuning Strategy Based on Task and Resources
Introduction to Hugging Face Transformers and PEFT Library
Setting Up a Finetuning Environment with Google Colab
Preparing Custom Datasets for Instruction Tuning and Task Adaptation
Monitoring Training Metrics and Evaluating Fine-tuned Models
Use Cases: Domain Adaptation, Instruction Tuning, Sentiment Customization
Hands-on
Track and compare multiple prompt versions using LangSmith
Implement a RAG evaluation pipeline using RAGAS on a custom QA system
Monitor model behavior and safety using TruLens in a live demo
Visualize cost and performance metrics from a deployed LLM API
Skills
Setting up LLMOps pipelines for observability and evaluation
Using RAGAS, TruLens, and LangSmith to assess model quality and safety
Managing cost and performance trade-offs in production GenAI systems
Course Details
Course Overview and Key Features
This LLM Prompt Engineering Certification Course guides you through basic to advanced generative AI techniques, including prompt engineering, retrieval-augmented generation (RAG), and vector databases. You will gain practical skills to design and deploy cutting-edge GenAI applications using popular tools such as Python, PyTorch, LangChain, and OpenAI. The course also focuses on mastering LLM APIs, application architecture, and production-ready deployment strategies, equipping you to build real-world AI solutions.
Keyfeatures
Comprehensive coverage from fundamentals to advanced generative AI concepts
Hands-on experience with prompt crafting techniques to elicit precise LLM responses
Exploration of advanced prompting strategies like zero-shot, few-shot, and chain-of-thought prompting
Training on retrieval-augmented generation (RAG) and vector database integration
Practical usage of key tools and libraries: Python, PyTorch, LangChain, OpenAI API, and more
Understanding of LLMOps principles for deploying and managing LLM applications
Insights into ethical considerations, including bias and misinformation in prompt design
Application-focused learning across diverse domains such as content creation, code generation, and data analysis
Who should take this LLM prompt engineering certification course?
If you are an AI enthusiast, developer, or professional working with natural language processing, AI product development, or automation and you want to get better at designing effective prompts to make your AI applications smarter, the Prompt Engineering with LLM Course is a great fit for you.
What are the prerequisites for this course?
To succeed in this course, you should have a basic understanding of Python, machine learning, deep learning, natural language processing, generative AI, and prompt engineering concepts. However, you will receive self-learning refresher materials on generative AI and prompt engineering before the live classes begin.
What are the system requirements for the LLM Prompt Engineering course?
The system requirements for this Prompt Engineering with LLM Course include:
A laptop or desktop computer with a minimum of 8 GB RAM with Intel Core-i3 and above processor to run NLP and machine learning models is required.
A stable and high-speed internet connection is necessary for accessing online course materials, videos, and software.
How do I execute the practicals in this course?
Practical for this Prompt Engineering course are done using Python, VS Code, and Jupyter Notebook. You will get a detailed step-by-step installation guide in the LMS to set up your environment smoothly. Additionaly, Edurekaโs Support Team is available 24/7 to help with any questions or technical issues during your practical sessions.
Prompt Engineering with LLM Course Projects
Automated Code Review Assistant
Design an AI-powered assistant that analyzes code snippets, offers improvement suggestions, and educates developers on coding best practices to enhance productivity.
Document-Based Knowledge Assistant
Develop a Retrieval-Augmented Generation (RAG) system that efficiently retrieves and generates precise answers from extensive document collections in response to user queries.
Financial Report Analyzer
Build a chatbot that summarizes and answers questions from financial statements and investor reports.
Conversational API-Integrated Bot
Build a chatbot capable of interfacing with external APIs to deliver dynamic, real-time responses for applications such as customer support.
Technical Troubleshooting Q&A System with Document Retrieval
Develop an AI-powered Q&A system that retrieves and analyzes information from technical guides and documentation to deliver precise solutions for IT and software troubleshooting ....
Prompt Engineering with LLM Course Certification
Upon successful completion of the Prompt Engineering with LLM Course, Edureka provides the course completion certificate, which is valid for a lifetime.
To unlock Edurekaโs Prompt Engineering with LLM course completion certificate, you need to fully participate in the course by completing all the modules and successfully finish the quizzes and hands-on projects included in the curriculum.
The Prompt Engineering with LLM certification can be tough if youโre new to the field,it covers a lot, from understanding how large language models work to actually crafting prompts and building projects.
Yes, once you complete the certification, you will have lifetime access to the course materials. You can revisit the course content anytime, even after completing the certification.
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The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate
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Suman RajaIT Analyst at Tata Consultancy Services Greater Philadelphia Area Information Technology and Services
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Definitely there is no doubt in saying that all the instructors at Edureka are industry experienced and the support staff provides a quick response to the tickets you log whether it be Day or Night. I like the way the sessions have been organized, with the Pre-requisites required for the next session and the assignments, QUIZ post session etc...I like the LMS a lot, You can find enough of required information in the forums. They even share the video recordings of other instructors as well in the LMS. So that if one couldn't get the content clearly in your session, you can always refer to other instructors recordings shared in your LMS. This part helped me in understanding few concepts in a better way.
December 09, 2017
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I confirm that Edureka team is working excellent software development training programs online .And the instructor of the training explains the every concept of programming in well mannered.And it is the better way to do learn from anywhere without any problem.And the online 24*7 helpline support is very good.The recording of every classes and the and code is very helpful to clear any doubt at any time. I would highly recommend your support team that the edureka is the best training provider team.
December 09, 2017
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Earlier I had taken training in different technologies from other institutes and companies but no doubt Edureka is completely different, First time in my carrier I have received such kind of training and support. They have really awesome instructors. The support persons are technically sound and I would like to appreciate their 24 x 7 support. I never seen such kind of support by other companies in India till now. When I had started training on Hadoop I do not have any idea of Java but their training structure is marvelous and they taught Java in very easy way and build up confidence in it. My training is still going on and it is about to finish and I would like to thanks Edureka to help me to find robust path of carrier with such a new and emerging technology of Big Data.
There is a plethora of online training material available for Android; the reason I chose Edureka is the rare combination of great instructors, comprehensive course material . The course has a clear direction, which is perfect for efficiency-oriented professionals like us! What differentiates Edureka training from numerous other Android trainers is that they bring a lot of corporate experience on the table, and that is evident in their teaching techniques.
December 09, 2017
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I would like to recommend any one who wants to be a Data Scientist just one place: Edureka. Explanations are clean, clear, easy to understand. Their support team works very well such any time you have an issue they reply and help you solving the issue. I took the Data Science course and I'm going to take Machine Learning with Mahout and then Big Data and Hadoop and after that since I'm still hungry I will take the Python class and so on because for me Edureka is the place to learn, people are really kind, every question receives the right answer. Thank you Edureka to make me a Data Scientist.
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December 09, 2017
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FAQs
What is LLM?
Large Language Model (LLM) is an AI trained on huge text data to understand and generate human-like language.
What is prompt engineering in LLM?
It's the art of crafting inputs (prompts) that guide large language models (LLMs) to give accurate, useful responses.
Why should I learn LLM?
Learning LLMs lets you build advanced AI apps like chatbots and content tools shaping the future of tech.
What are examples of LLMs?
Examples include OpenAIโs GPT series (ChatGPT, GPT-4), Googleโs BERT,powerful models for language tasks.
What if I miss a live class of this training course?
You will have access to the recorded sessions that you can review at your convenience.
What if I have queries after I complete the course?
You can reach out to Edurekaโs support team for any queries and youโll have access to the community forums for ongoing help.
What skills will I acquire upon completing the Prompt Engineering with LLM training course?
Upon completing the Prompt Engineering with LLM training, you will acquire skills in prompt structuring, prompt tuning, task-specific prompting, and model behavior analysis.
Who are the instructors for the LLM Prompt Engineering Course?
All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.
What is the cost of a prompt engineering course?
The price of the course is 18,999 INR.
What is the salary of a prompt engineer fresher?
According to Glassdoor, Freshers in India typically start around โนโน6 to โน7 LPA, while in the US it can range from $70,000 to $100,000 annually.
Will I get placement assistance after completing this Prompt Engineering with LLM training?
Edureka provides placement assistance by connecting you with potential employers and helping with resume building and interview preparation
How soon after signing up would I get access to the learning content?
Once you sign up, you will get immediate access to the course materials and resources.
Is the course material accessible to the students even after the Prompt Engineering with LLM training is over?
Yes, you will have lifetime access to the course material and resources, including updates.
Is there a demand for prompt engineering?
Yes, prompt engineers are currently in high demand. With the rapid growth of AI adoption, companies are actively seeking professionals skilled in prompt design.
Is prompt engineering the future?
Its future is more about growing and adapting than becoming outdated.