Prompt Engineering Certification Course [Updated 2025]

Name: Prompt Engineering with Generative AI
Item: Prompt Engineering with Generative AI
Rating: 5
Author: Vijay Kalkundri

Why should you take Prompt Engineering Course?

Gartner reported that VC firms had invested more than $1.7 B in generative AI solutions over the past three years

Generative AI market is expected to grow from $11.3 B in 2023 to $51.8 B by 2028 at a CAGR of 35.6% - Markets and Markets

OpenAI is actively hiring applied AI research and prompt engineering domain with salaries upto $370,000 - LinkedIn

Generative AI and its Industry Applications

Topics:

Generative AI Principles
Types of Generative Models
Applications of Generative Models
Machine Learning Algorithms with GenAI
Applications of Generative AI
Generative AI: Advantages and Disadvantages
Ethical Considerations

Hands-On:

Implementing Generative AI Use Cases
Implementing Machine Learning with GenAI

Skills You will Learn:

Generative AI Fundamentals
Generative AI for Problem Solving
Ethical Insights into Generative AI

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NLP and Deep Learning

Topics:

Natural Language Processing (NLP) Essentials
Text Classification
Text Preprocessing
Basic NLP Tasks
Deep Learning for NLP
Neural Networks
Backpropagation
RNN
LSTM
Deep Learning Applications in NLP

Hands-On:

Simple Text Classification Task
Implementing Core NLP Tasks
Working with Deep Learning for NLP

Skills You will Learn:

Text Classification
Text Pre-processing
Deep Learning Applications for NLP
Neural Network Architectures

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Autoencoders and GANs

Topics:

Basic Autoencoders
Variational Autoencoders (VAEs)
Applications in Data Compression and Generation
Basic GAN Architecture
Training GANs
Variants of GANs
DCGAN
CycleGAN

Hands-On:

Working with GANs
Data Compression with Autoencoders
Training Variants of GANs

Skills You will Learn:

Working with Autoencoders and VAEs
GAN Architecture
GAN Training Techniques

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Language Models and Transformer-based Generative Models

Topics:

Exploring Language Models
Types of Language Models
Applications of Language Models
The Transformer Architecture: Attention Mechanism
Advanced Transformer Models
GPT
BERT
Applications of Transformer-based Models

Hands-On:

Working with GPT
Implementing BERT
Applying Advanced Transformer Models

Skills You will Learn:

Working with Language Models
Transformer Architectures
Implementing Transformer-based Models

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Prompt Engineering

Topics:

Prompt Engineering Principles
What is Prompt Engineering?
Importance and Applications
Prompt Design Strategies
Types of Prompting
Crafting Effective Prompts
Parameter Tuning

Hands-On:

Designing Precise Prompts
Experimenting with Various Prompt Design Strategies
Advanced Parameter Tuning for Prompt Engineering

Skills You will Learn:

Prompt Engineering Principles
Crafting Effective Prompts
Advanced Parameter Tuning for Prompts

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Generative AI with LLMs

Topics:

LLMs and Generative AI Project Lifecycle
LLM Pre-Training and Scaling
Fine-Tuning LLMs with Specific Instructions
Efficient Fine-Tuning of Parameters
Reinforcement Learning from Human Response

Hands-On:

Experimenting with LLM
Applying Fine-Tuning on Parameters
LLM Project Lifecycle
Reinforcement Learning Exercises

Skills You will Learn:

LLM Scaling and Pre-training
Fine-tuning Techniques for LLMs
Implementing Reinforcement Learning in LLMs

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LLMs for Search, Prediction, and Generation

Topics:

Search Query Completion
Next Word Prediction
Word Embeddings
Transformers
Generating Text
Stacking Attention Layers

Hands-On:

Execute Search Query and Next-word Prediction using LLMs
Implement LLMs with TensorFlow and PyTorch
Build Chatbot using LLMs

Skills You will Learn:

LLM Application in NLP Tasks
LLM Implementation with Python Libraries
Problem Solving using LLM

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LangChain for LLM Application Development

Topics:

LangChain Foundations
Benefits of using LangChain
Using LangChain to Develop LLM Applications
Value Propositions of LangChain
Components of LangChain
Off-the-Shelf Chains in LangChain
Build and Deploy LLM-Powered Applications using LangChain

Hands-On:

Build an LLM-Powered Application using LangChain
Experiment with Off-the-Shelf Chains in LangChain
Deploy an LLM Application

Skills You will Learn:

LangChain Implementation
Grasping LangChain Foundations
Developing LLM applications using LangChain

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Interacting with Data Using LangChain and RAG

Topics:

Understanding Retrieval-Augmented Generation (RAG)
Document Loading and Splitting
Vector Stores and Embeddings
Retrieval
Question Answering with Chatbots
Building RAG Models using LangChain

Hands-On:

Construct a LangChain-RAG Chatbot for Custom Data
Deploy Chatbot in a Production Environment
Develop a Basic RAG Model

Skills You will Learn:

Document Management with Loading and Splitting
Retrieval Techniques
Chatbot-Based Question and Answering
RAG Model Construction with LangChain

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Generative AI on Cloud

Topics:

Cloud Computing Foundations
AWS S3
Amazon EC2 Trn1n
Amazon EC2 Inf2
Amazon Sagemaker
Amazon CodeWhisperer
Amazon Bedrock
Azure OpenAI

Hands-On:

Setting up a Cloud Computing Environment
Navigating Cloud Platforms for AI Development
Utilizing Amazon Elastic Compute Cloud (EC2) Trn1n Instances for AI Workloads
Building and Deploying Machine Learning Models using SageMaker

Skills You will Learn:

Working with Amazon EC2 Inf2 Instances
Incorporating CodeWhisperer into AI Development
Implementing Azure OpenAI for Generative AI Solutions

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Working with ChatGPT (Self-paced)

Topics:

Introduction to ChatGPT
Leveraging ChatGPT for Productivity
Mastering Excel through ChatGPT
Becoming a Data Scientist using ChatGPT
Data Analysis in PowerBI with ChatGPT
Creating a Content Marketing Plan
Social Media Marketing using ChatGPT
Keyword Search and SEO using ChatGPT
Generating Content using ChatGPT
Implementing ChatGPT for Customer Service
ChatGPT for Developers
ChatGPT for Creating Programs
ChatGPT for Debugging
ChatGPT for Integrating New Features
ChatGPT for Testing
Documenting the Code with ChatGPT

Hands-On:

Explore ChatGPT's Capabilities
ChatGPT for Programming and Productivity Enhancement
Leveraging ChatGPT for Debugging and Integrating New Features
Experiment with ChatGPT for Testing Purposes and Generating Test Cases
Practice Documenting Code and API Concepts with ChatGPT

Skills You will Learn:

Explore the power of ChatGPT
Productivity Enhancement
Programming with ChatGPT
ChatGPT for Code Debugging and Documentation
Software Testing using ChatGPT

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Python with Generative AI (Self-paced)

Topics:

Python Code Generation with Generative AI
Gen AI Tools for Coding
Advanced Code Optimization with ChatGPT Gen AI Tool
Coding with ChatGPT
Building an Application in Python with ChatGPT

Hands-On:

Utilize Gen AI Tools to Enhance Coding Tasks
Optimize a Code using the ChatGPT Gen AI Tool
Create Python Scripts using ChatGPT

Skills You will Learn:

Generative AI-Powered Python Coding
Code Enhancement with ChatGPT

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Evaluating LLM Performance (Self-Paced)

Topics:

LLM Performance Comparison
Perplexity
BLEU Score
Human Evaluation
Choosing the Right Metrics
Interpreting the Results

Hands-On:

Evaluate LLM using Various Performance Metrics
Select Appropriate Metrics for Specific Generative AI Task
Analyze LLM Performance

Skills You will Learn:

LLM Performance Evaluation
Interpreting LLM Performance Results

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Industry Case Studies and In-class Project (Self-Paced)

Topics:

In-class Project: AI-Powered Text and Image Generator
Case Study: Generative AI for Personalized Learning
Case Study: Generative AI for Creative Content Generation
Case Study: Generative AI for Business

Hands-On:

Building a Generative AI Powered Text and Image Generator

Skills You will Learn:

Analyzing Generative AI Implementations
Building Generative AI Models

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Bonus Module - Machine Learning with Generative AI (Self-paced)

Topics:

Artificial Intelligence Essentials
Disciplines of AI
Types of AI
Machine Learning Fundamentals
Predictive ML Models
ML Algorithms: Deep Dive
Supervised Learning
Unsupervised Learning
Semi-Supervised Learning
Reinforcement Learning

Hands-On:

Experiment with Various AI Tools
Implement a ML Model
Explore Different Disciplines and Types of AI

Skills You will Learn:

Machine Learning Fundamentals
Machine Learning Algorithms
Working with Predictive ML Models

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Bonus Module - Generative AI Tools (Self-paced)

Topics:

Hugging Face Transformers
OpenAI GPT3 API
Google Cloud AI Platform
MidJourney
DALL E-2
Google Bard

Hands-On:

Implement a Basic Model using Hugging Face Transformers
Generate content with OpenAI GPT3 API
Deploy a Model on Google Cloud AI Platform
Generate Images using MidJourney and DALL E-2
Working with Google Bard

Skills You will Learn:

Implementing Hugging Face Transformers
Working with OpenAI GPT3 API
Working with MidJourney and DALL E-2
Content Generation with Google Bard

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View course curriculum

Testimonial Reviews

Karunakar ReddySenior System Analyst at Santander UK

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Shilpa ChutakeFinancial Analyst, JPMorgan Chase & Co.

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What is Prompt Engineering?‎

Prompt engineering involves optimizing artificial intelligence engineering for multiple purposes. It includes refining large language models (LLMs) using specific prompts and recommended outputs. Additionally, it focuses on enhancing input to different generative AI services to make text or images. With advancements in generative AI tools, prompt engineering becomes crucial for generating diverse content, such as robotic process automation bots, 3D assets, scripts, robot instructions, and various digital artifacts.

Does Edureka provide a Prompt Engineering Training Course with Placement assistance?

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

What is the Background of Prompt Engineering with ChatGPT?

Prompt engineering involves crafting effective inputs (prompts) to interact with large language models like ChatGPT. It has emerged as a crucial skill, particularly with the rise of conversational AI and tools such as ChatGPT. Understanding how to structure and optimize prompts allows users to maximize the model's potential, ensuring it generates accurate, coherent, and contextually relevant responses. As language models like ChatGPT grow in capability, mastering prompt engineering is becoming essential for anyone working with AI, from developers to educators and business professionals.

Can I attend a demo session before enrollment in Prompt Engineering Course Online?

To maintain the quality standards, we have a limited number of participants in a live session. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording, which will give you a clear insight into how the classes are conducted, the quality of instructors, and the level of interaction in a class.

What is the Prompt Engineering Course syllabus?‎

To enhance your knowledge in the area of Prompt Engineering or related fields such as natural language processing (NLP), artificial intelligence (AI), and machine learning (ML), consider studying the following topics:

Natural Language Processing (NLP)
Machine Learning
Deep Learning
Generative Models
AI Ethics and Bias
Language Models
Data Preprocessing and Feature Engineering:
Reinforcement Learning
Human-Computer Interaction
Automation and Scripting
Semantic Web and Linked Data
Industry Applications

Who are the instructors for Prompt Engineering Course Online?

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 if I have more queries after completion of Prompt Engineering Certification Course?

Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co.

How can I learn prompt engineering?

To learn Python for prompt engineering, follow these steps :

Learn syntax.
Explore libraries like NumPy, Pandas, Matplotlib, and Scikit-learn.
Get hands-on natural language libraries such as NLTK, spaCy, TextBlob, and others.
Exercise data analysis.
Understand about machine learning models.
Practice Python coding.

How to create complex prompt-based applications for your life, business, or education?

Prompt engineering can be used to build complex, prompt-based applications that help automate tasks in personal, business, and educational contexts. For example:

Create AI assistants to handle tasks like scheduling, personal research, or creative writing.
Develop AI-driven chatbots for customer service, marketing copy generation, or project management assistance.
Build personalized tutoring systems or content recommendation engines to enhance learning experiences.

What if I miss a class of Prompt Engineering Course?

You will never miss a lecture at Edureka! You can choose either of the two options:

View the recorded session of the class available in your LMS.
You can attend the missed session, in any other live batch.

How will Prompt Engineering help your career?

Prompt Engineering can dramatically boost your career by giving you the skills to customize AI models for specific tasks—an invaluable skill set in fields like content generation, data analysis, and automation, where AI customization is highly valued.

How Can Prompt Engineering Be Applied to Work Effectively with Large Language Models like ChatGPT?

Prompt engineering with ChatGPT helps to control and refine the outputs of large language models by tailoring the input queries. By learning how to design precise prompts, users can guide ChatGPT to provide more accurate and useful answers in various contexts, from writing content and solving technical problems to brainstorming ideas.

Does ChatGPT use Prompt Engineering?

Prompt Engineering is important for maximizing the effectiveness of LLMs and serves as a potent mechanism for tailoring interactions with ChatGPT. This process entails formulating precise and detailed instructions or questions to prompt the desired outputs from the language model.

What is Prompt Engineering Salary?

According to Glassdoor, the average salary of an AI prompt engineer is ₹ $7,41,000 in India. Prompt hourly pay ranges from approximately $17 per hour for a Picker/Packer to $55 per hour for a Software Engineer.

Is it worth learning Prompt Engineering?

Prompt engineering presents a compelling career opportunity. You can delve into AI language models and technological advancements, utilize your writing skills or passion, and contribute to companies in achieving their objectives.

What are the basic skills of a Prompt Engineer?

A Prompt Engineer, particularly in the context of working with generative AI models, should possess the following basic skills:

Understanding of AI Fundamentals
Programming Proficiency
Data Handling
NLP Expertise
Model Customization
Problem-Solving
Domain Knowledge
Ethical Considerations

How do we use prompt patterns to tap into powerful capabilities within large language models?

Using specific prompt patterns enables you to tap into the diverse capabilities of ChatGPT and other large language models. These patterns might include:

Chain of thought prompting: Encouraging the model to "think" step-by-step to arrive at more logical and detailed responses.
Role-based prompting: Assigning a specific role to ChatGPT (e.g., teacher, developer, consultant) to tailor the response to a particular domain.
Few-shot prompting: Provide examples within the prompt to demonstrate the type of response you want from ChatGPT.

Does Edureka Provide a Prompt Engineering Training near me?

Yes, Edureka provides the best Prompt Engineering Course worldwide. Edureka offers online courses, so their Prompt Engineering online training Course can be accessed from anywhere with an internet connection. You don't need to be physically near a specific location to enroll in a course.

Does Prompt Engineering have a future?

Yes, prompt engineering has a promising future. As AI and machine learning models, especially language models, become more sophisticated and widespread, the need for effective and efficient prompt design grows. This involves crafting inputs to elicit the best possible responses from AI models, which is critical in applications like customer service, content creation, education, and more.

Which AI tools are taught in this prompt engineering short-term training course?

This prompt engineering course covers several key AI tools in conjunction with ChatGPT, including:

OpenAI’s GPT models (like ChatGPT): For developing conversational agents, creative writing tools, and more.
AI-enhanced writing tools: Such as Jasper and Copy.ai, which rely on prompt engineering for marketing, content, and automation.
Code generation tools: Tools like GitHub Copilot that use language models to help with programming tasks.
Text analysis and summarization tools: Applications like SummarizeBot or Paperpile, which assist in content summarization and text understanding.

How can a Prompt Engineering certification course advance my career?

Completing a Prompt Engineering course can significantly enhance your career prospects in fields like AI development, data analysis, and consultancy. It equips you with the skills to work effectively with AI models, enabling automation, decision-making, and optimization across various industries, including tech, finance, healthcare, and customer service.

Can a fresher become a Prompt Engineer?

Yes, a fresher can become a prompt engineer. While experience is beneficial, enthusiasm, willingness to learn, and practical skills are crucial. Starting with internships or entry-level positions in companies focusing on AI can provide valuable experience.

Is coding required for Prompt Engineering?

While not all aspects of prompt engineering require deep coding knowledge, a basic understanding of programming is highly beneficial. Familiarity with languages like Python, which is commonly used in AI development, is important. Coding skills help in:

Understanding how language models work.
Implementing and testing prompts.
Integrating AI models into applications.

What is an example of format length and audience in prompt engineering?

In prompt engineering:

Format could be a question or statement.
Length might vary from a brief query to a detailed instruction.
The audience could be a beginner or expert user.

What is the purpose of prompt engineering in Gen AI systems?

The purpose of prompt engineering in generative AI systems is to craft inputs that guide the AI to generate relevant, accurate, and coherent responses, ensuring it meets the user's needs and expectations.

Which is an example of iteration in prompt engineering?

An example of iteration in prompt engineering would be refining a prompt like:

Initial prompt: "Tell me about AI."
Refined prompt: "Explain the basics of AI in simple terms for a beginner."
Final prompt: "Provide an overview of AI concepts, with examples, that a high school student would understand."

Each version improves the clarity and specificity of the response based on the initial output, showcasing the iterative process.

What is an example of using roles in prompt engineering?

An example of using roles in prompt engineering is:

Prompt with Role: "As a teacher, explain the concept of photosynthesis in simple terms to a 10-year-old."

By assigning the role of "teacher," the AI is guided to adjust its tone, language, and level of complexity to suit the audience and context.

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Prompt Engineering with Generative AI

Why should you take Prompt Engineering Course?

Instructor-led Prompt Engineering Course live online classes

Financing Options

Prompt Engineering Course Syllabus

Generative AI and its Industry Applications

NLP and Deep Learning

Autoencoders and GANs

Language Models and Transformer-based Generative Models

Prompt Engineering

Generative AI with LLMs

LLMs for Search, Prediction, and Generation

LangChain for LLM Application Development

Interacting with Data Using LangChain and RAG

Generative AI on Cloud

Working with ChatGPT (Self-paced)

Python with Generative AI (Self-paced)

Evaluating LLM Performance (Self-Paced)

Industry Case Studies and In-class Project (Self-Paced)

Bonus Module - Machine Learning with Generative AI (Self-paced)

Bonus Module - Generative AI Tools (Self-paced)

Prompt Engineering Online Course Details

About Prompt Engineer Certification Course Online

What are the learning outcomes of this Prompt Engineering Training?

Why should you enroll in the Online Prompt Engineer training Course?

Who should take up this Prompt Engineering online Course?

What are the prerequisites for this Prompt Engineering certification?

What is the Prompt Engineer Course fee?

What are the system requirements for this Prompt Engineering courses online?

How will I execute the practicals in this Prompt Engineering certification training?

What is the duration of this Prompt Engineer course?

Testimonial Reviews

Video Reviews

Prompt Engineer Course FAQs

What is Prompt Engineering?‎

Does Edureka provide a Prompt Engineering Training Course with Placement assistance?

What is the Background of Prompt Engineering with ChatGPT?

Can I attend a demo session before enrollment in Prompt Engineering Course Online?

What is the Prompt Engineering Course syllabus?‎

Who are the instructors for Prompt Engineering Course Online?

What if I have more queries after completion of Prompt Engineering Certification Course?

How can I learn prompt engineering?

How to create complex prompt-based applications for your life, business, or education?

What if I miss a class of Prompt Engineering Course?

How will Prompt Engineering help your career?

How Can Prompt Engineering Be Applied to Work Effectively with Large Language Models like ChatGPT?

Does ChatGPT use Prompt Engineering?

What is Prompt Engineering Salary?

Is it worth learning Prompt Engineering?

What are the basic skills of a Prompt Engineer?

How do we use prompt patterns to tap into powerful capabilities within large language models?

Does Edureka Provide a Prompt Engineering Training near me?

Does Prompt Engineering have a future?

Which AI tools are taught in this prompt engineering short-term training course?

How can a Prompt Engineering certification course advance my career?

Can a fresher become a Prompt Engineer?

Is coding required for Prompt Engineering?

What is an example of format length and audience in prompt engineering?

What is the purpose of prompt engineering in Gen AI systems?

Which is an example of iteration in prompt engineering?

What is an example of using roles in prompt engineering?

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