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Prompt Engineering Course
Prompt Engineering Course
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Live Online Classes starting on 18th May 2024
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Instructor-led Prompt Engineering with Generative AI live online Training Schedule
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Price 18,99916,149
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Why enroll for Prompt Engineering with Generative AI?
Prompt Engineering Course Benefits
Bloomberg recently reported that the generative AI market is poised to reach $1.3 trillion by 2032, and the World Economic Forum's โThe Future of Jobs Report 2020" predicts AI will replace 85 million jobs globally by 2025. Prompt engineering with Generative AI allows for better control of AI outputs and customization. This ensures desired results while minimizing biases and increasing the AI's reliability and utility. Join us now to harness the full power of generative AI.
Annual Salary
Hiring Companies
Want to become a Prompt Engineer?
Annual Salary
Hiring Companies
Want to become a Prompt Engineer?
Annual Salary
Hiring Companies
Want to become a Prompt Engineer?
Annual Salary
Hiring Companies
Want to become a Prompt Engineer?
Why Prompt Engineering with Generative AI 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 Generative AI
Prompt Engineering Skills Covered
Prompt Engineering Tools Covered
Prompt Engineering Course Curriculum
Curriculum Designed by Experts
Generative AI and its Industry Applications
7 Topics
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
![skill]( "Hands On Experience")
- Implementing Generative AI Use Cases
- Implementing Machine Learning with GenAI
![skill]( "skill you will learn")
- Generative AI Fundamentals
- Generative AI for Problem Solving
- Ethical Insights into Generative AI
NLP and Deep Learning
10 Topics
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
![skill]( "Hands On Experience")
- Simple Text Classification Task
- Implementing Core NLP Tasks
- Working with Deep Learning for NLP
![skill]( "skill you will learn")
- Text Classification
- Text Pre-processing
- Deep Learning Applications for NLP
- Neural Network Architectures
Autoencoders and GANs
8 Topics
Topics:
- Basic Autoencoders
- Variational Autoencoders (VAEs)
- Applications in Data Compression and Generation
- Basic GAN Architecture
- Training GANs
- Variants of GANs
- DCGAN
- CycleGAN
![skill]( "Hands On Experience")
- Working with GANs
- Data Compression with Autoencoders
- Training Variants of GANs
![skill]( "skill you will learn")
- Working with Autoencoders and VAEs
- GAN Architecture
- GAN Training Techniques
Language Models and Transformer-based Generative Models
8 Topics
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
![skill]( "Hands On Experience")
- Working with GPT
- Implementing BERT
- Applying Advanced Transformer Models
![skill]( "skill you will learn")
- Working with Language Models
- Transformer Architectures
- Implementing Transformer-based Models
Prompt Engineering
7 Topics
Topics:
- Prompt Engineering Principles
- What is Prompt Engineering?
- Importance and Applications
- Prompt Design Strategies
- Types of Prompting
- Crafting Effective Prompts
- Parameter Tuning
![skill]( "Hands On Experience")
- Designing Precise Prompts
- Experimenting with Various Prompt Design Strategies
- Advanced Parameter Tuning for Prompt Engineering
![skill]( "skill you will learn")
- Prompt Engineering Principles
- Crafting Effective Prompts
- Advanced Parameter Tuning for Prompts
Generative AI with LLMs
5 Topics
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
![skill]( "Hands On Experience")
- Experimenting with LLM
- Applying Fine-Tuning on Parameters
- LLM Project Lifecycle
- Reinforcement Learning Exercises
![skill]( "skill you will learn")
- LLM Scaling and Pre-training
- Fine-tuning Techniques for LLMs
- Implementing Reinforcement Learning in LLMs
LLMs for Search, Prediction, and Generation
6 Topics
Topics:
- Search Query Completion
- Next Word Prediction
- Word Embeddings
- Transformers
- Generating Text
- Stacking Attention Layers
![skill]( "Hands On Experience")
- Execute Search Query and Next-word Prediction using LLMs
- Implement LLMs with TensorFlow and PyTorch
- Build Chatbot using LLMs
![skill]( "skill you will learn")
- LLM Application in NLP Tasks
- LLM Implementation with Python Libraries
- Problem Solving using LLM
LangChain for LLM Application Development
7 Topics
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
![skill]( "Hands On Experience")
- Build an LLM-Powered Application using LangChain
- Experiment with Off-the-Shelf Chains in LangChain
- Deploy an LLM Application
![skill]( "skill you will learn")
- LangChain Implementation
- Grasping LangChain Foundations
- Developing LLM applications using LangChain
Interacting with Data Using LangChain and RAG
6 Topics
Topics:
- Understanding Retrieval-Augmented Generation (RAG)
- Document Loading and Splitting
- Vector Stores and Embeddings
- Retrieval
- Question Answering with Chatbots
- Building RAG Models using LangChain
![skill]( "Hands On Experience")
- Construct a LangChain-RAG Chatbot for Custom Data
- Deploy Chatbot in a Production Environment
- Develop a Basic RAG Model
![skill]( "skill you will learn")
- Document Management with Loading and Splitting
- Retrieval Techniques
- Chatbot-Based Question and Answering
- RAG Model Construction with LangChain
Generative AI on Cloud
8 Topics
Topics:
- Cloud Computing Foundations
- AWS S3
- Amazon EC2 Trn1n
- Amazon EC2 Inf2
- Amazon Sagemaker
- Amazon CodeWhisperer
- Amazon Bedrock
- Azure OpenAI
![skill]( "Hands On Experience")
- 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
![skill]( "skill you will learn")
- Working with Amazon EC2 Inf2 Instances
- Incorporating CodeWhisperer into AI Development
- Implementing Azure OpenAI for Generative AI Solutions
Working with ChatGPT (Self-paced)
16 Topics
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
![skill]( "Hands On Experience")
- 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
![skill]( "skill you will learn")
- Explore the power of ChatGPT
- Productivity Enhancement
- Programming with ChatGPT
- ChatGPT for Code Debugging and Documentation
- Software Testing using ChatGPT
Python with Generative AI (Self-paced)
5 Topics
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
![skill]( "Hands On Experience")
- Utilize Gen AI Tools to Enhance Coding Tasks
- Optimize a Code using the ChatGPT Gen AI Tool
- Create Python Scripts using ChatGPT
![skill]( "skill you will learn")
- Generative AI-Powered Python Coding
- Code Enhancement with ChatGPT
Evaluating LLM Performance (Self-paced)
6 Topics
Topics:
- LLM Performance Comparison
- Perplexity
- BLEU Score
- Human Evaluation
- Choosing the Right Metrics
- Interpreting the Results
![skill]( "Hands On Experience")
- Evaluate LLM using Various Performance Metrics
- Select Appropriate Metrics for Specific Generative AI Task
- Analyze LLM Performance
![skill]( "skill you will learn")
- LLM Performance Evaluation
- Interpreting LLM Performance Results
Industry Case Studies and In-class Project (Self-paced)
4 Topics
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
![skill]( "Hands On Experience")
- Building a Generative AI Powered Text and Image Generator
![skill]( "skill you will learn")
- Analyzing Generative AI Implementations
- Building Generative AI Models
Bonus Module - Machine Learning with Generative AI (Self-paced)
10 Topics
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
![skill]( "Hands On Experience")
- Experiment with Various AI Tools
- Implement a ML Model
- Explore Different Disciplines and Types of AI
![skill]( "skill you will learn")
- Machine Learning Fundamentals
- Machine Learning Algorithms
- Working with Predictive ML Models
Bonus Module - Generative AI Tools (Self-paced)
6 Topics
Topics:
- Hugging Face Transformers
- OpenAI GPT3 API
- Google Cloud AI Platform
- MidJourney
- DALL E-2
- Google Bard
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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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Prompt Engineering Course Details
About Prompt Engineering Course
This Prompt Engineering Course offers a comprehensive journey through Generative AI, covering fundamental concepts, Deep Learning in NLP, and advanced Generative Models like GANs and Transformers. You'll explore the crucial art of Prompt Engineering and dive into Large Language Models (LLMs) for various applications. Additionally, you'll gain practical skills with LangChain and RAG for effective data interaction and understand how to evaluate model performance. The Prompt Engineer course concludes with insights into essential Generative AI tools such as Hugging Face Transformers and the OpenAI GPT3 API for practical application and deployment. At the end of the course, you will be completing a capstone project to endorse your learning.
What are the learning outcomes of this Prompt Engineering Course?
The learning outcomes of this Prompt Engineering Course are as follows:
- Prompt Engineering
- Leveraging Generative AI
- Large Language Models
- LLM Application Development
- Working with ChatGPT
- Working with Popular GenAI Tools
Why take up the Online Prompt Engineering Course?
Enrolling in the Online Prompt Engineering Course offers a structured and effective way to gain the skills and knowledge needed to master AI model customization. This will enable you to leverage AI technology to its fullest potential for your specific applications and needs.
Who should take up this Prompt Engineering Course?
The Prompt Engineering Course is suitable for a wide range of individuals, including:
- AI professionals
- Developers
- Data scientists
- Business professionals
- Anyone interested in AI
What are the prerequisites for this Prompt Engineering with Generative AI course?
There are no prerequisites required for this Prompt Engineering with Generative AI course. However, it is beneficial to have:
- Basic Python Programming Knowledge
- Problem Solving Skills
- Fundamentals of Machine Learning
What is the Prompt Engineering Course fee?
The cost of the Prompt Engineering Course is INR18,999, but you can avail yourself of a 10% discount, and the discounted price is INR 17,099. The EMI starts at 5,700 / month with No Cost EMI.
What are the system requirements for this Prompt Engineering Course?
The system requirements for a Prompt Engineering course include:
- A computer: A laptop or desktop computer with a minimum of 8 GB RAM and Intel Core-i3 processor to run NLP and machine learning models is required.
- An internet connection: A stable and high-speed internet connection is necessary for accessing online course materials, videos, and software.
How will I execute the practicals in this Prompt Engineering Course?
Practicals for this course will be implemented using Python, VS Code and Jupyter Notebook. Detailed step-by-step installation guides are available on the LMS. In case you come across any doubt, the 24*7 support team will promptly assist you.
How long is the Prompt Engineering Course online?
The Prompt engineering course duration is 30 hrs. The batches are scheduled on the weekend. You can choose your flexible schedule and time while enrolling in the Prompt Engineering Certification course.
Prompt Engineering Certification
To unlock Edurekaโs Prompt Engineering course completion certificate, you must ensure the following:
- Completely participate in this Prompt Engineering with Generative AI course certificate.
- Evaluation and completion of the quizzes and projects listed as part of the curriculum.
Edureka provides industry-recognized course completion certificates for prompt engineering. These certificates have lifetime validity. To earn this certification, you need to enroll in the Prompt Engineering Certification Course and fulfill the minimum requirements.
Prompt Engineering certification provides several distinct advantages:
- Skills Validation: Proving proficiency in tailoring AI models has become increasingly sought-after across industries.
- Career Advancement: Certification can provide opportunities and career advancement in fields like content generation, data analysis and AI development.
- Competitive Edge: It demonstrates your expertise in AI customization and problem-solving that sets you apart from others.
- Industry Relevance: Generative AI technology can be found across industries, making your certification relevant and applicable across numerous fields.
- Ethical AI Practices: Certification programs typically include training on ethical AI usage and emphasizing responsible practices, which have become increasingly significant.
- Entrepreneurship: Certification equips you to develop AI-powered solutions while encouraging entrepreneurship and innovation within AI applications.
- Professional Networks: Certification programs often present an excellent opportunity to network with industry professionals and expand your professional connections.
After earning your Prompt Engineering certification, you could be qualified for various job roles related to Prompt Engineering and Generative AI. Some examples may include being qualified for: Prompt Engineer, NLP Engineer, Chatbot Developer, Data Scientist and AI Engineer as well as Content Creator or Social Media Influencer roles.
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Prompt Engineering Course FAQs
What is Prompt Engineering?โ
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.
Will I get placement assistance after completing this Prompt Engineering Course?
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 kinds of jobs can you get with Prompt Engineering skills?โ
Here are some potential job roles:
- Machine Learning Engineer
- Data Scientist
- Natural Language Processing (NLP) Engineer
- AI Research Scientist
- Software Engineer (AI/ML)
- Data Engineer
- Conversational AI Developer
- AI Product Manager
- AI Ethicist
Can I attend a demo session before enrollment in Prompt Engineering Course Online?
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.
What is the Prompt Engineering Course syllabus?โ
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?
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.
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 boost your career dramatically 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.
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 โน7,41,000 in India, and The average Prompt hourly pay ranges from approximately $17 per hour for a Picker/Packer to $55 per hour for a Software Engineer. Prompt employees rate the overall compensation and benefits package as 3.7/5 stars.
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
What are Large Language Models?
LLMs can be defined as models with a large set of parameters and data that make them especially powerful in natural language understanding and generation, including content creation and chatbots; data analysis, and customer support services.
How can beginners leverage Generative AI?
Beginners can take advantage of Generative AI as a tool for producing human-like text based on the input provided. This can prove valuable across a range of applications, such as:
Content Generation:
Creative Writing
Learning and Research
Translation Services
Coding Assistance
Conversational Agents
Business Applications
Does Edureka Provide a Prompt Engineering Course near me?
Yes, Edureka provides the best Prompt Engineering Course worldwide. Edureka offers online courses, so their Prompt Engineering 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.
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