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Introduction to Generative AI
Introduction to Generative AI
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Why enroll for Introduction to Generative AI Fundamental Course?
Learn Generative AI Fundamentals 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. The Introduction to Generative AI Fundamental course helps you to harness the power of generative AI for various industry applications. Join us now to harness the full power of generative AI.
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Why Introduction to Generative AI Fundamental 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 Introduction to Generative AI Fundamental Course
Skills Covered in Generative AI Learning Path
Tools Covered in Generative AI Learning Path
Introduction to Generative AI Fundamentals Course Curriculum
Curriculum Designed by Experts
Generative AI Fundamentals
9 Topics
Topics
- Introduction to Generative AI
- What is Generative AI?
- Generative AI explained
- Generative vs Discriminative Models
- Popular Generative AI Tools
- Applications of Generative Models
- Applications of Generative AI
- Generative AI: Advantages and Disadvantages
- Ethical Considerations
![skill]( "Hands On Experience")
- Implementing Generative AI Use Cases
![skill]( "skill you will learn")
- Generative AI Fundamentals
- Generative AI for Problem Solving
- Ethical Insights into Generative AI
Prompt Engineering
10 Topics
Topics
- Introduction to Prompt Engineering
- Why Prompt Engineering?
- What is Prompt Engineering?
- Applications of Prompt Engineering
- Importance and Applications
- Prompt Design Strategies
- Types of Prompting
- Priming Prompts
- Prompt Decomposition
- How to Get Better Responses from ChatGPT
![skill]( "Hands On Experience")
- Designing Precise Prompts
- Experimenting with Various Prompt Design Strategies
![skill]( "skill you will learn")
- Prompt Engineering Principles
- Crafting Effective Prompts
Deep Learning and NLP Essentials
12 Topics
Topics
- Natural Language Processing (NLP) Essentials
- Deep Learning Fundamentals
- Neural Networks
- Basic Autoencoders
- Variational Autoencoders (VAEs)
- Applications in Data Compression and Generation
- GAN Architecture
- Exploring Language Models
- Types of Language Models
- Applications of Language Models
- The Transformer Architecture: Attention Mechanism
- Advanced Transformer Models
![skill]( "Hands On Experience")
- Working with GANs
- Data Compression with Autoencoders
- Working with GPT
- Implementing BERT
![skill]( "skill you will learn")
- Working with Autoencoders and VAEs
- Working with Language Models
- Transformer Architecture
- Implementing Transformer-based Models
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
Generative AI Industry Use Cases
3 Topics
Topics
- Generative AI for Software Development
- Generative AI for Retail
- Generative AI Application in Marketing
- Generative AI for Data Science
![skill]( "Hands On Experience")
- Leveraging Generative AI for Software Development
- Generative AI for Retail
- Application of Generative AI in Marketing
![skill]( "skill you will learn")
- Code Generation
- Creating Images
- Content Generation
Building an Interactive Chatbot
2 Topics
Topics
- Interactive Chatbot using Rasa
- Chatbot using ChatGPT API
![skill]( "Hands On Experience")
- Build an interactive chatbot using Rasa
- Build a chatbot using ChatGPT API
![skill]( "skill you will learn")
- ChatGPT API integration
- Chatbot creation
- Rasa framework integration
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Introduction to Generative AI Learning Path Details
About Introduction to Generative AI Fundamentals Course
This course on Introduction to Generative AI is designed to equip learners with a solid understanding of generative models, from fundamental concepts to advanced applications. Starting with the basics, learners will grasp the principles of Generative AI, differentiate between generative and discriminative models, and explore popular tools in the field. Ethical considerations are addressed alongside practical skills like prompt engineering and deep learning techniques such as autoencoders and GANs. Advanced topics include working with large language models (LLMs), fine-tuning them for specific tasks, and applying reinforcement learning. Real-world industry applications are emphasized, from software development to marketing, and participants gain hands-on experience in creating code, images, and interactive chatbots using frameworks like Rasa and ChatGPT API.
What are the learning outcomes of this Introduction to Generative AI learning path Course?
Upon completing the Introduction to Generative AI Fundamentals Course, participants will attain the following learning outcomes:
- Develop a comprehensive understanding of generative AI, including its principles, applications, and significance across various domains.
- Gain practical experience through interactive sessions and exercises, enabling participants to apply theoretical concepts to real-world scenarios.
- Familiarize with popular generative AI algorithms such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models.
- Explore the creative potential of generative AI in generating realistic images, text, music, and other forms of media, fostering innovation and experimentation.
- Understand the ethical implications and considerations associated with generative AI, including privacy, bias, and misuse, and learn strategies to address them responsibly.
- By the course's conclusion, learners will be equipped with the foundational understanding, practical skills, and ethical awareness necessary to leverage generative AI effectively and responsibly in their respective fields.
Why take up this Introduction to Generative AI Fundamentals Course?
Enroll in the Introduction to Generative AI fundamentals Course to acquire a thorough grasp of generative models, covering everything from basic concepts to cutting-edge uses. Delve into ethical considerations and practical techniques for creating generative AI solutions for actual industry situations, equipping you for various positions in AI advancement and creativity.
Who should take up this Generative AI learning path Course?
This course on Introduction to Generative AI is perfect for individuals aiming to pursue a career in AI, including data scientists, researchers, and developers who wish to explore generative models. It is also beneficial for professionals in various sectors like software development, marketing, and retail who want to utilize AI for problem-solving and innovation. Regardless of your level of experience, whether you are a novice or a seasoned practitioner, this course provides valuable knowledge and practical skills to enhance your expertise in Generative AI.
What are the prerequisites for this Introduction to Generative AI fundamentals Course?
There are no prerequisites required for this course on Introduction to Generative AI. However, it is beneficial to have:
- Basic Python Programming Knowledge
- Problem Solving Skills
- Fundamentals of Machine Learning
What are the system requirements for this Introduction to Generative AI fundamentals course?
The system requirements for a Introduction to Generative AI fundamentals 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.
- Stable and high-speed internet connection is necessary for accessing online course materials, videos, and software.
How will I execute the practical in this Generative AI learning path 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.
Projects in Generative AI Learning Path
Question answering with a fine-tuned BERT
The objective of this project is to develop a question-answering system that can accurately extract answers from given passages or contexts. By fine-tuning the pre-trained BERT m....Building an Interactive Chatbot
This chatbot involves developing a conversational agent capable of understanding and responding to user input naturally. This entails training models for natural language underst....Generative AI for Beginners Certification
To unlock Edurekaโs Introduction to Generative AI Fundamental course completion certificate, you must ensure the following:
- Completely participate in this Introduction to Introduction to Generative AI fundamental program.
- Evaluation and completion of the quizzes and projects listed.
The Generative AI fundamental Certification Introduction enhances the value of your credentials by confirming your expertise in this fast-developing area. It showcases your adeptness in grasping generative models and ethical aspects, as well as practical abilities such as prompt engineering and implementing generative AI solutions. This certification boosts your credibility and attractiveness to the market, creating pathways for career growth in AI-related positions within different industries.
After completing the Generative AI fundamental program, you will qualify for various job opportunities in the artificial intelligence field. These positions encompass roles such as:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Research Scientists working in AI and Machine Learning
- AI Developer
- Software Engineer specializing in AI applications
- Natural Language Processing (NLP) Engineer
- Computer Vision Engineer
- AI Consultant
- Product Manager for AI-driven solutions
Equipped with your acquired expertise in generative AI, you can actively contribute to cutting-edge projects, research initiatives, and innovation spanning across diverse industries.
John Doe
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with Grade X
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Generative AI Fundamentals Course FAQs
What is Generative AI?
Generative AI is a branch of artificial intelligence that focuses on producing or creating fresh content, such as images, text, audio, or even videos, that closely resembles data generated by humans. In contrast to conventional AI models that learn to identify patterns or make decisions based on existing data (discriminative models), generative AI models are trained to produce new data that mirrors the original training data. These models have a wide range of applications, including generating images, text, synthesizing data, and even engaging in creative tasks like art and music generation.
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 Introduction to Generative AI Fundamental 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.
Who are the instructors for Introduction to Generative AI Fundamental 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.
Is the Introduction to Generative AI program worth it?
Yes! Introduction to Generative AI is indeed a worthwhile investment for several compelling reasons. This course offers an extensive and approachable initiation into the captivating realm of generative artificial intelligence.
What if I have more queries after completion of Introduction to Generative AI learning path Course?
Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co.
What if I miss a class of Introduction to Generative AI 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 much time is required to learn generative AI basics?
The duration of this Introduction to Generative AI program is 21 hours. The batches will be scheduled on weekend.
What is the salary of beginners in generative AI?
According to Glassdoor, the average salary for an AI Engineer in India is โน11,03,357 per year.
What are the other Courses on Artificial Intelligence provided by Edureka?
Here is the list of courses offered by Edureka:
Which is the best Introduction to a Generative AI program?
Edurekaโs Introduction to Generative AI program is well-suited for both beginners and professionals. It covers the basics of advanced concepts.
Is coding knowledge required for generative AI?
While coding knowledge is not necessarily a strict requirement for understanding the concepts and applications of generative AI, it can significantly enhance your ability to work with generative models effectively.
What is the cost of an Introduction to Generative AI program?
The Introduction to Generative AI program costs INR14,999, but you can get it at INR 12,749 at 15% OFF, saving INR 2,250. This offer is for a limited time only. You can also opt for a no-cost EMI starting at INR 4,250 per month.
How can I get started with Generative AI?
To get started with Introduction to Generative AI, you can:
- Enroll in the Introduction to Generative AI Learning Path course.
- Read research papers and books on Generative AI.
- Experiment with open-source code repositories and frameworks.
- Join online communities and forums to learn from others and seek advice.
Be future ready, start learning
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