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Introduction to Generative AI

Introduction to Generative AI

Name: Introduction to Generative AI
Item: Introduction to Generative AI
Rating: 5
Author: Janardhan Singamaneni

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Embark on a journey to harness the full potential of Generative AI with our expertly curated foundation course. Explore the fascinating world of AI-driven innovation, master the cutting-edge techniques directly from the leading industry experts, and apply the acquired knowledge to practice. Join us to be a part of this AI revolution and propel your career to the next level.

3k+ satisfied learners Read Reviews

Why should you take Introduction to Generative AI Fundamental Course?

Bloomberg Intelligence reported that market size for Generative AI is poised to reach $1.3 Trillion by 2032

Generative AI products can add up to $280 billion in software revenue from personalized assistants and coding copilots

OpenAI is actively hiring applied AI researchers and prompt engineers with salaries up to $370,000 - LinkedIn

Curriculum

Generative AI Fundamentals

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

Hands On:

Implementing Generative AI Use Cases

Skills You Will Learn:

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

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Prompt Engineering

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

Hands On:

Designing Precise Prompts
Experimenting with Various Prompt Design Strategies

Skills You Will Learn:

Prompt Engineering Principles
Crafting Effective Prompts

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Deep Learning and NLP Essentials

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

Hands On:

Working with GANs
Data Compression with Autoencoders
Working with GPT Implementing BERT

Skills You Will Learn:

Working with Autoencoders and VAEs
Working with Language Models
Transformer Architecture
Implementing Transformer-based Models

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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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Generative AI Industry Use Cases

Topics:

Generative AI for Software Development
Generative AI for Data Science
Generative AI for Retail
Generative AI Application in Marketing

Hands On:

Leveraging Generative AI for Software Development
Generative AI for Retail
Application of Generative AI in Marketing

Skills You Will Learn:

Code Generation
Creating Images
Content Generation

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Building an Interactive Chatbot

Topics:

Interactive Chatbot using Rasa
Chatbot using ChatGPT API

Hands On:

Build an interactive chatbot using Rasa
Build a chatbot using ChatGPT API

Skills 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.

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Testimonial Reviews

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Anil AlgolePrinciple Consultant at Infosys

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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?‎

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 ₹11,03,357 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?

Edureka’s 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.

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Structure your learning and get a certificate to prove it.

Introduction to Generative AI

Why should you take Introduction to Generative AI Fundamental Course?

Curriculum

Generative AI Fundamentals

Prompt Engineering

Deep Learning and NLP Essentials

Generative AI with LLMs

Generative AI Industry Use Cases

Building an Interactive Chatbot

Introduction to Generative AI Learning Path Details

About Introduction to Generative AI Fundamentals Course

What are the learning outcomes of this Introduction to Generative AI learning path Course?

Why take up this Introduction to Generative AI Fundamentals Course?

Who should take up this Generative AI learning path Course?

What are the prerequisites for this Introduction to Generative AI fundamentals Course?

What are the system requirements for this Introduction to Generative AI fundamentals course?

How will I execute the practical in this Generative AI learning path Course?

Testimonial Reviews

Video Reviews

Generative AI Fundamentals Course FAQs

What is Generative AI?

What is Prompt Engineering?‎

Will I get placement assistance after completing this Introduction to Generative AI Fundamental Course?

Who are the instructors for Introduction to Generative AI Fundamental Course?

Is the Introduction to Generative AI program worth it?

What if I have more queries after completion of Introduction to Generative AI learning path Course?

What if I miss a class of Introduction to Generative AI Course?

How much time is required to learn generative AI basics?

What is the salary of beginners in generative AI?

What are the other Courses on Artificial Intelligence provided by Edureka?

Which is the best Introduction to a Generative AI program?

Is coding knowledge required for generative AI?

What is the cost of an Introduction to Generative AI program?

How can I get started with Generative AI?

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