Generative AI Fundamentals Specialization
Generative AI Fundamentals Specialization, available at $54.99, has an average rating of 3.4, with 9 lectures, 1 quizzes, based on 12 reviews, and has 2179 subscribers.
You will learn about Define Generative AI and its use-cases Learn about Large Language Models (LLM) Understand the LLMs in the AI landscape Get a grasp of Prompt Engineering Understand the Tools for Prompt Engineering Learn the fundamentals & importance of Responsible AI Understand Google's 7 AI principles Comprehend the impact, considerations, and ethical Issues of Generative AI This course is ideal for individuals who are Beginners and newbies aspiring for a career in Generative AI or Generative AI Scientists or AI Scientists & Engineers or Anyone interested in Artificial Intelligence and genAI or Generative AI Field Solutions Architect Managers or Generative AI Product Owners or Machine Learning Scientists or Machine Learning Engineers or Generative AI Specialists or Deep Learning Engineers or Data Scientists or Generative AI Leads or Generative AI Specialists or Data Science Managers or Data Pipeline Engineers or Data Engineers It is particularly useful for Beginners and newbies aspiring for a career in Generative AI or Generative AI Scientists or AI Scientists & Engineers or Anyone interested in Artificial Intelligence and genAI or Generative AI Field Solutions Architect Managers or Generative AI Product Owners or Machine Learning Scientists or Machine Learning Engineers or Generative AI Specialists or Deep Learning Engineers or Data Scientists or Generative AI Leads or Generative AI Specialists or Data Science Managers or Data Pipeline Engineers or Data Engineers.
Enroll now: Generative AI Fundamentals Specialization
Summary
Title: Generative AI Fundamentals Specialization
Price: $54.99
Average Rating: 3.4
Number of Lectures: 9
Number of Quizzes: 1
Number of Published Lectures: 9
Number of Published Quizzes: 1
Number of Curriculum Items: 10
Number of Published Curriculum Objects: 10
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Define Generative AI and its use-cases
- Learn about Large Language Models (LLM)
- Understand the LLMs in the AI landscape
- Get a grasp of Prompt Engineering
- Understand the Tools for Prompt Engineering
- Learn the fundamentals & importance of Responsible AI
- Understand Google's 7 AI principles
- Comprehend the impact, considerations, and ethical Issues of Generative AI
Who Should Attend
- Beginners and newbies aspiring for a career in Generative AI
- Generative AI Scientists
- AI Scientists & Engineers
- Anyone interested in Artificial Intelligence and genAI
- Generative AI Field Solutions Architect Managers
- Generative AI Product Owners
- Machine Learning Scientists
- Machine Learning Engineers
- Generative AI Specialists
- Deep Learning Engineers
- Data Scientists
- Generative AI Leads
- Generative AI Specialists
- Data Science Managers
- Data Pipeline Engineers
- Data Engineers
Target Audiences
- Beginners and newbies aspiring for a career in Generative AI
- Generative AI Scientists
- AI Scientists & Engineers
- Anyone interested in Artificial Intelligence and genAI
- Generative AI Field Solutions Architect Managers
- Generative AI Product Owners
- Machine Learning Scientists
- Machine Learning Engineers
- Generative AI Specialists
- Deep Learning Engineers
- Data Scientists
- Generative AI Leads
- Generative AI Specialists
- Data Science Managers
- Data Pipeline Engineers
- Data Engineers
A warm welcome to the Generative AI Fundamentals Specializationcourse by Uplatz.
Generative AI, also known as genAI, is a powerful and exciting field of artificial intelligence focused on creating new content, unlike many other AI systems that primarily analyze or interpret existing data. It can produce diverse outputs like:
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Text: Poems, code, scripts, musical pieces, emails, letters, etc.
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Images: Photorealistic portraits, landscapes, abstract art, 3D models, etc.
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Audio: Music in various styles, sound effects, speech, etc.
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Video: Realistic simulations, stylized animations, etc.
How Generative AI works
Imagine generative AI as a highly creative artist trained on massive amounts of data (text, images, etc.). This training allows it to:
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Learn patterns and relationships within the data. For example, how words typically combine in sentences, how light interacts with objects to create an image, or how musical notes sequence to form melodies.
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Develop statistical models that capture these patterns. These models act like internal “recipes” for generating new content.
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Receive prompts or inputs from users, which guide the creative process. This could be a text description, a sketch, or even just a style preference.
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Use its models and the provided prompts to generate entirely new creations that resemble the training data but are not simply copies.
Different techniques used in generative AI
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Generative Adversarial Networks (GANs): Two AI models compete, one creating new content, the other trying to distinguish it from real data. This competition refines the generative model’s ability to create realistic outputs.
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Variational Autoencoders (VAEs): Encode data into a latent space, allowing for manipulation and generation of new data points within that space.
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Transformers: Powerful neural network architectures adept at understanding and generating text, code, and other sequential data.
Key points to remember
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Generative AI is still under development, but it’s rapidly evolving with amazing potential.
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While highly creative, it’s crucial to remember it’s still a machine and the ethical implications of its outputs need careful consideration.
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It’s a powerful tool for various applications like art, design, drug discovery, and more.
Generative AI Fundamentals Specialization – Course Curriculum
Introduction to Generative AI
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What is Generative AI?
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Journey of Generative AI
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How does Generative AI works?
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Applications of generative AI in different sectors and industries
Introduction to Large Language Models (LLM)
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What is LLM?
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How do large language models work?
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General Architecture of Large Language Model
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What can a language model do?
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What are the challenges and limitations of LLM?
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LLM in the AI landscape
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LLM use cases/Application
Generative AI: Prompt Engineering Basics
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What is prompt Engineering?
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Relevance of prompt engineering in generative AI models
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Creating prompts and explore examples of impactful prompts
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Commonly used tools for prompt engineering to aid with prompt engineering
Introduction to Responsible AI
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What is Responsible AI?
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Why it’s important?
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How Google implements responsible AI in their products?
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Google’s 7 AI principles
Generative AI: Impact, Considerations, and Ethical Issues
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Limitations of generative AI and the related concerns
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Identify the ethical issues, concerns, and misuses associated with generative AI
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Considerations for the responsible use of generative AI
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Economic and social impact of generative AI
Course Curriculum
Chapter 1: Introduction to Generative AI
Lecture 1: Part 1 – Introduction to Generative AI
Lecture 2: Part 2 – Introduction to Generative AI
Lecture 3: Part 3 – Introduction to Generative AI
Chapter 2: Introduction to Large Language Models (LLMs)
Lecture 1: Part 1 – Introduction to Large Language Models (LLMs)
Lecture 2: Part 2 – Introduction to Large Language Models (LLMs)
Chapter 3: Prompt Engineering
Lecture 1: Part 1 – Prompt Engineering
Lecture 2: Part 2 – Prompt Engineering
Chapter 4: Responsible AI
Lecture 1: Responsible AI
Chapter 5: Generative AI Impact, Considerations, and Ethical Issues
Lecture 1: Generative AI Impact, Considerations, and Ethical Issues
Chapter 6: End of Course Quiz
Instructors
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Uplatz Training
Fastest growing global Technology & Cloud Training Provider
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 3 votes
- 3 stars: 1 votes
- 4 stars: 1 votes
- 5 stars: 5 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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