Skills you will learn

  • Fundamentals of AIML and Deep Learning
  • Understanding Neural Networks and Transformer Architectures
  • Natural Language Processing
  • LLMs, GANs, VAEs, and Diffusion Models
  • Prompt Engineering Techniques
  • Working with Gemini, Claude, and other GenAI Tools
  • GenAI Applications across Business Domains
  • Responsible AI, Security, and Bias in GenAI
  • Workflow Automation using GenAI Tools

Who should learn

  • Software Developers
  • Data Scientists
  • Business Analysts
  • Product Managers
  • Marketing Professionals
  • Students

What you will learn

  • Introduction to Generative AI Fundamentals

    • Lesson 01: Introduction

      03:43
      • 1.01 Introduction to Generative AI Fundamentals Concepts Use Cases and Practical Essentials
        01:30
      • 1.02 Kickstarting with Generative AI Fundamentals Concepts Use Cases and Practical Essentials
        02:13

    • Lesson 02: Overview of Artificial Intelligence (AI), Machine Learning ML and Deep Learning DL (1)

      59:28
      • 2.01 Lesson Introduction
        03:01
      • 2.02 Introduction to Artificial Intelligence
        03:04
      • 2.03 Evolution of Artificial Intelligence
        03:27
      • 2.04 Types of AI
        01:44
      • 2.05 Key Components of AI
        03:03
      • 2.06 AI in Everyday Life and Its Benefits
        02:32
      • 2.07 Challenges of AI and Why AI is Powerful
        03:46
      • 2.08 Early AI Milestones and the Rise of Machine Learning
        03:08
      • 2.09 Emergence of Deep Learning and Key Breakthroughs in AI
        03:26
      • 2.10 Case Study Google Ads
        02:40
      • 2.11 Introduction to Machine Learning
        02:03
      • 2.12 Types of Machine Learning
        02:15
      • 2.13 Applications of Machine Learning in Business
        02:33
      • 2.14 Case Study Netflix
        02:25
      • 2.15 Understanding Reinforcement Learning and Deep Learning
        02:58
      • 2.16 Case Study Amazon Alexa
        02:09
      • 2.17 Machine Learning vs Deep Learning
        02:28
      • 2.18 ML and DL Applications
        02:49
      • 2.19 Introduction to Neural Networks
        02:50
      • 2.20 Types of Neural Networks
        03:13
      • 2.21 Case Study Amazon
        01:55
      • 2.22 Key Takeaways
        01:59

    • Lesson 03: Introduction to Transformers, Advanced AI Models and Natural Language Processing NLP

      01:18:04
      • 3.01 Lesson Introduction
        02:31
      • 3.02 Attention Mechanism and Transformers
        03:44
      • 3.03 Types of Attention Mechanism
        04:33
      • 3.04 Introduction to Transformer Models
        03:18
      • 3.05 Understanding Self Attention
        03:00
      • 3.06 Understanding How Self Attention Works
        03:00
      • 3.07 Transformer Model Architecture
        02:15
      • 3.08 How Encoders Work
        03:00
      • 3.09 How Decoders Work
        04:46
      • 3.10 Text Processing in Transformers
        03:59
      • 3.11 How Transformers Revolutionized AI
        02:49
      • 3.12 Transformer Model Advantages
        03:15
      • 3.13 Introduction to BERT
        03:13
      • 3.14 How BERT Learns Through MLM
        03:11
      • 3.15 Real World Applications of BERT
        03:38
      • 3.16 Introduction to GPT Models
        02:53
      • 3.17 Zero Shot Learning Few Shot Learning and Prompt Engineering
        02:57
      • 3.18 Introduction to Natural Language Processing (NLP)
        02:29
      • 3.19 NLP How It Works and What It Powers
        02:30
      • 3.20 Categories of NLP and Techniques Used in NLP
        04:15
      • 3.21 Real-World Applications of NLP Chatbots
        02:37
      • 3.22 Text Classification and Its Common Applications
        03:23
      • 3.23 Applications of NLP in Business
        02:27
      • 3.24 Case Study Bank of America
        02:00
      • 3.25 Key Takeaways
        02:21

    • Lesson 04: Overview of GenAI and AI Project Implementation

      58:47
      • 4.01 Lesson Introduction
        01:48
      • 4.02 What Are GenAI Models
        04:12
      • 4.03 Transformer Based Large Language Models
        02:58
      • 4.04 GAN Based Models
        03:25
      • 4.05 VAE Based Models
        02:47
      • 4.06 Diffusion Models
        02:44
      • 4.07 Capabilities and Limitations of GenAI Models
        02:31
      • 4.08 Introduction to GenAI Applications and Tools
        02:48
      • 4.09 GenAI Tools and Business Use Cases
        03:37
      • 4.10 Introduction to Prompt Engineering
        03:54
      • 4.11 Demo Generating a Product Launch Campaign Using ChatGPT
        04:11
      • 4.12 Introduction to the GenAI Open Source Landscape
        03:48
      • 4.13 Demo Exploring AI Capabilities with Hugging Face Spaces
        09:56
      • 4.14 GenAI Security Bias and Responsible Use
        04:44
      • 4.15 Future of AI and Emerging Trends
        03:25
      • 4.16 Key Takeaways
        01:59

    • Lesson 05: Working with GPTs

      01:47:38
      • 5.01 Day to Day Tasks ChatGPT Can Do
        02:23
      • 5.02 Demo Multilingual Book Translation Using ChatGPT ​
        03:24
      • 5.03 Demo Creating a LinkedIn Profile Using ChatGPT​
        07:01
      • 5.04 Demo Sentiment Analysis of User Reviews Using ChatGPT ​
        03:46
      • 5.05 ChatGPT Multimodal Capabilities
        03:04
      • 5.06 Demo Exploring Multimodal Capabilities of ChatGPT
        09:40
      • 5.07 Demo Customer Feedback Analysis Using ChatGPT
        05:01
      • 5.08 Comparison Between ChatGPT 3 5 4 and 4o
        05:08
      • 5.09 ChatGPT Comparison Based on a Use Case​
        04:04
      • 5.10 Comparison Based on a Prompt
        03:15
      • 5.11 Exploring GPTs Categories and Use Cases With Examples
        05:36
      • 5.12 Demo Creating Marketing Content for Eco Friendly Water Bottles Using Write for Me GPT
        03:35
      • 5.13 Demo Designing Visually Appealing Content Using Canva GPT​
        03:21
      • 5.14 Demo Creating a Website Design Using DesignerGPT
        05:37
      • 5.15 Demo Streamlining Literature Surveys on LLM Impact with Consensus GPT
        06:30
      • 5.16 Demo Enhancing Educational Material Using Universal Primer GPT
        06:18
      • 5.17 Generative AI in Business Impact Across Domains and Workflow Automation
        01:30
      • 5.18 Demo Setting Up a Zapier Account and Creating a Zap
        06:53
      • 5.19 Sales and Marketing
        01:30
      • 5.20 Demo Creating a Video Using AI
        04:07
      • 5.21 Software Engineering
        01:08
      • 5.22 Demo Designing User Interfaces with Generative AI​
        03:45
      • 5.23 Data Analytics
        00:47
      • 5.24 Demo Data Integrity Using GenAI
        03:39
      • 5.25 Customer Service and Operations
        02:16
      • 5.26 Demo Transcribing Audio Calls to Text
        04:20

    • Lesson 06: Advanced GenAI Tools

      15:22
      • 6.01 Gemini
        01:47
      • 6.02 Demo Marketing Strategy Using Gemini
        04:02
      • 6.03 Descript
        00:26
      • 6.04 Demo Creating a Video Using Descript
        04:05
      • 6.05 Claude
        00:53
      • 6.06 Demo Creating a Blog Post Using Claude
        03:22
      • 6.07 Sora
        00:47
      • Knowledge check
About the Course:

This course introduces you to Generative AI, starting with the basics of Artificial Intelligence, Machine Learning, and Deep Learning. You'll move on to more advanced topics like Transformer models, Large Language Models, and Generative AI tools. Along the way, you'll explore real business uses for Generative AI, try out hands-on exercises with tools such as ChatGPT, Gemini, and Claude, and build skills in prompt engineering and workflow automation. The course is designed for both beginners and those who want to deepen their knowledge, helping you gain the skills needed to use Generative AI at work.Read More

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FAQs

  • Is this course free?

    Yes, this course is free. You can access all lessons and demos for free and still receive a professional certificate upon successful completion.

  • Is this course beginner-friendly?

    Yes, this course is designed for beginners and starts from the very fundamentals of AI, Machine Learning, and Deep Learning before progressing to Generative AI concepts and tools.

  • Are there any prerequisites for this course?

    There are no strict prerequisites. A basic curiosity about AI and technology is all you need to get started, as the course is designed to build your knowledge from the basics.

  • What topics are covered in this course?

    This course covers AI, Machine Learning, Deep Learning, Neural Networks, Transformer models, BERT, GPT, NLP, GenAI models, prompt engineering, ChatGPT, Gemini, Claude, Sora, and GenAI applications across business domains.

  • Does this course cover ChatGPT in detail?

    Yes, Lesson 05 is extensively dedicated to working with GPTs, covering ChatGPT capabilities, multimodal features, version comparisons, specialized GPTs, and business automation with hands-on demos throughout.

  • What GenAI tools will I learn in this course?

    The course covers a wide range of GenAI tools, including ChatGPT, Gemini, Claude, Sora, Descript, Hugging Face, Canva GPT, DesignerGPT, Consensus GPT, Universal Primer GPT, Write for Me GPT, and Zapier for workflow automation.

  • Does this course explain prompt engineering?

    Yes, the course covers prompt engineering concepts, including zero-shot learning and few-shot learning, and includes a hands-on demo on generating a product launch campaign using ChatGPT to put these concepts into practice.

  • Does this course address responsible AI and bias?

    Yes, Lesson 04 includes a dedicated sub-lesson on GenAI security, bias, and responsible use, helping you understand the ethical considerations and risks associated with deploying Generative AI in real-world applications.

  • Are there real-world case studies included in this course?

    Yes, the course includes multiple real-world case studies from leading organizations such as Google Ads, Netflix, Amazon Alexa, Amazon, and Bank of America, demonstrating how AI and GenAI are applied in practice.

  • Does this course include hands-on demos?

    Yes, the course is packed with hands-on demos covering product launch campaigns, multilingual translation, sentiment analysis, marketing strategies, video creation, UI design, blog writing, and more using various GenAI tools.

  • What is the difference between Machine Learning and Deep Learning?

    Machine Learning involves algorithms that learn patterns from data to make predictions, while Deep Learning is a subset of ML that uses multi-layered neural networks to learn complex representations. Both are covered in detail in Lesson 02.

  • How long will it take to complete this course?

    This course has a total duration of approximately 5.5 hours and is fully self-paced.

  • Is a certificate provided upon completion of this course?

    Yes, you will receive a free professional certificate, which you can add to your resume to demonstrate your Generative AI knowledge to potential employers.

  • Is this course accessible via mobile phone?

    Yes, this course is accessible on both desktop and mobile devices. You can learn anytime, anywhere, at your own pace.

  • Can I add this certificate to my LinkedIn profile?

    Yes, once you complete the course and receive your certificate, you can add it to your LinkedIn profile under the Licenses and Certifications section to showcase your Generative AI expertise to recruiters and employers.

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  • Career Impact Results vary based on experience and numerous factors.