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(2 Ratings)

Generative AI

Categories: AI
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About Course

Students will be able to understand and apply generative AI techniques to solve real-world problems, culminating in the creation of a generative AI-driven project relevant to industry needs.

Module 1: Introduction to Generative AI

Lesson Plan:

  • Learning Objectives: Understand what generative AI is and its applications.
  • Real World Example: Generative AI in content creation (e.g., text, images, music).
  • Activities:
    1. Watch a video introduction to generative AI.
    2. Discuss examples of generative AI in various industries.
    3. Explore a simple generative AI tool (e.g., ChatGPT for text generation).
  • Discussion Questions:
    • How can generative AI be used to address real-world challenges?
    • What are some ethical considerations of using generative AI?
  • Ways to Expand Learning:
    • Research different generative AI models and their uses.
    • Join online forums or groups focused on AI innovation.

Module 2: Fundamentals of Generative AI Models

Lesson Plan:

  • Learning Objectives: Learn about different types of generative AI models and their functions.
  • Real World Example: Generative Adversarial Networks (GANs) for image synthesis.
  • Activities:
    1. Read an article on GANs and their applications.
    2. Watch a tutorial on creating a simple GAN model.
    3. Discuss how GANs can be applied in various industries.
  • Discussion Questions:
    • How do GANs differ from other generative models?
    • What are the limitations of GANs in practical applications?
  • Ways to Expand Learning:
    • Experiment with pre-built GAN models.
    • Explore advanced topics in generative AI research.

Module 3: Designing a Generative AI Project

Lesson Plan:

  • Learning Objectives: Design a project plan for a generative AI application.
  • Real World Example: Creating a chatbot for customer service.
  • Activities:
    1. Define the problem your project will address.
    2. Outline the steps needed to develop your AI solution.
    3. Create a project proposal with goals, research, and implementation strategies.
  • Discussion Questions:
    • What are the key components of a successful AI project proposal?
    • How can you ensure your project aligns with industry needs?
  • Ways to Expand Learning:
    • Review case studies of successful generative AI projects.
    • Seek feedback from industry experts on your project proposal.

Module 4: Developing and Training Generative AI Models

Lesson Plan:

  • Learning Objectives: Understand the development and training processes of generative AI models.
  • Real World Example: Training a text generation model for content creation.
  • Activities:
    1. Follow a tutorial on training a generative model using a dataset.
    2. Experiment with adjusting model parameters and evaluating results.
    3. Document your development process and findings.
  • Discussion Questions:
    • What challenges might you face while training a generative AI model?
    • How can you improve the performance of your model?
  • Ways to Expand Learning:
    • Participate in AI development workshops.
    • Explore additional resources on model optimization.

Module 5: Evaluating Generative AI Solutions

Lesson Plan:

  • Learning Objectives: Evaluate the effectiveness and impact of generative AI solutions.
  • Real World Example: Assessing the performance of an AI-generated marketing campaign.
  • Activities:
    1. Use evaluation metrics to assess your AI model’s performance.
    2. Collect feedback from test users and analyze results.
    3. Prepare a report summarizing your findings and recommendations.
  • Discussion Questions:
    • What metrics are most useful for evaluating generative AI solutions?
    • How can you incorporate user feedback into improving your project?
  • Ways to Expand Learning:
    • Study advanced evaluation techniques.
    • Network with professionals who specialize in AI evaluation.

Module 6: Presenting Your Generative AI Project

Lesson Plan:

  • Learning Objectives: Develop and deliver a presentation of your generative AI project.
  • Real World Example: Creating a presentation for a pitch to potential investors.
  • Activities:
    1. Design a presentation highlighting your project’s objectives, process, and results.
    2. Practice delivering your presentation to peers for feedback.
    3. Revise your presentation based on feedback and prepare for the final presentation.
  • Discussion Questions:
    • What are the key elements of an effective project presentation?
    • How can you effectively communicate the value of your AI solution?
  • Ways to Expand Learning:
    • Attend presentations or webinars on AI innovation.
    • Join a public speaking group to improve presentation skills.

 

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What Will You Learn?

  • You will learn to design, develop, and present generative AI solutions for real-world applications

Student Ratings & Reviews

5.0
Total 2 Ratings
5
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1
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RK
2 months ago
The course exceeded my expectations. The blend of theory and practical exercises made learning engaging and effective. The project work was especially insightful.
AK
2 months ago
This course provided a clear and practical introduction to generative AI. The hands-on projects were particularly useful for understanding real-world applications.