Generative AI for All

This course offers a comprehensive introduction to the evolution of AI, from its inception to the modern advancements we see today. Learners will explore core concepts, key milestones, and the different branches of AI, including machine learning and deep learning, emphasizing their applications and differences. Additionally, the course will delve into the distinctions between various forms of AI, providing a foundational understanding suitable for beginners.

• Key terminologies and core concepts in AI, machine learning, and deep learning.
• The historical journey of AI: From inception through the AI winters to the modern AI era
• An exploration of various machine learning techniques: Supervised, unsupervised, and reinforcement learning
  
• Understanding deep learning's foundational structures and its types, including ANN, CNN, RNN, GAN, and autoencoders
  
• Dffierences between Discriminative vs. Generative AI and Narrow vs. General AI (AGI)

This course is available to learners upon enrollment.

• Understanding LLMs Key prompt templates
  
• Zero-shot, one-shot, few-shot Chain-of-thought
  
• Checklist to craft effective prompts
  
• Workflow for effective prompt engineering
  

• Executing classification/labeling tasks with few-shot and chain-of-thought prompting
  
• Evaluating outputs, synthesis, and summarization with chain-of-thought prompting
  
• LLM as a judge for the evaluation of LLM outputs
  

• Limitations of LLMs (knowledge cutoffs, defining RAG)
• Key components of an RAG workflow (Data store, retriever, generator)
  
• Best practices to organize knowledge sources for RAG
  
• Performance metrics to evaluate RAG
  

In this project, you'll use Generative AI to analyze customer feedback in the retail industry. Your goal is to accurately identify which product or service the feedback pertains to and generate meaningful insights that can help improve the overall customer experience. This process will enable businesses to better understand customer needs and preferences, leading to more targeted enhancements and customer satisfaction.

Tools and Concepts: Generative AI, Customer Feedback Analysis, Insights Generation, Sentiment Understanding

This course covers how to use Generative AI safely and responsibly. You'll learn about the key principles of fairness, accountability, transparency, and privacy in AI. You will explore how to identify and assess security risks using a simple framework called the CIA triad and understand how AI systems handle data. Additionally, the course covers practical ways to manage and filter AI-generated content, ensuring you can use AI effectively and securely in your workplace. 

• Tenets of Responsible AI (fairness, accountability, transparency, privacy)
  
• Assessing GenAI security risks using the CIA triad
  
• Understanding how LLM providers process data
  
• Enterprise best practices on content filtering and risk mitigation

This course introduces you to Multimodal Generative AI, a technology that combines different types of media, such as text, images, music, and video, to create unique and rich outputs. You'll learn to use tools like DALL-E and Midjourney to transform text into stunning images and art. Additionally, the course covers how AI can generate music and videos, showcasing its creative potential across multiple media platforms.

• Creating images and art (using DALL-E, Midjourney)
  
• Application of Multimodal GenAI for music and video generation