Introduction to Modern AI

What will you learn in Introduction to Modern AI course?

• Define key AI concepts, such as machine learning, models, and generative vs. non-generative AI.
• Explore computer vision techniques: Students will gain practical knowledge of computer vision techniques, such as object detection, similarity search, image segmentation, and optical character recognition.
• Understand machine translation challenges: Students will learn about the challenges of machine translation, particularly concerning word order, context, idiomatic expressions, and the distance between words.
• Use and understand chatbots: Students will gain practical experience in using various chatbots and understand their capabilities and limitations. They will be able to utilize popular chatbots like ChatGPT, Gemini, Claude, and others. They will learn about different chatbot functionalities, including expanding, synthesizing, transforming, evaluating, chatting, and taking actions.
• Apply prompt engineering techniques: Students will learn about effective prompt engineering techniques to improve chatbot performance. They will understand the importance of providing clear instructions, breaking down tasks into sub-tasks, and setting expectations for the chatbot. They will also learn about techniques like few-shot prompting, giving the chatbot a persona, and asking for output in specific formats.
• Recognize chatbot limitations: Students will understand the limitations of chatbots, including issues like hallucinations and memory limitations. They will be able to identify instances where chatbots might provide inaccurate or fabricated information and learn strategies for mitigating these issues.
• Gain awareness of generative AI: Students will learn about generative AI and how it differs from non-generative AI. They will understand the concept of generative AI producing new outputs based on learned patterns, while non-generative AI relies on predefined outputs.
• Understand key vocabulary in AI: Students will gain familiarity with essential vocabulary related to AI, including terms like transformers, foundation models, pre-training, instruction tuning, and GPT.