
Master tokenization, context windows, and embeddings, and learn how foundational models, fine-tuning, validation data, and knowledge bases drive ai applications like ChatGPT and Bedrock agents.
Build an open source chat user interface using Hugging Face models, connect to the llama server for a retrieval augmented generative model, and deploy with MongoDB and SvelteKit.
Explore generative AI fundamentals by examining labeled and unlabeled data, supervised and unsupervised learning, and key terms like GPT, GAN, and Amazon bedrock.
Explore supervised and unsupervised learning concepts, including regression for numeric predictions, image classification, and clustering. Learn dimensionality reduction, semi-supervised learning, and reinforcement learning with human feedback.
Explore party rock, an Amazon Gen I app builder that lets you sign in with Google and generate AI-powered movie reviews and cooking recipes from user prompts.
Create a website chatbot with Dialogflow on Google Cloud, train intents with natural phrases, set parameters like GHC 2024, and embed the agent for online testing.
In Gen AI Fundamentals, explore core AI techniques from supervised and unsupervised learning to reinforcement learning with human feedback, and apply them by building a chatbot demo for your website.
In this course, one can learn the necessity of Generative Artificial Intelligence (Gen AI). Why is this domain gaining prominence? What are the advantages of using Generative AI?
Generative AI saves time in performing repetitive creative tasks like generating a different image for every person crossing the bridge at a scenic location. When you go to Disneyland, there is a picture of the roller coaster with the highest water splash point; everybody wants to picture themselves there. Generative AI has a lot of entertainment potential. In movies, films when un-imaginable tasks and scenes need to be created. Generative AI can come to the rescue of people whose imagination skills are lower than usual.
In terms of usefulness, Generative AI can create "job descriptions" with just a few lines about the job that the company is advertising. It can respond to commonly found illness symptoms and alleviate the necessity of a doctor for minor injuries, and illnesses.
The only problem is how you determine which images are authentically taken and which ones are autogenerated. There is a fine line of honesty embedded in the use of Generative AI, ethics play a huge role here. One has to find out whose essay in class was self-written and whose was generated through AI.
Several areas are still debatable and not everybody has agreed on the best form of use for Generative AI. But it does provide a lot of entertainment and imagination.