Generative AI Essentials - Practical Use Cases

Explore generative adversarial networks (gan) and how the generator and discriminator duel to create realistic data, enabling applications in images, music, text, and medical imaging.

Variational autoencoders encode inputs into a probabilistic latent space and decode samples to reconstruct or generate new data, offering structured compression, interpretability, and controlled generation.

Foundation models are multimodal AI engines trained on massive, diverse data, including text and images, using transformers like GPT-3, DALL-E, and CLIP to enable image recognition and speech processing.

Learn how large language models, a text-to-text foundation technology driven by transformers, enable translation, summarization, and meaningful coding help, while addressing bias and misinformation risks.

Learn how retrieval augmented generation (rag) enhances large language models by retrieving relevant knowledge and augmenting prompts. This technique boosts accuracy, creativity, and domain-specific performance.

Explore popular generative ai tools—ChatGPT, Google Gemini, and Microsoft Copilot—and learn how to access, prompt, and explore their capabilities in a practical workshop.

Explore prompt engineering to craft precise prompts for generative AI, learn its structure and best practices, and see how clear instructions boost model performance, efficiency, and creativity.

Explore the anatomy of prompts, including keywords, instructions, constraints, and format and structure, and apply best practices for clarity, conciseness, context, and evaluation.

Explore prompt anatomy with ChatGPT by examining keywords, instructions, constraints, and formatting, then apply these components to tasks like summarization, DevOps principles, and email writing.

Explore zero-shot and few-shot prompting to guide language models without or with minimal examples, then master chain-of-thought prompting and knowledge injection to improve accuracy and transparency.

Explore practical prompt engineering with ChatGPT, learning zero-shot and few-shot contexts to guide outputs. Discover real-world use cases of summarization, code generation, travel planning, and creative writing powered by GPT.

Explore practical use cases of generative AI, from crafting emails and summarizing content to creating blogs, videos, presentations, data analyses, and websites, while prioritizing data privacy and security.

Explore practical techniques for using generative AI to craft professional emails in business contexts, mastering clear communication, tone, and timely responses for negotiations, client interactions, and internal communications.

Demonstrate how to summarize long emails and proposals for managers using ChatGPT, extracting project overview, goals, budget, deadlines, and next steps for quick understanding.

Explore how generative AI powers PDF reading as a conversation with Ask Your PDF, enabling quick summaries and interactive questions to extract key points for informed decisions.

Explore generative AI power tools for efficient content creation across blogs, YouTube videos, and shorts, using Gravity Right to generate blog outlines, scripts, and reels.

Explore a hands-on demo of text to image generation with hotpot AI for social visuals. Use prompts, styles, and stock photos to create realistic images with a commercial use license.

Transform written content into engaging videos with generative AI, creating short videos from prompts for YouTube Shorts and other social platforms.

Create visually stunning presentations in seconds with generative AI and tools like Visme. Learn to use prompts, templates, and AI designer features while balancing human input.

Leverage generative ai to design your brand logo by entering your business name, industry, and preferences, and customize templates to establish a polished brand identity.

Utilize generative AI to automatically record, transcribe, and summarize meetings, then share concise insights and action items with your team using tools like Mijikai, Dot AI, and Microsoft Teams transcription.

See how ChatGPT speeds IT development by generating Python code, converting to Java, testing, and hosting a port 80 site with one course.

See how Data Squirrel uses generative AI to clean and analyze data, producing AI-driven charts of revenue by product category over time while noting data security considerations.

Demonstrates building a complete website from scratch without code, using Gen AI tools like ChatGPT and prompt engineering to generate HTML, CSS, and Bootstrap.

Learn how to deploy a static website to an AWS ubuntu server using ChatGPT to generate deployment steps, configure nginx, transfer files, and enable HTTPS for global access.

Explore Google Vertex AI Studio's generative AI capabilities, including prompt management, model tuning, grounding, and code generation, with hands-on demos of image, audio, and text outputs.

Explore ai risks, including fake content, misinformation in politics, fraud in finance, and privacy and security concerns. Examine bias amplification, ai decision making, accountability, and copyright issues for responsible use.

Explore fairness and equity, transparency, privacy and data protection, and accountability as guiding principles for the ethical and responsible use of generative AI, building trust and safeguarding rights.

Engage diverse users and scenarios to gather feedback, plan ahead, and select suitable metrics; ensure unbiased training data, test across conditions, monitor post-deployment, and address ai risks.

Conceive and build a complete generative AI application using AWS Bedrock and Flask, guided by Python skills, prompt engineering, hands-on workshop, and ethical considerations.

Discover AWS Bedrock, a unified API for foundation models, with fine-tuning on your data to build secure chatbots and agents. Explore tokens, embeddings, and secure experimentation in the playground.

Explore Amazon Bedrock in this demo, including foundation models like Titan for chat, text, and image, with hands-on playgrounds, model access, and Bedrock API integration.

Capstone project using AWS Bedrock to build a Flask web app with text-to-text and text-to-image generation, powered by Anthropic LOD v2 and Stable Diffusion X1 v1 via Bedrock.

Demonstrate a capstone chatbot built on AWS Bedrock by configuring IAM, CLI, and a Flask app implementing Bedrock text-to-text and text-to-image models.