H2O Generative AI Starter Track

🚀 Ready to unlock the power of Generative AI? Join Andreea Turcu in the H2O Generative AI Starter Track by H2O.ai University and discover how AI can transform the way you work with data. 💡 What you’ll learn: ✨ The fundamentals of Generative AI & LLMs 📝 How to craft prompts for accurate AI responses ⚡ Real-world applications with h2oGPTe 🔍 Boosting results with Retrieval-Augmented Generation (RAG) This isn’t just a course—it’s your first step to mastering AI with our state-of-the-art H2O.ai tools. Are you ready to explore new possibilities? Let’s get started! 🚀 #GenerativeAI #H2Oai #AITraining #h2oGPTe #LLM #RAG #AICertification #TechInnovation

Welcome to the H2O Generative AI Starter Track! 🚀 In this introductory course, you’ll dive into the fundamentals of Generative AI and explore its real-world applications. Developed by our expert customer data science teams and H2O.ai University, this training is part of our onboarding and certification programs designed to equip you with practical AI skills. What You’ll Learn: • ✅ Core Concepts of Generative AI: Understand the basics of AI/ML and how they power generative models. • 📊 Application Across Data Types: Learn how to apply Generative AI to documents, images, and audio using tools like h2oGPTe. • ⚙️ Advanced Techniques: Discover how to configure Retrieval-Augmented Generation (RAG) and create dynamic outputs with prompt templates. Key Takeaways: By the end of this course, you’ll: • Gain a clear grasp of Generative AI principles. • Understand the role of Large Language Models (LLMs) in driving innovation. • Be able to craft effective prompts for more accurate AI interactions. Get ready to unlock new possibilities with Generative AI and drive transformative impact in your work. Let’s get started! 💡 #GenerativeAI #H2Oai #AITraining #MachineLearning #h2oGPTe #LLM #RAG #AIOnboarding #TechInnovation

Before diving into h2oGPTe, it’s crucial to grasp the key concepts behind Generative AI and how it’s reshaping industries. 💡 The 3 Paradigms of AI: 1️⃣ Machine Learning: Works with structured data for predictions (e.g., predicting health risks). 2️⃣ Deep Learning: Handles multimedia data like images & audio (e.g., detecting diseases from X-rays). 3️⃣ Generative AI: Goes beyond analysis to create new content—think interactive chatbots & dynamic solutions. 🤖 Generative AI & Large Language Models (LLMs): • Generative AI creates text, images, & videos from patterns in data. • LLMs like Danube3-4b excel at generating contextually rich, coherent text for real-world applications. 📊 Choosing the Right Model: • Compare models based on accuracy vs. cost using RAG benchmarks. • H2O’s Danube3-4b performs competitively among industry leaders. 🌍 Where GenAI Makes an Impact: 🎨 Visual Content: Image enhancement, video prediction, 3D models 🎵 Audio Generation: Music composition, TTS, STS 📝 Text Generation: Chatbots, creative writing, translation 💻 Code Generation: Bug fixing, code compilation, new code creation Generative AI is transforming how we create, communicate, and solve problems. Ready to explore its full potential with H2O.ai? Let’s dive in! 🚀 #GenerativeAI #H2Oai #h2oGPTe #MachineLearning #LLM #AIInnovation #TechTransformation #AIAutomation #RAG

In this video, we’ll explore one of the most critical elements of Generative AI—the prompt. Learn how the quality of your prompt directly impacts the relevance and accuracy of AI-generated responses. What You’ll Learn: • What a prompt is and why it’s essential for Generative AI • The importance of prompt engineering to get the best results • Key techniques like Role Play Prompts, Zero Shot Prompting, and Prompt Chaining By the end, you’ll understand how to craft prompts that unlock the full potential of Generative AI for any task. #GenerativeAI #H2Oai #PromptEngineering #LLM #h2oGPTe #AITraining #TechInnovation

In this video, we dive into Retrieval-Augmented Generation (RAG)—a powerful framework that combines data retrieval with AI-generated responses to deliver accurate, context-rich answers. What You’ll Learn: • 📥 The two key components of RAG: 1️⃣ Retriever - Finds relevant data from databases 2️⃣ Generator - Uses LLMs to create coherent, data-backed responses • ⚡ How RAG processes data using embedding models & vector databases • 💼 Real-world applications in customer support, financial analysis, and knowledge management Discover how RAG bridges the gap between data precision and AI creativity, delivering the best of both worlds. #GenerativeAI #RAG #H2Oai #LLM #AIInnovation #DataRetrieval #AITraining #h2oGPTe

In this series, we’ve explored the core concepts of Generative AI and how they’re reshaping industries and workflows. What We’ve Covered So Far: • 🤖 AI Paradigms: Understanding Machine Learning, Deep Learning, and how Generative AI stands out by creating new content. • 💡 Large Language Models (LLMs): The foundation of GenAI, focusing on generating context-aware, accurate text while balancing performance and cost. • 🌍 Real-World Applications: From AI-enhanced visuals to automating communication and creating natural audio experiences. • ✍️ Prompt Engineering: Techniques like role-playing, zero-shot prompting, and prompt chaining to improve AI outputs. • 🔍 Retrieval-Augmented Generation (RAG): Merging data retrieval with AI generation for precise, context-driven responses. With these fundamentals, you’re now ready to dive deeper into applying Generative AI to your data using H2O Enterprise GPTe. 🚀 #GenerativeAI #H2Oai #LLM #RAG #PromptEngineering #h2oGPTe #AIInnovation #AIApplications #TechSeries

In this part of the series, you’ll learn how to harness the power of h2oGPTe, our advanced Generative AI platform, to transform your data into actionable insights. What You’ll Explore: • 💬 Prompting: Start with intuitive, conversational interactions to get familiar with the platform. • 📥 Data Ingestion: Build personalized data collections for precise, relevant information retrieval. • ⚙️ Configuration: Customize settings like selecting LLMs, fine-tuning Temperature, and tailoring outputs to your needs. • 🔍 RAG (Retrieve and Generate): Combine retrieval with AI generation for contextually accurate responses. • 🔗 API Access: Learn how to integrate h2oGPTe into applications and workflows programmatically. By the end of this series, you’ll have the skills to unlock the full potential of h2oGPTe and apply Generative AI effectively to your data. #GenerativeAI #H2Oai #h2oGPTe #DataInsights #RAG #LLM #AITraining #TechInnovation #AIIntegration

In the upcoming videos, we’ll dive into h2oGPTe, a cutting-edge Generative AI platform powered by Retrieval-Augmented Generation (RAG). Learn how to analyze complex documents and generate precise, context-aware responses tailored to your needs. What You’ll Learn: 1️⃣ Prompting: Start with intuitive chats using your preferred LLM. 2️⃣ Data Ingestion: Build data collections for smarter information retrieval. 3️⃣ Configuration: Customize LLMs, tweak parameters, and adjust settings. 4️⃣ RAG (Retrieve & Generate): Combine data retrieval with AI generation for accurate results. 5️⃣ API Access: Integrate h2oGPTe into apps and workflows programmatically. Real-World Use Cases: • Drafting reports from uploaded articles • Generating speeches with AI-assisted outlines • Building self-service chatbots for HR & procurement queries By the end of this series, you’ll know how to make the most of h2oGPTe for your unique use cases. Let’s get started! 🚀 #GenerativeAI #H2Oai #h2oGPTe #RAG #AITraining #LLM #TechInnovation #APIAccess

In this video, discover how h2oGPTe can help you save time and enhance productivity with real-world applications. Use Cases You’ll Explore: • 📝 Report Generation: Quickly turn articles into structured drafts. • 🎤 Speech Drafting: Generate detailed drafts, so you can focus on fine-tuning. • 💬 Self-Service Chatbots: Automate HR & procurement queries for fast, consistent responses. Learn how to leverage h2oGPTe to make your work more efficient and effective. 🚀 #GenerativeAI #H2Oai #h2oGPTe #AIProductivity #TechInnovation #Chatbots #AIApplications

Ready to apply what you’ve learned? Explore Enterprise h2oGPTe, our end-to-end Generative AI platform designed for secure, scalable deployments—whether on-premises, in air-gapped environments, or in the cloud. Try It for Free: 👉 h2ogpte.genai.h2o.ai Sign in easily with your Google or GitHub account via id.public.h2o.ai. What You Can Do with Enterprise h2oGPTe: • 🔗 Connect Any LLM/Embedding Model: Scalable with Kubernetes, plus guardrails, cost controls, and custom options. • 🛠️ Customize & Deploy Open-Source Models: Build your own digital assistants and business GPTs. • 🚀 Develop & Share Trusted AI Apps: Perfect for enterprise and public sector use cases. With features like RAG with citation support, AI safety guardrails, and intelligent model routing, Enterprise h2oGPTe is designed to help you build safe, scalable AI solutions. ⚠️ Disclaimer: The platform is constantly evolving, so features may differ from what’s shown in this video. Refer to the latest documentation for updates. #GenerativeAI #H2Oai #h2oGPTe #EnterpriseAI #LLM #RAG #AIAutomation #TechInnovation #AIApplications

Exploring h2oGPTe: Start with Simple AI Interactions | H2O.ai Generative AI Series 🚀 In this video, we’ll begin demonstrating h2oGPTe’s capabilities through five key steps: Prompting, Collection, Configuration, RAG, and API. These steps will help you extract information efficiently and ensure clear, unbiased answers for your specific use cases. Step 1: Prompting 💬 Start with simple, user-friendly chats: • Ask: “Who are you?” to see how the AI introduces its capabilities. • Ask: “What are the factors of drug desistance?” to get a detailed, data-driven response on a complex topic. This intuitive approach shows how easily you can interact with h2oGPTe—whether for quick info, creative ideas, or complex queries. 🚀 #GenerativeAI #H2Oai #h2oGPTe #Prompting #AIApplications #TechInnovation #LLM

In this video, we’ll show you how to create document collections in h2oGPTe to get more tailored, accurate AI responses—perfect for specific data beyond the AI’s pre-trained knowledge. What You’ll Learn: 📂 Why Collections Matter: Upload your documents to eliminate AI hallucinations and get data-backed answers. 📊 Step-by-Step Setup: • Create a new collection • Upload files like Drug_use_desistance.pdf • Configure settings (embedding model, chunk size, guardrails) 🔍 Efficient Document Management: Organize, search, and manage documents with ease. This process enables Retrieval-Augmented Generation (RAG), ensuring precise, context-aware insights from your data. #GenerativeAI #H2Oai #h2oGPTe #RAG #AIApplications #DocumentManagement #TechInnovation

In this video, we’ll explore the three key tabs in h2oGPTe’s New Chat interface, highlighting how you can customize and optimize AI interactions. What You’ll Learn: 💬 Documents Tab: Upload, manage, and organize files for AI-driven insights. ⚙️ Configuration Tab: Fine-tune your chat by selecting LLMs, enabling vision capabilities, using agents, and optimizing cost-performance balance. ✍️ Prompts Tab: Customize AI behavior, define system prompts, and tailor responses for specific use cases. With h2oGPTe’s flexible, model-agnostic approach, you can seamlessly integrate text, images, retrieval-based responses (RAG), and advanced AI tools to enhance productivity and precision. #GenerativeAI #H2Oai #h2oGPTe #AIConfiguration #PromptEngineering #LLM #RAG #AIOptimization

Now that we’ve explored the core functionalities of h2oGPTe, let’s see it in action with a real use case. Demonstration: 🔍 Query: “What are the factors of drug desistance?” 📂 AI Response: Generates a summary directly from the uploaded document, ensuring accuracy. 📖 References Feature: View the exact pages and sections used for retrieval, confirming the AI’s reliance on trusted data. This process ensures responses remain grounded in real sources, avoiding hallucinations and enhancing contextual relevance. See how h2oGPTe transforms document-based AI retrieval! #GenerativeAI #H2Oai #h2oGPTe #RAG #LLM #AIApplications #ContextualAI #AITrustworthiness

In this final part of the flow, we’ll explore h2oGPTe’s API capabilities, enabling seamless integration into your applications, workflows, or systems. What You’ll Learn: 🔗 What is an API? A bridge that lets software communicate, enabling you to send requests and receive structured responses. 🔑 Generating an API Key: Create and manage API keys for secure, controlled access. 💡 API Key Types: • Global Keys – Full access to all API calls. • Collection-Specific Keys – Limited to specific document collections. ⚙️ Python Integration: Use the API with Python to interact programmatically with h2oGPTe. With API access, you can scale AI-powered solutions, customize interactions, and seamlessly embed h2oGPTe into your own ecosystem. #GenerativeAI #H2Oai #h2oGPTe #AIIntegration #APIAccess #PythonAI #TechInnovation

In this bonus session, we’ll dive into prompt engineering by creating a custom prompt template in h2oGPTe. Learn how to guide AI to generate structured, professional reports by defining system prompts and user inputs effectively. Key Takeaways: 📌 System Prompts vs. User Inputs: • System Prompts set the AI’s role, tone, and formatting rules. • User Inputs dynamically shape responses based on queries. 📌 Step-by-Step: Designing a Report Generation Template 1️⃣ Define the AI’s Role – Assign expertise (e.g., “You are an expert in report writing”). 2️⃣ Structure the Report – Guide sections: Introduction, Analysis, Recommendations, Conclusion. 3️⃣ Enhance Depth & Detail – Ask for data-backed insights. 4️⃣ Set the Right Tone – Ensure a professional and neutral writing style. 5️⃣ Optimize Presentation – Use bullet points, subheadings, and charts for clarity. 📌 Hands-On: Creating & Using a Prompt Template 🛠️ Navigate to the Prompt Catalog → Create a New Prompt Template. 📂 Apply it to a New Chat → Select a document collection, apply the prompt, and generate structured AI-driven reports. See how h2oGPTe enables custom AI workflows tailored to your needs! 🚀 #GenerativeAI #H2Oai #h2oGPTe #PromptEngineering #AIConfiguration #LLM #AIProductivity #StructuredAI

In this bonus segment, Jordan Seow will walk you through how H2O.ai Agents work and what makes them different from other AI systems. You will see how a single AI agent can handle multiple tasks by writing and running code on its own. Using real examples, including a Tesla stock analysis, Jordan shows you how these agents pick the right tools for each job and fix problems automatically when they come up. 🔗 Get to know more about H2O.ai : https://h2o.ai/ 🔗 Learn Generative AI basics and advanced LLMs with our courses : https://h2o.ai/university/

Let’s review everything we’ve covered in our journey with Generative AI and h2oGPTe, ensuring you walk away with a solid understanding of its core functionalities. Key Takeaways: 1️⃣ Prompting (Chat): Learned how to use prompt templates to structure AI interactions for consistent, intelligent responses. 2️⃣ Data Ingestion (Collections): Explored managing documents, images, audio, and websites with support for over 65 file types. 3️⃣ Retrieval-Augmented Generation (RAG): Leveraged uploaded collections to ensure AI-generated responses are contextual and accurate. 4️⃣ Configuration: Customized settings like LLM selection, RAG parameters, and prompt templates for optimal performance. 5️⃣ API: Discovered how to integrate h2oGPTe into applications and workflows for scalable AI solutions. What’s Next? This is just the beginning! Continue your learning journey at h2o.ai/university, where you’ll find in-depth courses on AI technologies and practical applications of h2oGPTe. 🚀 Keep exploring, keep experimenting, and put this knowledge into action. See you soon! #GenerativeAI #H2Oai #h2oGPTe #AITraining #LLM #RAG #AIIntegration #TechLearning