🚨 BREAKING: Microsoft just dropped an 18-episode series called "Generative AI for Beginners".
Ideal for beginners, developers, and AI enthusiasts looking to build a solid foundation.
Here’s a breakdown (Save this👇):🧵
Episode 1: Introduction to Generative AI and LLMs
– Carlotta Castelluccio introduces Generative AI and large language models, explaining their inner workings and how they are revolutionizing industries (with a focus on education)
– Carlotta Castelluccio and Pablo Lopes explore various types of large language models, their use cases across industries, and how businesses can harness their potential
– Explains why responsible AI is crucial for generative applications, covering how to ensure AI outputs are fair and non-harmful, and steps to improve the responsible use of AI
– Nitya Narasimhan walks through the fundamentals of prompt engineering, teaching how to craft effective prompts and iterate on them to improve generative AI results
– Chris Noring delves into advanced prompt-engineering techniques to optimize prompts and improve AI response quality, demonstrating these methods with real-world examples
– Covers the core concepts of text generation using OpenAI and shows how to build a text-generation application step by step, adjusting parameters like prompt, temperature, and tokens for desired output
– Jasmine Greenaway demonstrates how to efficiently build and integrate AI-powered chat applications into existing systems, including customization, fine-tuning, and monitoring strategies
Episode 8: Building Search Apps (Vector Databases)
– Dave Glover shows how to build semantic search apps using vector embeddings to index and query text, retrieving relevant video segments from an education startup's library.
– Chris Noring and Pablo Lopes explain how to generate images from text descriptions using models like DALL-E and Midjourney, and walk through building an image-generation app step by step
– Someleze Diko showcases Microsoft Power Platform's low-code tools with generative AI, featuring Copilot and AI Builder, to build AI-powered apps and workflows with little coding.
Episode 11: Integrating External Applications with Function Calling
– Korey Stegared-Pace discusses function calling in LLMs, explains implementing an OpenAI function call, and shows integration into applications to enhance AI capabilities.
– Bethany Jepchumba emphasizes designing AI app experiences by prioritizing user trust and transparency, understanding user needs, and fostering collaboration and feedback.
Episode 14: The Generative AI Application Lifecycle
– Pablo Lopes examines the AI lifecycle, emphasizing the shift from ML Ops to LLM Ops with tools for developing, deploying, monitoring, and improving AI solutions.
– Explores open-source large language models. Korey Stegared-Pace contrasts these with proprietary versions and guides on using and fine-tuning open models on platforms on Hugging Face or Azure AI Studio.
– Nitya Narasimhan explains fine-tuning pre-trained language models to enhance task-specific performance. This final episode covers what fine-tuning is, when it’s useful, how to do it, and its limitations.
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