Getting Started with Generative AI
Adopt generative AI tools to streamline your work and stay competitive in today’s rapidly evolving industry with this online course from PragmaticAI.
Duration
3 weeks
Weekly study
5 hours
100% online
How it works
Unlimited subscription
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Artificial intelligence is the talk of the town. As AI adoption becomes more and more commonplace, big companies are now relying on generative AI tools – and the people who know how to use them – to turn bigger profits.
Stay ahead of the curve and stand out as a tech-savvy professional by joining this online course from PragmaticAI, helping you adapt your practices to align with where AI is heading.
In just three weeks, you’ll not only have learned the basics of generative AI and how to leverage its models, you’ll also be on your way to building robust generative AI systems of your own.
You’ll begin with an introduction to generative AI, exploring what it is, how it started, and it’s evolution into the large language models (LLM) we use today.
In studying the generative AI landscape and systems available, as well as diving into generative AI’s architecture and processes, you’ll grasp how each model works, even major foundation models, like ChatGPT and Hugging Face.
Once you’ve grasped the basics, you’ll advance to interacting directly with generative AI models. You’ll learn the essentials of prompt engineering, including how to craft effective prompts and use techniques like few-shot prompting, chaining prompts, and task breakdowns.
By the end of the week, you’ll be able to apply advanced skills to overcome context limitations.
Finally, you’ll explore different types of generative AI applications, from API-based to multi-model systems.
With newly acquired AI skills, you’ll learn the fundamentals of building AI applications, like Retrieval Augmented Generation (RAG), and testing it it on cloud tools, like Azure.
These lessons will cover the foundational knowledge about Generative AI like its background history, and how large language models work in addition to how they can be created.
Find out more about what are LLMs are how do they work, including their benefits and risks as well as challenges of working with LLMs.
An overview of the platforms and technologies leading the AI landscape like OpenAI, HuggingFace and cloud-based solutions
We will cover employing prompting best practices and providing relevant context to generate outputs from AI systems. You will see how to use different techniques and examples to overcome context limitations
Building on the basics of prompting, now we will go through some advanced techniques like using feedback or building on previous context
By understanding the limits of context and applying advanced techniques, you will have the capabilities of enhancing the responses from AI systems
Find more about the common types of Gen AI applications and how they can be used to tackle different problems
This enhancing technique in Generative AI applications will provide you grounding and enhancement when designing robust AI applications
Apply your LLM knowledge when deploying an LLM to the cloud
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