Vanguard

Master Generative AI for engineers: prompt engineering, RAG, fine-tuning, Agentic AI and more. Build cutting-edge AI apps

Ritesh Vajariya

Global Head of Generative AI | AI Strategist | Educator

AI for Engineers

OpenAI

Hugging Face

Amazon Web Services

Anthropic

Meta

In this transformative course, you'll journey from being an AI novice to becoming a confident and skilled Generative AI Engineer. You'll gain a deep understanding of the fundamental concepts behind Large Language Models (LLMs) and their applications in solving real-world engineering challenges. Through hands-on projects and expert guidance, you'll master the art of prompt engineering, enabling you to effectively communicate with and guide LLMs to achieve desired outcomes. You'll explore cutting-edge techniques like Retrieval Augmented Generation (RAG) and fine-tuning, empowering you to build sophisticated AI systems that can process and generate human-like text. As you progress through the course, you'll develop the skills to create agentic systems that can autonomously perform complex tasks and make intelligent decisions. You'll also learn best practices for deploying and monitoring LLM applications in production environments, ensuring scalability and reliability. By the end of this course, you'll have a robust portfolio of Generative AI projects showcasing your ability to leverage LLMs for various engineering applications. You'll be equipped with the knowledge and practical experience needed to drive innovation in your organization and make a significant impact in the field of AI engineering. Some of the tools we will use during the course are: OpenAI chatGPT, Amazon SageMaker, Amazon Bedrock, Anthropic's Claude, LangChain, LlamaIndex, HuggingFace Whether you're a software engineer looking to expand your skill set, a data scientist seeking to harness the power of Generative AI, or a domain expert aiming to incorporate AI into your projects, this course will provide you with the tools and confidence to succeed. Join us on this transformative journey and unlock the limitless potential of Generative AI in engineering. Schedule at-a-glance: ⏰ Time:&nbsp;10:30 am - 12:00pm EST (New York time) P.S. Education should be accessible to everyone. If money is a barrier for you, please email (me@RiteshAI.com), and I will help by providing a discount. If you are from a developing country (e.g. India, Brazil), I will work with you to consider an appropriate discount. *disclaimer: credits are subject to change and you may not get full credit what vendor offers.

From AI Novice to Generative AI Engineer

Software Engineers and Developers:Expand your skills, build intelligent apps, automate tasks, and stay competitive in AI-driven development

Data Scientists and AI Enthusiasts:Explore Generative AI, leverage LLMs for insights, push boundaries, and solve real-world problems

Domain Experts and Researchers:Incorporate AI into your projects, automate tasks, gain insights, and collaborate with AI experts.

Who is this course for

What you’ll get out of this course

<ul><li>Learn to effectively communicate with and guide LLMs through optimized prompts.</li><li>Unlock the full potential of LLMs and achieve desired outcomes in your AI projects.</li></ul>

Mastering Prompt Engineering

<ul><li>Discover how RAG enhances LLMs by integrating external knowledge sources.</li><li>Build powerful question-answering systems and knowledge-intensive applications.</li></ul>

Implementing Retrieval Augmented Generation (RAG)

<ul><li>Adapt pre-trained LLMs to your specific domain or task requirements.</li><li>Improve the performance and accuracy of your AI models through fine-tuning techniques.</li></ul>

Fine-Tuning LLMs for Domain-Specific Tasks

<ul><li>Create autonomous AI agents that can perform complex tasks and make intelligent decisions.</li><li>Explore the concepts of goal-oriented behavior and rational decision-making in AI systems.</li></ul>

Developing Agentic AI Systems

<ul><li>Learn best practices for deploying LLM applications in production environments.</li></ul>

Deploying LLM Applications

Provide a brief description for each module as a way to sell the value of what students will be learning throughout the course.

First Module

Second Module

Third Module

Course syllabus

What people are saying

Meet your instructor

Saturday & Sunday

Before each weekend, there will be a pre-work for students to be ready to understand the concepts - either in form of pre-recorded video or pre-reading of articles.

Pre-work

Use 1 hour weekly to prepare your project which you can demonstrate to your peers, bosses and the world.

Capstone project

Course schedule

Learning about AI for your real project is more important than theory of it.

Go beyond the basics

I live with the content I am presenting everyday. Real world experience is coming from my own work at my current job - I am not an instructor or consultant.

Real world experience

Leadership is less lonely with a supportive community of peers.&nbsp; You will also join a peer community after the course for life long journey.

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