Becoming an AI Engineer with LLM Application Development

Becoming an AI Engineer with LLM Application Development
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 45m | 691 MB
Instructor: Mark Chen

A concise guide for AI engineers to develop and deploy LLM-powered applications

What you'll learn

• Learn the fundamental of LLM and generative AI
  
• Learn the fundamental of API development
  
• Learn the fundamental of Gradio framework
  
• Develop your own AI chatbot in a day
  
• Deploy your solution with Hugging Face Space
  
• Automate your application development and deployment workflow to improve software quality and delivery speed
  

Requirements

• Passion for AI
  
• Computer (MacOS, Linux, or Windows)
  
• Stable Network Connection
  
• Python Installed - Recommended version: 3.9 or 3.10
  
• Visual Studio Code Installed
  
• Hugging Face Pro Subscription
  
• OpenAI API Subscription
  
• GitHub Account (Free or Pro)
  

Description

Becoming an AI Engineer with LLM Application Development

| A concise guide for AI engineers to develop and deploy generative AI applications |

What is generative AI? Why you should be a part of this revolution?

Generative AI is a truly transformative technology that allows us to engineer and deploy various AI applications like chatbots and other automation workflows without costly upfront investments. Therefore, there is an emerging trend that many companies, even if not within the technology domains like finance and health care, are trying to adopt AI applications like ChatGPT. Here is what an AI engineer could do to help these organizations develop and deploy a valuable and cost-effective AI application using various open or closed-source models. If you want to be a part of this revolution, this course is right for you to learn the fundamental concepts and practical skills to become an AI engineer nowadays.

What can I learn from this course?

- Chapter 1 - Introduction to Generative AI

- Chapter 2 - Environment Set-up / Generative AI Platform Tours

- Chapter 3 - Develop your API endpoint for your generative AI applications

- Chapter 4 - Develop and Deploy with your Front-end Interface

- Chapter 5 - Streamline API Delivery with Automated Test and Deployment Pipeline

- Chapter 6 - Course Summary / Final Exam

Who is my instructor?

Mark is an entrepreneur and computer science student at the University of London who lives in Taiwan. He founded Mindify AI, a company aimed at helping software engineers learn new codebases faster with its flagship product, Mindify Chat. Mark is also involved in AI and quantum AI research, working on innovative projects, including utility-scale quantum generative AI models for the Google Quantum Application XPRIZE. In addition to his business ventures, Mark creates Notion templates and Udemy courses, generating side income. Mark's recent achievements include developing algorithms, leading research projects, starting a new company, and gaining traction for Mindify AI. He is dedicated to making his products profitable and advancing his research and business efforts.

Who this course is for:

• Professional software developers who are new to generative AI application development
  
• Computer science students who are interested in generative AI application development
  
• Web developers who is seeking to build an generative AI as a side project
  
• Python developers who is seeking to build an generative AI as a side project
  

More Info