This course is part of the Certified Cloud Applied Generative AI Engineer (GenEng)

1. Microsoft Azure Account https://azure.microsoft.com/en-us/free/ai-services/

Note: If possible register your account with a company email address.

Once you have a subscription id apply for Azure Open AI Service here:

https://azure.microsoft.com/en-us/products/ai-services/openai-service

2. Google Cloud Account https://cloud.google.com/free

From Microsoft to MIT MBA, the AI reeducation boot camp is coming for every worker and executive

The Age of AI has begun

Nvidia says generative AI will be bigger than the internet

Generative AI and Its Economic Impact: What You Need to Know

Must Read: OpenAI DevDay - a pivotal moment for AI

GenEng revolution being led by developers who build deep proficiency in how to best leverage and integrate generative AI technologies into applications

There is a clear separation of roles between those that create and train models (Data Scientists and Engineers) and those who use those models (Developers). This was already on the way, and it much clearer with the GenAI revolution - the future of the GenAI will be determined on how it will be driven to adoption - and it will be driven by how developers adopt it.

GenEng practitioners will need to have many of the same skills of traditional application development, including scalable architecting, integrating enterprise systems, and understanding requirements from the business user. These skills will be augmented with the nuances of building generative AI applications, such as involving the business domain experts in validating aspects of prompt engineering and choosing the right LLM based on price/performance and outcomes

The rise of GenEng: How AI changes the developer role

Watch: The Rise of GenEng

Google launches its largest and ‘most capable’ AI model, Gemini

Meta, IBM and Intel join alliance for open AI development while Google and Microsoft sit out

What Elon Musk has said about Ilya Sutskever, the chief scientist at the center of OpenAI’s leadership upheaval

Who is OpenAI chief scientist Ilya Sutskever, and what does he think about the future of AI and ChatGPT?

Sam Altman to return as CEO of OpenAI

The Year in Tech, 2024: The Insights You Need from Harvard Business Review

The Year in Tech 2024: The Insights You Need about Generative AI and Web 3.0 from Harvard Business Review will help you understand what the latest and most important tech innovations mean for your organization and how you can use them to compete and win in today's turbulent business environment. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.

McKinsey Technology Trends Outlook 2023

Watch Introduction to Generative AI

1. McKinsey: The economic potential of generative AI: The next productivity frontier, McKinsey Digital report, June 2023

2. GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models, Tyna Eloundou, Sam Manning, Pamela Miskin, and Daniel Rock, March 2023 (arXiv:2303.10130)

3. Goldman Sachs: The Potentially Large Effects of Artificial Intelligence on Economic Growth, Joseph Briggs and Devesh Kodnani, March 2023

OpenAI API is a collection of APIs

APIs offer access to various Large Language Models (LLMs)

LLM: Program trained to understand human language

ChatGPT is a web service using the Chat completion API Uses:

1. gpt-3.5-turbo (free tier)
2. gpt-4.0 (paid tier)

1. Chat completion: Given a series of messages, generate a response

2. Function calling: Choose which function to call

3. Image generation: Given a text description generate an image

4. Speech to text: Given an audio file and a prompt generate a transcript

5. Fine tuning: Train a model using input and output examples

The new Assistants API is a stateful evolution of Chat Completions API meant to simplify the creation of assistant-like experiences, and enable developer access to powerful tools like Code Interpreter and Retrieval.

The primitives of the Chat Completions API are Messages, on which you perform a Completion with a Model (gpt-3.5-turbo, gpt-4, etc). It is lightweight and powerful, but inherently stateless, which means you have to manage conversation state, tool definitions, retrieval documents, and code execution manually.

The primitives of the Assistants API are

1. Assistants, which encapsulate a base model, instructions, tools, and (context) documents,
2. Threads, which represent the state of a conversation, and
3. Runs, which power the execution of an Assistant on a Thread, including textual responses and multi-step tool use.

The OPL Stack stands for OpenAI, Pinecone, and Langchain. It's a collection of open-source tools and libraries that make building and deploying LLMs a breeze.

“AI will be the greatest wealth creator in history because artificial intelligence doesn’t care where you were born, whether you have money, whether you have a PhD,” Higgins tells CNBC Make It. “It’s going to destroy barriers that have prevented people from moving up the ladder, and pursuing their dream of economic freedom.”

It’s already valued at almost $100 billion, and expected to contribute $15.7 trillion to the global economy by 2030.

“It’s not that if you don’t jump on it now, you never can,” Higgins says. “It’s that now is the greatest opportunity for you to capitalize on it.”

A.I. will be the biggest wealth creator in history

Generative AI could add up to $4.4 trillion annually to the global economy

Research Report

Silicon Valley Sees a New Kind of Mobile Device Powered by GenAI

Microsoft CEO: AI is "bigger than the PC, bigger than mobile" - but is he right?

Artificial General Intelligence Is Already Here

Inside the race to build an ‘operating system’ for generative AI

Business intelligence in the era of GenAI

The Convergence of AI and Web3: A New Era of Decentralized Intelligence

What is the potential of Generative AI and Web 3.0 when combined?

How Web3 Can Unleash the Power of Generative AI

1. Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT and other LLMs
2. LangChain Crash Course: Build OpenAI LLM powered Apps
3. Build and Learn: AI App Development for Beginners: Unleashing ChatGPT API with LangChain & Streamlit
4. Generative AI in Healthcare - The ChatGPT Revolution
5. Generative AI in Accounting Guide: Explore the possibilities of generative AI in accounting
6. Using Generative AI in Business Whitepaper
7. Generative AI: what accountants need to know in 2023
8. 100 Practical Applications and Use Cases of Generative AI

LangChain Explained in 13 Minutes | QuickStart Tutorial for Beginners

LangChain Crash Course for Beginners

LangChain Crash Course for Beginners Video

LangChain for LLM Application Development

LangChain: Chat with Your Data

A Gentle Intro to Chaining LLMs, Agents, and Utils via LangChain

The LangChain Cookbook - Beginner Guide To 7 Essential Concepts

Greg Kamradt’s LangChain Youtube Playlist

1littlecoder LangChain Youtube Playlist

Pinecone

https://docs.pinecone.io/docs/quickstart

https://python.langchain.com/docs/integrations/vectorstores/pinecone

LangChain - Vercel AI SDK

https://sdk.vercel.ai/docs/guides/providers/langchain

Using Python and Flask in Next.js 13 API

https://github.com/wpcodevo/nextjs-flask-framework

https://vercel.com/templates/python/flask-hello-world

https://vercel.com/docs/functions/serverless-functions/runtimes/python

https://codevoweb.com/how-to-integrate-flask-framework-with-nextjs/#google_vignette

https://github.com/vercel/examples/tree/main/python

https://github.com/orgs/vercel/discussions/2732

https://flask.palletsprojects.com/en/2.3.x/tutorial/

https://flask.palletsprojects.com/en/2.3.x/

Reference Material:

LangChain Official Docs

LangChain AI Handbook

Top 5 Resources to learn LangChain

Official LangChain YouTube channel

Building Custom Q&A Applications Using LangChain and Pinecone Vector Database

End to End LLM Project Using Langchain | NLP Project End to End

Build and Learn: AI App Development for Beginners: Unleashing ChatGPT API with LangChain & Streamlit

Total Questions: 40

Duration: 60 minutes