Generative AI and LLMs for Dummies
David Baum, 2024

Microsoft Generative AI Training Course ✍️

https://github.com/microsoft/generative-ai-for-beginners

Inside Generative AI
Rick Spair, 2024

🗂 A collection of the good Gen AI free courses


🔹 Generative artificial intelligence

1️⃣ Generative AI for Beginners course : building generative artificial intelligence apps.

2️⃣ Generative AI Fundamentals course : getting to know the basic principles of generative artificial intelligence.

3️⃣ Intro to Gen AI course : from learning large language models to understanding the principles of responsible artificial intelligence.

4️⃣ Generative AI with LLMs course : Learn business applications of artificial intelligence with AWS experts in a practical way.

5️⃣ Generative AI for Everyone course : This course tells you what generative artificial intelligence is, how it works, and what uses and limitations it has.

📢 5-Day Generative AI Intensive Course with #Google is now available as a self-paced Learn Guide!

Access whitepapers, podcasts, code labs, & recorded livestreams. Additionally, there is a bonus assignment for you!
https://www.kaggle.com/learn-guide/5-day-genai

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10 GitHub Repositories to Master LLM

✅ brexhq/prompt-engineering
Tips and examples to improve your prompt engineering skills.
🔗 GitHub

✅ mlabonne/llm-course
A full course with tutorials and hands-on LLM projects.
🔗 GitHub

✅ Hannibal046/Awesome-LLM
Curated list of LLM papers, tools, and tutorials.
🔗 GitHub

✅ WooooDyy/LLM-Agent-Paper-List
Research papers focused on LLM-based agents.
🔗 GitHub

✅ avvorstenbosch/Masterclass-LLMs-for-Data-Science
Guide to using LLMs in data workflows, with exercises.
🔗 GitHub

✅ Shubhamsaboo/awesome-llm-apps
Real-world LLM apps using OpenAI, Gemini, and more.
🔗 GitHub

✅ BradyFU/Awesome-Multimodal-LLM
Resources on LLMs that handle text, images, and audio.
🔗 GitHub

✅ HandsOnLLM/Hands-On-LLM
Code examples from the O'Reilly hands-on LLM book.
🔗 GitHub

✅ SylphAI-Inc/LLM-engineer-handbook
Handbook for building and deploying LLMs.
🔗 GitHub

✅ rasbt/LLMs-from-scratch
Build a GPT-style model in PyTorch from scratch.
🔗 GitHub

Important AI Terms Explained

COMMON TERMINOLOGIES IN PYTHON - PART 1

Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?

In this series, we would be looking at the common Terminologies in python.

It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:

IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python noscripts.

Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately

System Python - This is the version of python that comes with your operating system

Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions

REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)

Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.

Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function

Return Value - this is the value that a function returns to the calling noscript or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.

Note: A return value can be any of these variable types: handle, integer, object, or string

Script - This is a file where you store your python code in a text file and execute all of the code with a single command

Script files - this is a file containing a group of python noscripts

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