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This book gives practical, hands-on guidance for using AI to learn faster, build software, and grow a tech career. It’s for aspiring AI professionals, developers, and curious learners who want step-by-step workflows: from prompts and specs to safe implementation, testing, and agent design. Read it to gain concrete skills, a career roadmap, and the judgment needed to apply AI responsibly in real projects.

Human + Machine: Practical Skills to Build, Ship, and Grow with AI

This guide is my curated breakdown of the skills humans still have the advantage in, as AI gets more capable.

HUMAN over AI Advantages

A curated guide to the most important open-source repositories AI engineers use to make large language models faster, cheaper, and easier to deploy. This PDF breaks down what each tool does, why it matters, and when to use it, with direct links to the GitHub repos so you can explore and build right away.

GitHub Repos for AI Engineers

Get hands-on with AI! This guide walks you through intermediate-level projects in machine learning, NLP, and deep learning, complete with tools, libraries, and resources to help you build real portfolio-ready skills.

ML PROJECTS GUIDE (INTERMEDIATE LEVEL)

This PDF breaks down the AI Engineer path in a simple, practical way. It’s designed for beginners who want clarity on what to learn, what tools matter, and where to start.

AI ENGINEER ROADMAP (START FROM ZERO)

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Before diving into developing AI-based APIs, it’s crucial to ensure that your development environment, tools, cloud accounts, and foundational knowledge are all properly set up. Foundations First is a project-based, hands-on course designed specifically for Python developers who want to build and deploy powerful APIs that integrate AI and cloud technologies.

This course eliminates the guesswork and fragmented setup process by guiding you through every essential step—setting up your AWS and OpenAI accounts, initializing and connecting your Django backend with a PostgreSQL database, installing tools like Docker and Git, managing repositories on GitHub, and understanding the basics of using AWS services such as Lambda, S3, RDS, ECR, and API Gateway.

By the end of this course, you’ll have a fully configured development environment and the practical knowledge needed to start building MVP-level AI-based API projects confidently. You won’t just install tools—you’ll understand them. 

This is the deep setup course that ensures you don’t skip foundational steps.

🎯 Course Goals
1. To simplify the setup process for building real-world AI-based APIs.
2. To help learners confidently install, connect, and configure essential tools and services.
3. To ensure that learners are 100% ready to begin building and deploying scalable, cloud-based APIs.

✅ Learning Outcomes
By the end of this course, learners will:
1. Set up a local development environment using Python, Django, and PostgreSQL.
2. Create and manage GitHub repositories using Git and branches effectively.
3. Create and configure IAM users and permissions on AWS.
4. Understand and test core AWS services (S3, Lambda, API Gateway, RDS, and ECR).
5. Set up OpenAI accounts and obtain API keys for future AI integrations.
6. Use tools like Docker, Postman, and VS Code/PyCharm in their workflow.
7. Build confidence in setting up a secure, production-ready backend environment.

🧱 Module 1: Welcome & Introduction

💻 Module 2: Setting Up Your Local Python Development Environment

🗃️ Module 3: PostgreSQL, SQLite and Django Integration

🌐 Module 4: Git and GitHub Essentials

☁️ Module 5: Setting Up AWS

🔐 Module 6: Connecting to OpenAI

🛠️ Module 7: Tooling for API Development

🚀 Module 8: Final Setup Checklist & Launch Readiness

📚 Bonus Module: Next Steps

Foundations First: Set Up Your Development Environment to Build AI based APIs with Python & Cloud Services

AI-Based API Development Course

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GoogleColab Notebooks

This course is designed for early-career software developers, backend engineers, and AI enthusiasts who want to move beyond tutorials and build complete AI-powered backend systems from scratch. The course avoids theoretical fluff and dives straight into project implementation, helping learners build confidence by delivering working software that solves real-world problems.

🧪 Key Features
- FastAPI backend
- PostgreSQL database
- OpenAI + AWS Rekognition
- AWS: S3, Lambda, EventBridge, ECR
- Dockerized local development
- Secure login with JWT
- API documentation with Swagger

AI-Powered Apps with Python: A Hands-On Guide

🔍 Built for You:
No cloud, no compromise. This local chatbot extracts key info from your content and delivers answers that fit your exact context—ideal for FAQs, internal knowledge, and customer support.

💻 Tech That Works:
FastAPI and Streamlit power the experience, Docker keeps it secure, and RAG ensures your chatbot’s answers are truly your own. It’s a flexible, expandable solution for serious content-based conversations!

RAG Chatbot project

RAG Chatbot source code

This beginner-friendly, hands-on notebook walks you through building an AI-powered Tone Changer app using LangChain and OpenAI — in under 40 lines of Python code.

✅ Rewrite messages to sound more formal, casual, or assertive
⚡️ Powered by LangChain PromptTemplates + LangSmith debugging
🎓 Perfect for Python & AI learners — no prior experience needed
📁 Includes clean, editable code and example prompts
📊 Great starter for building your own AI-powered tools

Whether you're a content creator, developer, or just curious about LLM apps, this notebook will help you build your first real-world AI app — fast!

Tone Changer App Notebook (LangChain + OpenAI)

Tone Changer app notebook

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AI_Engineering_Resources_2026_Fafacodes.pdf

quoteGenerator

pictures2pages

FormFix AI GitHub repo

python_data_manipulation_reel.ipynb

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Fafa Modey

Python 🐍 | AI 🤖 | Cloud ☁️

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GoogleColab Notebooks

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