Category: Computer Programming Tutorials

This comprehensive AI Engineering roadmap will walk you through the essential skills and techniques every aspiring AI Engineer should master by 2025. From fundamental mathematics and key machine learning algorithms to deep learning, AI Engineering best practices, and large language models—you’ll get hands-on AI Engineering experience and invaluable career insights that will set you on the fast track to success in this rapidly evolving field. Course developed by Tatev Aslanyan from @LunarTech_ai Apply to AI Engineering Bootcamp Here: https://www.lunartech.ai/bootcamp/ai-engineering-bootcamp ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Contents ⭐️
(0:00:00) AI Engineering Roadmap Introduction
(0:03:59) What is AI Engineering
(0:05:47) AI Engineering Applications
(0:08:31) Must-Have Skills for an AI Engineer
(0:09:05) Mathematical Foundations
(0:17:38) Statistics Essentials
(0:23:37) Data Science Skills
(0:28:05) Traditional Machine Learning
(0:32:36) Deep Learning Foundations
(0:38:36) Practical Implementation in Python
(0:40:54) Generative AI Fundamentals
(0:46:39) Large Language Models (LLMs)
(0:51:07) Fine-tuning Large Language Models
(0:52:05) Reinforcement Learning with Human Feedback (RLHF)
(0:53:05) Retrieval-Augmented Generation (RAG)
(0:53:28) Evaluating & Optimizing LLMs
(0:54:14) AI Engineering Ethics & Safety
(0:56:44) Additional Resources & Career Paths
(0:57:34) Outro & Final Remarks 🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual — Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Want to deploy your **Flask app** using **AWS Elastic Container Registry (ECR)**? 🚀 In this tutorial, I’ll walk you through the **entire process** of building a Docker image, pushing it to AWS ECR, and running it on your system or an AWS service. By the end of this video, you’ll know how to **PUSH, PULL, and RUN** a **Flask app container** with AWS ECR and manage your containerized applications like a pro! 💻 — ## **🔹 What You’ll Learn in This Video:** ✅ How to **set up AWS ECR** for container image storage ✅ How to **build and tag a Docker image** for a Flask app ✅ How to **push the Docker image** to AWS ECR ✅ How to **pull the image** from AWS ECR ✅ How to **run the container** locally using Docker — ## **🔹 Prerequisites** ✔️ **AWS Account** (Sign up at [aws.amazon.com](https://aws.amazon.com/)) ✔️ **Docker Installed** ([Download Docker](https://www.docker.com/get-started)) ✔️ **AWS CLI Installed & Configured** ([AWS CLI Guide](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html)) ✔️ Basic knowledge of **Flask and Docker** — ## **🔹 Step 1: Create an AWS ECR Repository** 1️⃣ Log in to your **AWS Management Console** 2️⃣ Go to **Elastic Container Registry (ECR)** 3️⃣ Click **Create Repository** 4️⃣ Choose **Private or Public** (Private is recommended) 5️⃣ Copy the **ECR repository URL** — ## **🔹 Step 2: Authenticate Docker with AWS ECR** Before pushing a Docker image, you need to log in to AWS ECR: “`bash
aws ecr get-login-password –region your-region | docker login –username AWS –password-stdin your-account-id.dkr.ecr.your-region.amazonaws.com
“` — ## **🔹 Step 3: Build & Tag Your Flask App Docker Image** First, create a **Dockerfile** for your Flask app: “`dockerfile
# Use official Python image
FROM python:3.9 # Set working directory
WORKDIR /app # Copy application files
COPY . . # Install dependencies
RUN pip install -r requirements.txt # Expose the Flask app port
EXPOSE 5000 # Run the Flask app
CMD ["python", "app.py"]
“` Now, build and tag the Docker image: “`bash
docker build -t flask-app .
docker tag flask-app:latest your-account-id.dkr.ecr.your-region.amazonaws.com/flask-app:latest
“` — ## **🔹 Step 4: Push the Docker Image to AWS ECR** Now, push the tagged image to AWS ECR: “`bash
docker push your-account-id.dkr.ecr.your-region.amazonaws.com/flask-app:latest
“` — ## **🔹 Step 5: Pull and Run the Docker Image from AWS ECR** To **pull** the image from AWS ECR: “`bash
docker pull your-account-id.dkr.ecr.your-region.amazonaws.com/flask-app:latest
“` To **run the Flask app container locally**: “`bash
docker run -p 5000:5000 your-account-id.dkr.ecr.your-region.amazonaws.com/flask-app:latest
“` Your Flask app should now be accessible at: 👉 **http://localhost:5000** — ## **🔹 Step 6: Deploy Your Flask App to AWS Services (Optional)** After pushing your Docker image to AWS ECR, you can use it with: ✔️ **AWS Fargate** (Serverless container hosting) ✔️ **Amazon ECS** (Elastic Container Service) ✔️ **Amazon EKS** (Kubernetes Service) — ## **🔹 FAQs About AWS ECR & Docker** 🔹 **What is AWS ECR?** AWS **Elastic Container Registry (ECR)** is a managed container registry to store, manage, and deploy Docker container images. 🔹 **Why use AWS ECR instead of Docker Hub?** AWS ECR offers **private repositories**, **seamless AWS integration**, and **IAM-based security controls**. 🔹 **Can I automate the push process?** Yes! You can use **GitHub Actions, AWS CodePipeline, or Jenkins** for CI/CD automation. — ## **🔹 Who Is This Tutorial For?** ✅ Developers **deploying Flask apps with Docker** ✅ DevOps engineers working with **AWS ECR & ECS** ✅ Anyone **new to AWS container management** — ## **🔹 More AWS & Docker Tutorials:** 📌 **How to Deploy a Flask App with AWS EC2 & Nginx** → [Watch Now] 📌 **How to Build & Run a Flask Docker Container** → [Watch Now] 📌 **How to Deploy a Django App with AWS Elastic Beanstalk** → [Watch Now] — ## **👍 Like, Share & Subscribe!** If this tutorial helped you, please **LIKE, SHARE, and SUBSCRIBE** for more **AWS, Docker, and DevOps tutorials**! 🚀 💬 Have questions? Drop them in the **comments** below! — ### **🔹 Hashtags:** #AWS #ECR #Docker #Flask #Python #ElasticContainerRegistry #AmazonECS #DevOps #CloudComputing #Containerization #AWSCloud Now, you can push, pull, and run Docker images on AWS ECR like a pro! 🚀🔥

Learn how to build a website with Next.js 15 and Strapi 5. In this course you'll learn to build a fully functional summer camp website from start to finish. Through hands-on practice, you'll discover how to combine the power of Next.js's server components with Strapi's headless CMS capabilities, creating dynamic, content-rich websites that are both developer-friendly and client-manageable. Project Repo Resources: https://github.com/PaulBratslavsky/freecodecamp-surfcamp-final
Strapi Docs: https://strapi.link/getting-started Course from @CodingAfterThirty ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Contents ⭐️
⌨️ (0:00:00) Course introduction and project overview
⌨️ (0:11:37) How to follow this course and local project setup
⌨️ (0:15:59) Getting started with Next.js 15 and Strapi 5
⌨️ (0:22:26) Section 1- Building the home page
⌨️ (1:29:20) Section 2 – Building the experience page
⌨️ (1:41:16) Section 3 – Building top navigation
⌨️ (1:54:21) Section 4 – Building out the footer
⌨️ (2:04:02) Section 5 – Building the blog page
⌨️ (2:17:08) Section 6 – Form submission with server action
⌨️ (2:41:23) Section 6.5 – How to structure our blog data in Strapi
⌨️ (2:58:07) Section 7 – Custom data loading content list component ⌨️ (3:14:41) Section 8 – Implementing search and pagination in Next.js
⌨️ (3:45:48) Section 9 – Building a single blog detail page ⌨️ (4:12:17) Section 10 Building the events page and form
⌨️ (4:55:25) Conclusion
⌨️ (4:57:03) Where to next?
⌨️ (4:58:18) Interview with Niklas on styling and Figma Design
⌨️ (5:22:06) Why use Next.js
⌨️ (5:28:22) Setting up Next.js
⌨️ (5:32:12) Routing
⌨️ (5:36:20) Layout Page
⌨️ (5:41:32) Links and Navigation
⌨️ (5:44:30) Server and Client Components
⌨️ (5:52:25) Data fetching
⌨️ (5:59:34) Dynamic Routing
⌨️ (6:11:44) Not Found Page
⌨️ (6:16:26) Figma for developers 🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual — Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

If you're interested in learning how to write software that runs on a blockchain distributed ledger database, this comprehensive course will teach you everything from scratch using Python and Vyper, even if you're a complete beginner. The course will enable you to:
1. Be able to develop smart contracts in Vyper, the pythonic smart contract blockchain language
2. Script in python (you can have 0 python experience for this course, we teach you python too!!)
3. Interact with smart contracts in Python and Vyper
4. Work with AI tools to speed up your development It also covers:
– Fuzzing
– NFTs
– Algorithmic Trading
– AI
– ERC20s
– DeFi And so much more! Code and resources: https://github.com/Cyfrin/moccasin-full-course-cu Cyfrin Updraft course: https://updraft.cyfrin.io/courses/intro-python-vyper-smart-contract-development ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp Timestamps:
0:00:00 – Blockchain Basics
2:55:04 – Remix Favorite’s List
4:54:18 – Remix Buy Me A Coffee
7:28:35 – AI Prompting 7:36:05 – Python Crash Course
9:56:25 – Web3py Favorites
11:45:23 – Boa Favorites
12:44:32 – Moccasin Favorites
15:03:48 – Moccasin Five More
16:01:17 – Moccasin Buy Me A Coffee
18:23:01 – HTML/JS
https://updraft.cyfrin.io/courses/intermediate-python-vyper-smart-contract-development/mox-html/mox-intro
18:27:45 – Moccasin ERC20 and getting hired
20:35:02 – Moccasin NFTs
22:55:48 – Algorithmic Trading
24:45:58 – Moccasin Stablecoin
27:42:06 – Moccasin Signatures
29:36:15 – Final project, Moccasin Upgrades

Want to build a **REST API** using Flask? 🚀 In this tutorial, we’ll walk you through creating a **Flask RESTful API** with **GET and POST** requests step by step. Flask makes it easy to build lightweight, scalable, and efficient APIs for web and mobile applications. By the end of this tutorial, you'll have a fully functional **Flask API** that can **send and receive JSON data** using HTTP requests. — ## **🔹 What You’ll Learn in This Video:** ✅ Setting up Flask for API Development ✅ Creating a Flask RESTful API with `Flask` and `Flask-RESTful` ✅ Handling **GET & POST Requests** ✅ Sending & Receiving **JSON Data** ✅ Running & Testing the API with **Postman or cURL** — ## **🔹 Prerequisites** Before starting, ensure you have: ✔️ **Python 3.x** installed → [Download Python](https://www.python.org/downloads/) ✔️ **Flask & Flask-RESTful Installed** ✔️ **VS Code or Any Code Editor** — ## **🔹 Step-by-Step Guide** ### **1️⃣ Install Required Packages** Open the terminal and run the following command: “`bash
# Create a project directory
mkdir flask-rest-api && cd flask-rest-api # Create a virtual environment
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate # Install Flask and Flask-RESTful
pip install flask flask-restful
“` — ### **2️⃣ Create a Flask API Project** Create a new file called **`app.py`** and add the following code: “`python
from flask import Flask, request, jsonify
from flask_restful import Resource, Api app = Flask(__name__)
api = Api(app) # Sample in-memory data
data = [] # Define a Resource for GET and POST
class ItemResource(Resource): def get(self): return jsonify({"items": data}) def post(self): new_item = request.get_json() # Get JSON data from request data.append(new_item) return jsonify({"message": "Item added!", "item": new_item}) # Add the resource to the API
api.add_resource(ItemResource, "/items") if __name__ == "__main__": app.run(debug=True)
“` — ### **3️⃣ Run the Flask API Server** Save the file and run: “`bash
python app.py
“` You should see Flask running on **http://127.0.0.1:5000** — ### **4️⃣ Test the API with GET & POST Requests** #### **✅ GET Request (Fetch Items)** Open a browser or Postman and visit: 👉 **http://127.0.0.1:5000/items** It should return: “`json
{"items": []}
“` #### **✅ POST Request (Add an Item)** Use **Postman** or cURL to send a **POST request** with JSON data: “`json
{ "name": "Laptop", "price": 1200
}
“` **Postman Setup:** – Select **POST** – Enter **http://127.0.0.1:5000/items** – Go to **Body** → **raw** → **JSON** – Paste the JSON data and hit **Send** 💡 The API will respond: “`json
{ "message": "Item added!", "item": { "name": "Laptop", "price": 1200 }
}
“` — ### **5️⃣ Fetch Updated Items** Re-run the **GET request** to **http://127.0.0.1:5000/items** Now it should return the updated list: “`json
{ "items": [ { "name": "Laptop", "price": 1200 } ]
}
“` — ## **🔹 Who Is This Tutorial For?** ✅ Web Developers Building APIs ✅ Backend Engineers Working with REST APIs ✅ Anyone Looking to Learn API Development with Flask — ## **🔹 Resources Mentioned in This Video:** 📌 Flask Documentation → [https://flask.palletsprojects.com/](https://flask.palletsprojects.com/) 📌 Flask-RESTful Docs → [https://flask-restful.readthedocs.io/](https://flask-restful.readthedocs.io/) — ## **💡 Pro Tips for API Development** ✔ Use **Postman** to test API endpoints. ✔ Add **error handling** for better responses. ✔ Use a **database (MySQL, PostgreSQL, SQLite)** instead of in-memory storage. ✔ Deploy your API using **Docker, AWS, or GCP**. — ## **👍 Like, Share & Subscribe!** If this tutorial helped you, please **LIKE, SHARE, and SUBSCRIBE** for more **Flask, Python, and Web Development** tutorials! 🚀 💬 Got questions? Drop them in the **comments** below! — ### **🔹 Hashtags:** #Flask #API #RESTAPI #Python #WebDevelopment #Backend #FlaskTutorial #PythonAPI #APIDevelopment #FlaskRestful Start building your Flask REST API today! 🐍🚀

Want to connect **Flask with MySQL** in **Visual Studio Code (VS Code)?** 🔥 In this step-by-step tutorial, we’ll guide you through setting up a Flask web application and integrating it with a MySQL database. This is perfect for **web developers** and **backend engineers** looking to build dynamic, database-driven applications using Flask and MySQL. — ### **🔹 What You’ll Learn in This Video:** ✅ Installing Flask and MySQL in VS Code ✅ Setting Up a Virtual Environment in VS Code ✅ Installing `Flask-MySQL` Connector ✅ Creating a Flask App with MySQL Integration ✅ Running SQL Queries from Flask ✅ Performing CRUD Operations in Flask — ## **🔹 Prerequisites** Before starting, ensure you have: ✔️ **Python 3.x** installed → [Download Python](https://www.python.org/downloads/) ✔️ **MySQL Server** installed → [Download MySQL](https://dev.mysql.com/downloads/) ✔️ **VS Code** installed → [Download VS Code](https://code.visualstudio.com/) ✔️ **MySQL Workbench (Optional) for Database Management** — ## **🔹 Step-by-Step Guide** ### **1️⃣ Install Required Packages** Open **VS Code Terminal** and run the following commands: “`bash
# Create a project directory
mkdir flask-mysql && cd flask-mysql # Create a virtual environment
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate # Install Flask and MySQL Connector
pip install flask flask-mysql mysql-connector-python
“` — ### **2️⃣ Set Up a Flask Application** Create a file named **`app.py`** and add the following Flask code: “`python
from flask import Flask, render_template
import mysql.connector app = Flask(__name__) # Configure MySQL Connection
db = mysql.connector.connect( host="localhost", user="your_username", password="your_password", database="your_database"
)
cursor = db.cursor() @app.route('/')
def home(): cursor.execute("SELECT 'Hello, Flask with MySQL!'") message = cursor.fetchone()[0] return f"[h1]{message}[/h1]" if __name__ == "__main__": app.run(debug=True)
“` Replace `"your_username"`, `"your_password"`, and `"your_database"` with your actual MySQL credentials. — ### **3️⃣ Create a MySQL Database** Log in to MySQL via terminal or MySQL Workbench and run: “`sql
CREATE DATABASE flaskdb;
USE flaskdb; CREATE TABLE users ( id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(100), email VARCHAR(100) UNIQUE
); INSERT INTO users (name, email) VALUES ('John Doe', 'john@example.com');
“` — ### **4️⃣ Run Flask App in VS Code** To start the Flask app, run: “`bash
python app.py
“` Visit **http://127.0.0.1:5000/** in your browser, and you should see **"Hello, Flask with MySQL!"** — ### **5️⃣ Fetch Data from MySQL in Flask** Modify **`app.py`** to display database records: “`python
@app.route('/users')
def users(): cursor.execute("SELECT * FROM users") users_list = cursor.fetchall() return f"[h2]Users:[/h2]" + " 8br 9".join([f"{user[1]} – {user[2]}" for user in users_list])
“` Restart Flask and visit **http://127.0.0.1:5000/users** to see database records. — ## **🔹 Who Is This Tutorial For?** ✅ Python & Flask Developers ✅ Backend Engineers Working with Databases ✅ Anyone Looking to Build Web Apps with Flask & MySQL — ## **🔹 Resources Mentioned in This Video:** 📌 Flask Documentation → [https://flask.palletsprojects.com/](https://flask.palletsprojects.com/) 📌 MySQL Documentation → [https://dev.mysql.com/doc/](https://dev.mysql.com/doc/) 📌 VS Code Download → [https://code.visualstudio.com/](https://code.visualstudio.com/) — ## **💡 Pro Tips for Smooth Setup** ✔ Ensure MySQL Server is **running** before connecting. ✔ Always use **virtual environments** for Python projects. ✔ Use **Flask-SQLAlchemy** for an ORM-based approach. ✔ If you get connection errors, **check your MySQL username/password.** — ## **👍 Like, Share & Subscribe!** If this tutorial helped you, please **LIKE, SHARE, and SUBSCRIBE** for more **Flask, Python, and Web Development** tutorials! 🚀 💬 Got questions? Drop them in the **comments** below! — ### **🔹 Hashtags:** #Flask #MySQL #Python #VSCode #WebDevelopment #FlaskTutorial #Database #PythonMySQL #BackendDevelopment #SQL Start building powerful Flask apps with MySQL today! 🐍🔥

Want to containerize your Flask application with Docker? 🐳 In this tutorial, we’ll walk you through the process of building a **Docker image** for a Flask app and running it seamlessly on your system. This is perfect for developers looking to deploy Flask applications in a **consistent and portable** environment. — ### **What You’ll Learn in This Video:** ✅ What is Docker & Why Use It for Flask? ✅ Setting Up a Flask App for Dockerization ✅ Writing a Dockerfile for Flask ✅ Building and Running a Docker Image ✅ Exposing Flask to the Host System ✅ Debugging and Managing Docker Containers — ## **Why Use Docker for Flask?** – 📦 Creates an isolated, reproducible environment – 🚀 Eliminates "works on my machine" issues – ⚡ Simplifies deployment across multiple environments – 🔄 Works seamlessly with cloud platforms — ## **Step-by-Step Guide** ### **1️⃣ Install Prerequisites** Before you start, ensure you have: ✔️ Python & Flask installed ✔️ Docker installed ([Download Docker](https://www.docker.com/get-started)) — ### **2️⃣ Create a Flask App** If you don’t have a Flask project, create a simple app: “`bash
mkdir flask-docker && cd flask-docker
python -m venv venv
source venv/bin/activate # For Windows: venv\Scripts\activate
pip install flask
“` Create a **`app.py`** file with the following content: “`python
from flask import Flask app = Flask(__name__) @app.route("/")
def home(): return "Hello, Dockerized Flask!" if __name__ == "__main__": app.run(host="0.0.0.0", port=5000)
“` — ### **3️⃣ Create a `requirements.txt` File** “`bash
flask
“`
Save this file in the project folder. — ### **4️⃣ Create a `Dockerfile`** Inside your **flask-docker** directory, create a file named **Dockerfile** and add the following content: “`dockerfile
# Use the official Python image as the base image
FROM python:3.9 # Set the working directory in the container
WORKDIR /app # Copy the current directory contents into the container at /app
COPY . /app # Install dependencies
RUN pip install –no-cache-dir -r requirements.txt # Expose the Flask port
EXPOSE 5000 # Run the Flask app
CMD ["python", "app.py"]
“` — ### **5️⃣ Create a `.dockerignore` File** To exclude unnecessary files, create a **`.dockerignore`** file: “`
__pycache__/
*.pyc
*.pyo
venv/
“` — ### **6️⃣ Build the Docker Image** Run the following command in your project directory: “`bash
docker build -t flask-app .
“` — ### **7️⃣ Run the Docker Container** To run the Flask app inside a container, use: “`bash
docker run -p 5000:5000 flask-app
“` Now, open your browser and visit: 🔗 [http://localhost:5000](http://localhost:5000) — ### **8️⃣ (Optional) Run in Detached Mode** To keep the container running in the background: “`bash
docker run -d -p 5000:5000 flask-app
“` — ### **9️⃣ (Optional) View Running Containers** List all running containers: “`bash
docker ps
“` Stop a container: “`bash
docker stop container_id
“` — ## **Who Is This Tutorial For?** – 🚀 Developers looking to deploy Flask apps using Docker – 🛠️ Beginners who want to learn containerization – 💻 Anyone interested in streamlining app deployment — ## **Resources Mentioned in This Video:** – 🔗 Docker Docs: [https://docs.docker.com/](https://docs.docker.com/) – 📜 Flask Docs: [https://flask.palletsprojects.com/](https://flask.palletsprojects.com/) — ## **Pro Tips for a Smooth Setup:** ✅ Use a **`.dockerignore`** file to exclude unnecessary files. ✅ **Expose the correct ports** so Flask is accessible outside the container. ✅ Bind mount a volume during development to **avoid rebuilding the image** every time. “`bash
docker run -v $(pwd):/app -p 5000:5000 flask-app
“` — ## **Don’t Forget to Subscribe!** If this tutorial helped you, give it a **thumbs up 👍, subscribe** for more Docker and Python content, and leave a comment if you have any questions! 🚀 ### **Hashtags:** #Docker #Flask #Python #DockerTutorial #Containerization #WebDevelopment #DevOps #FlaskDocker #PythonDevelopment #DeployFlask Start running your Flask apps with Docker today! 🐳🔥