Welcome to the Robo-AI-Recorded repository—a meticulously curated guide to mastering Python, Artificial Intelligence, Machine Learning, and Robot Operating System (ROS). Whether you're a beginner or an advanced learner, this repository offers a structured path to enhance your expertise across these cutting-edge technologies.
Content is thoughtfully divided into Basic and Advanced tiers for seamless learning progression.
| Topic Name | Basic | Advanced |
|---|---|---|
| Python 101 | - Why Python? Intro to Google Colab - Python basics (syntax, datatypes) - Conditional statements, Collections, Loops - String manipulation (slicing, indexing, formatting, splitting, joining) - Classes, objects, Importing Libraries - Python examples |
- Object-Oriented Programming (OOPs) - Classes & Objects, Inheritance, Polymorphism & Scope - Keywords ( self, with, open, etc.)- Functions and Methods - Creating custom Python libraries |
| Artificial Intelligence | - Theoretical understanding of AI, ML, and DL - Concepts of Search, Knowledge, and Uncertainty |
- Hands-on coding for: - Depth-first Search - Breadth-first Search - Greedy Best-first Search - A* Search |
| Machine Learning | - Overview of Regression and Classification Problems | - Hands-on applications, mathematical intuition, and project development for: - Linear Regression - Logistic Regression - Decision Trees |
| Reinforcement Learning | - Introduction to RL - Algorithms in Discrete and Continuous Spaces - Q-learning, PPO |
- Hands-on RL: - Environment definition - Simulation of a toy-world |
| Artificial Neural Networks | - History of AI - Biological Neurons vs Artificial Neurons - Perceptrons, Single-layer architecture - Multi-layer networks |
- Forward and backward propagation - Hands-on programming a Perceptron from scratch |
| Deep Learning | - Activation Functions - Types of Deep Neural Network Architectures - Encoders and Decoders |
- Hands-on Deep Learning Architecture Development using PyTorch/TensorFlow |
| Generative AI | - Introduction to Generative AI - Encoder-decoder architecture - Large-Language Models, Diffusion Models |
- Hands-on usage of state-of-the-art LLMs using Python APIs - Prompt Engineering |
| Large Language Modeling | - Introduction to HuggingFace - Hands-on Project Development - GUI for ChatBots |
- Creating a personal assistant using Gradio - Creating a Text-Summarization App (similar to Quillbot) |
| Image Processing | - What is an image (human vs computer)? - Image enhancement techniques, color correction |
- Hands-on: - Image sharpening - Edge detection - Noise reduction - Feature extraction |
| Convolutional Neural Nets | - Convolutional Neural Networks - Types of Convolutions (Strided, Dilated, Padding, Pooling Layers) |
- Hands-on coding for computer vision using OpenCV - Modern computer vision applications: - YOLOx Series - SAM by Meta |
| Topic Name | Basic | Advanced |
|---|---|---|
| ROS2 Installation and Setup | - Downloading ISO image for ROS2 Humble Hawksbill and Ubuntu - Install Ubuntu 22.04 on Oracle VirtualBox - Installing ROS2 Humble in the VM |
- Installing Programming Tools (e.g., Terminal, Visual Studio Code) - Install Colcon - Create Workspace |
| Introduction to ROS2 | - What is ROS2? Why, and When to use it? - ROS2 Application in Industry, Use-case and applications |
- ROS2 Fundamentals - Nodes, RQT, RQT_Graph - Hands-on: Writing your first Python Node (Minimum Implementation) |
| Nodes | - Hands-on: Writing your first Python Node (OOPs Method) | - Talker-Listener Demo - TurtleSim Simulation - Teleoperation |
| Publisher / Subscriber | - Understanding Publisher-Subscriber Architecture in context of Robotics | - Hands-on writing your own Publisher Node and a Subscriber Node |
| ROS2 Essentials | - Fundamentals of ROS2 in Robotics - Topics, Services, Launch files, Workspace |
- Packages - Understanding Transforms (TFs) |
| Robot Description and Visualization | - Create a URDF of a Robot - Create and Visualize a link, Material property - Combine 2 links with a joint, Types of joints in a URDF, Add a wheel |
- Robot State Publisher - Improve URDF with XACRO |
| Simulation | - Run Gazebo - How Gazebo works - Add Inertia and Collision Tags in the URDF |
- Spawn the robot - Fixing inertia values - Create a world in Gazebo - Launch robot in the world |
| TurtleBotX | - Introduction to TurtleBot3 - Simulation of Sensors and Actuator |
- Basic TurtleBot3 Controls Architecture using Teleoperation and Sensor Data |
| SLAM (Mapping) | - Introduction to Navigation2 Stack in ROS2 - Where and Why to use it? - Installing Nav2 stack, tools to use |
- Introduction to Simultaneous Localization and Mapping (SLAM) - Hands-on generating and saving the map with SLAM |
| SLAM (Navigation) | - Hands-on Navigate using generated map - Waypoint following for TurtleBot3 |
- Dynamic Obstacle Avoidance - Understanding Global and Local Planning Methods |
This repository is organized into directories corresponding to each topic. Each directory contains:
- 📖 Lecture Notes
- 💻 Code Examples
- 🧠 Exercises
- 🔨 Project Templates
Contributions are welcome! Raise an issue or comment with your feedback to help improve the content.
This repository is licensed under the MIT License.