Artificial Intelligence
Duration
6-12 Months
About the Course
The AI course offers an in-depth understanding of artificial intelligence, covering key areas such as machine learning, deep learning, and neural networks. Students will explore algorithms, data preprocessing, and model evaluation using tools like Python, TensorFlow, and Keras. The curriculum includes practical applications in natural language processing, computer vision, and robotics. Designed for both beginners and professionals, the course combines theoretical knowledge with hands-on projects. By the end of the course, participants will be equipped to build and deploy AI solutions to address real-world challenges.
AI and Robotics: Topics, Tools, Theories, Algorithms, and Applications
Category | Topics | Tools and Software |
Foundations of AI and Robotics | Introduction to Artificial Intelligence and Robotics | Python (NumPy, Pandas), R, MATLAB |
History and Evolution of AI and Robotics | Jupyter Notebook, ROS (Robot Operating System) | |
AI vs. Human Intelligence in Robotics | ||
Machine Learning for Robotics | Introduction to Machine Learning in Robotics | Scikit-learn, TensorFlow, Keras, PyTorch |
Supervised and Reinforcement Learning for Robotics | OpenAI Gym, RLlib | |
Unsupervised Learning Techniques | K-means, PCA, DBSCAN | |
Robotics Fundamentals | Kinematics and Dynamics of Robots | Robot Kinematics Software, V-REP |
Sensors and Actuators | Lidar, IMU, Cameras | |
Robot Vision and Perception | OpenCV, Point Cloud Library (PCL) | |
Robotics Control Systems | Robot Control Architectures | PID Controllers, State Estimation |
Motion Planning and Navigation | A* Algorithm, RRT (Rapidly-exploring Random Trees) | |
Path Planning Algorithms | Dijkstra's Algorithm, RRT* | |
Artificial Intelligence in Robotics | AI Planning and Decision Making | A* Search Algorithm, Markov Decision Processes (MDPs) |
Machine Learning for Robot Perception | Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) | |
Natural Language Processing for Human-Robot Interaction | Speech Recognition, Dialogue Systems | |
Robotics Applications | Industrial Robotics | Robotic Arms, CNC Machines |
Service Robotics | Autonomous Delivery Robots, Assistive Robots | |
Autonomous Vehicles | Self-Driving Cars, UAVs (Drones) | |
Medical Robotics | Surgical Robots, Rehabilitation Robots | |
Ethics and AI Governance in Robotics | Ethical Considerations in Robotics | IEEE Ethically Aligned Design |
Bias and Fairness in AI | Fairness Indicators, Bias Mitigation Strategies | |
Regulations and Policies | Robotics and AI Governance Frameworks |
Tools and Environments:
Integrated Development Environments (IDEs): Jupyter Notebook, MATLAB
Robot Operating System (ROS): Robotics middleware for controlling robotic systems
Simulation Environments: V-REP, Gazebo
Robotics Hardware Platforms: Arduino, Raspberry Pi, NVIDIA Jetson
Vision Libraries: OpenCV, PCL (Point Cloud Library)
Motion Planning Libraries: OMPL (Open Motion Planning Library), ROS Navigation Stack
Syllabus Will Change*