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AI+ Robotics™ Self-Paced Learning
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Module 1: Introduction to Robotics and Artificial Intelligence (AI)
1.0 Introduction to Robotics and Artificial Intelligence (AI)
1.1 Introduction to Robotics
1.2 Historical Milestones in Robotics Development
1.3 Evolution of Robotic Technologies and Their Impact on Industries
1.4 Definition of AI and its Role in Robotics
1.5 Types of AI used in Robotics (e.g., reactive, limited memory, theory of mind)
1.6 Explanation of Machine Learning and its Applications in Robotics
1.7 Overview of Deep Learning, Neural Networks, and Their Relevance to Robotics
1.8 Artificial Neural Networks (ANNs) and their Function in Robotic
1.9 Examples: Neural Network Applications in Robotics
1.10 Summary: Introduction to Robotics and ArtificialIntelligence (AI)
Quiz
Module 2: Understanding AI and Robotics Mechanics
2.0 Introduction: Understanding AI and Robotics Mechanics
2.1 Hardware Components: Sensors, Actuators, Processors, and Controllers
2.2 Software Components
2.3 Sensors
2.4 Actuators and Control Systems
2.5 Supervised Learning
2.6 Unsupervised Learning
2.7 Reinforcement Learning
2.8 Neural Networks
2.9 Summary: Understanding AI and Robotics Mechanics
Quiz
Module 3: Autonomous Systems and Intelligent Agents
3.0 Intro: Autonomous Systems and Intelligent Agents
3.1 Autonomous Systems: Definition, Traits, and Industry Examples (e.g., Self-Driving Cars, Drones)
3.2 Understanding the Components and Interaction Mechanisms of Intelligent Agents
3.3 Real-World Examples and Challenges in Autonomous Systems
3.4 Key Platforms for Development: ROS (Robot Operating System)
3.5 Overview of ROS and Its Role in Robotics Development
3.6 Benefits of Using ROS for Building Autonomous Systems
3.7 Summary: Autonomous Systems and Intelligent Agents
Quiz
Module 4: AI and Robotics Development Frameworks
4.0 Introduction: AI and Robotics Development Frameworks
4.1 Basics of Python Programming Language
4.2 Using Python for Robotics Development and Machine Learning
4.3 Overview of TensorFlow and PyTorch Libraries
4.4 Implementation of TensorFlow and PyTorch for AI Algorithms
4.5 Overview of Other Popular Robotics Development Frameworks (e.g., OpenCV, Robot Operating System)
4.6 Applications and Benefits of Using These Frameworks in AI and Robotics Projects
4.7 Summary: AI and Robotics Development Frameworks
Quiz
Lab Practice 4.1
Lab Practice 4.2
Python File Download
Module 5: Deep Learning Algorithms in Robotics
5.0 Introduction: Deep Learning Algorithms in Robotics
5.1 Neural Networks and CNNs in Robotics
5.2 CNNs for Image Recognition and Object Detection
5.3 Overview of Robotic Vision Systems: Components, Techniques, and Algorithms
5.4 Practical Session: Train a CNN using Real-World Data for Object
5.5 Guidance on Data Preprocessing, Model Training, and Evaluation
5.6 Robotic Vision Systems in Action: Case Studies and Examples
5.7 Summary: Deep Learning Algorithms in Robotics
Quiz
Lab Practice 5.1
Python File Download
Module 6: Reinforcement Learning in Robotics
6.0 Introduction: Reinforcement Learning in Robotics
6.1 RL Concept and its Application in Robotics
6.2 Key Components of RL such as Agents, Environments, States, Actions
6.3 Overview of Popular RL Algorithms Used in Robotics (e.g., Q-learning, DQN)
6.4 Implementation of RL Algorithms for Robotic Applications
6.5 Case Study: Demonstrating How RL is Used to Optimize Warehouse
6.6 Examples: Improved Efficiency and Resource Utilization through RL-Based Robotic
6.7 Summary: Reinforcement Learning in Robotics
Quiz
Lab Practice 6.1
Lab Practice 6.2
Lab Practice 6.3
Python File Download
Module 7: Generative Artificial Intelligence (AI) for Robotic Creativity
7.0 Introduction: Generative AI for Robotic Creativity
7.1 Introduction to Generative Adversarial Networks (GANs) and Working
7.2 Applications of GANs in Robotics, such as Generating Realistic Images
7.3 Generative AI is Enabling Robots to Design, Create, and Innovate
7.4 Examples: Creative Projects and Products Developed by AI-Driven Robots
7.5 Optimizing AI Parameters in Robotics
7.6 Case Study: Demonstrating the Use of AI-Generated Designs in Custom Manufacturing
7.7 Benefits of Generative AI for Creating Unique and Customized Products
7.8 Summary: Generative Artificial Intelligence (AI) for Robotic Creativity
Quiz
Lab Practice 7.1
Lab Practice 7.2
Python File Download
Module 8: Natural Language Processing (NLP) for Human-Robot Interaction
8.0 Introduction: Natural Language Processing (NLP) for Human-Robot Interaction
8.1 Basics of Natural Language Processing and its Application in Robotics
8.2 Overview of NLP techniques used for Human-Robot Communication
8.3 Design and Implementation of Voice-Activated Control Systems
8.4 Integration of NLP Algorithms for Recognizing and Processing Voice Commands
8.5 Case study: The use of NLP-Enabled Robots in Healthcare Settings
8.6 Latest Innovations in Robotics and AI
8.7 Summary: Natural Language Processing (NLP) for Human-Robot Interaction
Quiz
Lab Practice 8.1
Lab Practice 8.2
Python File Download
Module 9: Emerging Technologies and Innovation in Robotics
9.0 Introduction: Emerging Technologies and Innovation in Robotics
9.1 Enhancing Security and Traceability with Blockchain in Robotics
9.2 Use-case: Blockchain Integration in Robotic Systems
9.3 Understanding the Basics of Quantum Computing and its Implications
9.4 Quantum Computing and AI Algorithms in Robotics
9.5 Use-Case: Environmental Conservation with Robotics
9.6 Summary: Emerging Technologies and Innovation in Robotics
Quiz
Lab Practice 9.1
Lab Practice 9.2
Lab Practice 9.3
Lab Practice 9.4
Lab Practice 9.5
Lab Practice 9.6
Python File Download
Module 10: Exploring Artificial Intelligence (AI) with Robotic Process Automation
10.0 Introduction: Exploring Artificial Intelligence (AI) with Robotic Process Automation
10.1 Robotic Process Automation (RPA) and its Significance in Automating
10.2 Discuss the Basic Functioning of RPA and its Typical Use Cases
10.3 Identify the Leading RPA Tools in the Market
10.4 Compare the Features, Advantages, and Industry Applications of RPA
10.5 Concepts of AI-powered RPA: Cognitive Automation and Decision
10.6 Examples of AI integrations: Natural Language Processing for processing unstructured data, Machine Learning models for predictive tasks
10.7 Case Studies on AI-Enhanced RPA Implementations in Different
10.8 Summary: Exploring Artificial Intelligence (AI) with Robotic Process Automation
Quiz
Module 11: Artificial Intelligence (AI) Ethics, Safety, and Policy
11.0 Introduction: AI Ethics, Safety, and Policy
11.1 Discussing Ethical Challenges such as Bias, Transparency, and Accountability
11.2 Strategies for Designing Ethical AI Systems in Robotics
11.3 Overview of Safety Standards and Regulations for AI-Driven
11.4 Importance of Safety in Robotic Design, Operation, and Interaction
11.5 Exploring Current and Future AI Policies and Regulations
11.6 Impact of AI Policies on Robotics Development
11.7 Summary: Artificial Intelligence (AI) Ethics, Safety, and Policy
Quiz
Module 12: Innovations and Future Trends in AI and Robotics
12.0 Introduction: Innovations and Future Trends in AI and Robotics
12.1 Exploring Cutting-Edge Developments and Breakthroughs
12.2 Examples: Innovative AI and Robotics Projects and Technologies
12.3 How AI and Robotics are Reshaping Industries and Workplaces
12.4 Societal Implications of AI and Robotics Advancements
12.5 Summary: Innovations and Future Trends in AI and Robotics
Quiz
Resources
AI+ Robotics Tools
AI+ Robotics Blueprint
AI+ Robotics Detailed Curriculum
AI+ Robotics Resources and References
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Robotics Examination
AI+ Robotics Examination
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AI+ Robotics™ Self-Paced Learning
