What’s Included?
High-Quality Video, E-book & Audiobook
Modules Quizzes
AI Mentor
Access for Tablet & Phone
Online Proctored Exam with One Free Retake
Prerequisites
- Familiarity with basic concepts of Artificial Intelligence (AI), without the need for technical expertise.
- Openness to generate innovative ideas and concepts, leveraging AI tools effectively in the process.
- Ability to analyze information critically and evaluate the implications of AI and Robotics technologies.
- Readiness to engage in problem-solving activities and apply AI techniques to real-world scenario
Self Study Materials Included
Videos
Engaging visual content to enhance understanding and learning experience.
Podcasts
Insightful audio sessions featuring expert discussions and real-world cases.
Audiobooks
Listen and learn anytime with convenient audio-based knowledge sharing.
E-Books
Comprehensive digital guides offering in-depth knowledge and learning support.
Module Wise Quizzes
Interactive assessments to reinforce learning and test conceptual clarity.
Additional Resources
Supplementary references and list of tools to deepen knowledge and practical application.
Tools You’ll Master
OpenAI Gym
GreyOrange
Neurala
Dialogflow
What You’ll Learn
Algorithm Development and Implementation
Developing the ability to implement deep learning and reinforcement learning algorithms specifically tailored for robotics, equipping learners with the skills to create intelligent and adaptive robotic behaviors.
Human-Robot Interaction and Communication
Gaining expertise in Natural Language Processing (NLP) for facilitating effective human-robot interaction, enhancing the ability of robots to understand and respond to human commands and communications.
Generative AI for Creative Applications
Learning to apply generative AI techniques for enhancing robotic creativity, allowing robots to generate novel solutions and approaches in various tasks and problem-solving scenarios.
Practical Application and Use-Case Implementation
Developing hands-on experience through practical activities and real-world use-cases, which reinforces theoretical knowledge and provides learners with the skills to apply their learning to actual robotic projects and challenges.
Course Modules
Module 1: Introduction to Robotics and Artificial Intelligence (AI)
- 1.1 Overview of Robotics: Introduction, History, Evolution, and Impact
- 1.2 Introduction to Artificial Intelligence (AI) in Robotics
- 1.3 Fundamentals of Machine Learning (ML) and Deep Learning
- 1.4 Role of Neural Networks in Robotics
Module 2: Understanding AI and Robotics Mechanics
- 2.1 Components of AI Systems and Robotics
- 2.2 Deep Dive into Sensors, Actuators, and Control Systems
- 2.3 Exploring Machine Learning Algorithms in Robotics
Module 3: Autonomous Systems and Intelligent Agents
- 3.1 Introduction to Autonomous Systems
- 3.2 Building Blocks of Intelligent Agents
- 3.3 Case Studies: Autonomous Vehicles and Industrial Robots
- 3.4 Key Platforms for Development: ROS (Robot Operating System)
Module 4: AI and Robotics Development Frameworks
- 4.1 Python for Robotics and Machine Learning
- 4.2 TensorFlow and PyTorch for AI in Robotics
- 4.3 Introduction to Other Essential Frameworks
Module 5: Deep Learning Algorithms in Robotics
- 5.1 Understanding Deep Learning: Neural Networks, CNNs
- 5.2 Robotic Vision Systems: Object Detection, Recognition
- 5.3 Hands-on Session: Training a CNN for Object Recognition
- 5.4 Use-case: Precision Manufacturing with Robotic Vision
Module 6: Reinforcement Learning in Robotics
- 6.1 Basics of Reinforcement Learning (RL)
- 6.2 Implementing RL Algorithms for Robotics
- 6.3 Hands-on Session: Developing RL Models for Robots
- 6.4 Use-case: Optimizing Warehouse Operations with RL
Module 7: Generative AI for Robotic Creativity
- 7.1 Exploring Generative AI: GANs and Applications
- 7.2 Creative Robots: Design, Creation, and Innovation
- 7.3 Hands-on Session: Generating Novel Designs for Robotics
- 7.4 Use-case: Custom Manufacturing with AI
Module 8: Natural Language Processing (NLP) for Human-Robot Interaction
- 8.1 Introduction to NLP for Robotics
- 8.2 Voice-Activated Control Systems
- 8.3 Hands-on Session: Creating a Voice-command Robot Interface
- 8.4 Case-Study: Assistive Robots in Healthcare
Module 9: Practical Activities and Use-Cases
- 9.1 Hands-on Session-1: Building AI Models for Object Recognition using Python Programming
- 9.2 Hands-on Session-2: Path Planning, Obstacle Avoidance, and Localization Implementation using Python Programming
- 9.3 Hands-on Session-3: PID Controller Implementation using Python programming
- 9.4 Use-cases: Precision Agriculture, Automated Assembly Lines
Module 10: Emerging Technologies and Innovation in Robotics
- 10.1 Integration of Blockchain and Robotics
- 10.2 Quantum Computing and Its Potential
Module 11: Exploring AI with Robotic Process Automation
- 11.1 Understanding Robotic Process Automation and its use cases
- 11.2 Popular RPA Tools and Their Features
- 11.3 Integrating AI with RPA
Module 12: AI Ethics, Safety, and Policy
- 12.1 Ethical Considerations in AI and Robotics
- 12.2 Safety Standards for AI-Driven Robotics
- 12.3 Discussion: Navigating AI Policies and Regulations
Module 13: Innovations and Future Trends in AI and Robotics
- 13.1 Latest Innovations in Robotics and AI
- 13.2 Future of Work and Society: Impact of AI and Robotics
Optional Module: AI Agents for Robotics
- 1. What Are AI Agents
- 2. Key Capabilities of AI Agents in Robotics
- 3. Applications and Trends for AI Agents in Robotics
- 4. How Does an AI Agent Work
- 5. Core Characteristics of AI Agents
- 6. The Future of AI Agents in Robotics
- 7. Types of AI Agents
Frequently Asked Questions
The AI+ Robotics™ Certification provides a comprehensive understanding of the intersection of Artificial Intelligence (AI) and Robotics.
This certification is ideal for professionals and enthusiasts interested in AI and Robotics, including those with basic familiarity with AI concepts.
You will gain hands-on experience in building AI models, training neural networks, developing reinforcement learning models.
This certification will enhance your skills in AI and Robotics, making you a valuable asset in industries adopting automation and AI-driven solutions.
Participants should have a basic understanding of AI concepts, be open to generating innovative ideas, have the ability to critically analyze information.