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AI+ Robotics™

# AT-420

Empowering Innovation: Master Artificial Intelligence and Robotics Integration

The AI+ Robotics™ certification provides a transformative learning experience, focusing on the integration of Artificial Intelligence (AI) with Robotics. Participants explore foundational concepts such as Deep Learning Algorithms and Reinforcement Learning, tailored for real-world robotics applications. Modules cover autonomous systems, intelligent agents, and Generative AI, preparing learners to lead in the evolving field of smart automation. Through practical projects and real-world case studies, participants gain hands-on experience in designing, implementing, and optimising robotic systems. Ethical considerations and industry policies are navigated to ensure responsible innovation. This program equips learners with robust theoretical knowledge and practical expertise, enabling them to shape the future of robotics and smart technologies.

$495.00

High-Quality Video, E-book & Audiobook

Modules Quizzes

AI Mentor

Access for Tablet & Phone

Online Proctored Exam with One Free Retake

LABs Practices

Prerequisites

Familiarity with AI Basics: Understanding of basic AI concepts without the need for technical expertise.
Innovative Mindset: Openness to generating creative ideas and leveraging AI tools for robotics development.
Analytical Skills: Ability to critically analyze information and evaluate the implications of Robotics and AI technologies.
Problem-Solving Readiness: Willingness to engage in real-world scenarios using AI and Robotics techniques.

Exam Details

Exam Blueprint

Modules	Percentage
Introduction to Robotics and Artificial Intelligence (AI)	5
Understanding AI and Robotics Mechanics	6
Autonomous Systems and Intelligent Agents	6
AI and Robotics Development Frameworks	9
Deep Learning Algorithms in Robotics	9
Reinforcement Learning in Robotics	9
Generative AI for Robotic Creativity	9
Natural Language Processing (NLP) for Human-Robot Interaction	9
Practical Activities and Use-Cases	8
Emerging Technologies and Innovation in Robotics	9
Exploring AI with Robotic Process Automation (RPA)	9
AI Ethics, Safety, and Policy	6
Innovations and Future Trends in AI and Robotics	6

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.

Labs

Interactive lab sessions to apply concepts and strengthen technical skills.

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 Will You Learn?

Algorithm Development and Implementation

Develop skills in implementing Deep Learning and Reinforcement Learning Algorithms, creating adaptive and intelligent robotic systems.

Generative AI for Robotics

Learn to apply Generative AI techniques to enable robots to generate creative solutions for diverse challenges.

Human-Robot Interaction

Master Natural Language Processing (NLP) and other tools to enhance communication between robots and humans.

Practical Robotics Applications

Gain hands-on experience in applying AI to robotic projects through real-world use cases.

Certification 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

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Industry Opportunities after Certification Completion

Median Salaries

$59,391

With AI+ Robotics™

$130,558

% Difference

120

AI Robotics Integration Expert

Enhance existing robotic systems by integrating cutting-edge AI technologies for better performance and new functionalities.

Robotics Engineer with AI Expertise

Design advanced robots, leveraging AI to optimize decision-making, autonomy, and functionality.

AI Robotics System Developer

Build complex robotic systems with capabilities such as learning, perception, and adaptive behaviours.

AI Intelligent Robotics Specialist

Specialize in developing intelligent robots for advanced tasks like navigation, human interaction, and manipulation.

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Learner Success Stories

Frequently Asked Questions

What is the AI+ Robotics™ Certification about?

The AI+ Robotics™ Certification provides a comprehensive understanding of the intersection of Artificial Intelligence (AI) and Robotics.

Who should enroll in this certification?

This certification is ideal for professionals and enthusiasts interested in AI and Robotics, including those with basic familiarity with AI concepts.

What practical skills will I gain from this certification?

You will gain hands-on experience in building AI models, training neural networks, developing reinforcement learning models.

How will this certification benefit my career?

This certification will enhance your skills in AI and Robotics, making you a valuable asset in industries adopting automation and AI-driven solutions.

What are the prerequisites for enrolling in the certification?

Participants should have a basic understanding of AI concepts, be open to generating innovative ideas, have the ability to critically analyze information.