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AI+ Robotics™

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  • Build the Future with Smart Automation
  • Assess your skills before enrolling
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$174.50

Intermediate
AI+ Robotics.
40h
1 Year.
$174.50
Training 5 or more people?
Get a Quote

Build the Future with Smart Automation.

  • AI-Driven Robotics: Apply AI in Deep Learning, Reinforcement Learning, and smart automation
  • Real-World Systems: Work with autonomous systems and intelligent agents
  • Ethics & Innovation: Learn industry-aligned practices and innovation strategies
  • Hands-On Projects: Gain experience designing, optimising, and deploying robotics solutions
  • Demand for Certified AI & Robotics Professionals: Organizations are seeking certified professionals who can integrate AI into robotics to optimize processes, enhance automation, and improve operational efficiency.
  • Risks of Mismanaging AI & Robotics: Mismanagement of robotic systems and AI technologies can lead to operational inefficiencies and safety risks.
  • Role of Certification in Robotics Strategy: Certified professionals are key in developing robotics strategies that maximize performance, safety, and compliance with industry regulations.
  • Career Advantage & Leadership Opportunities: As robotics and AI continue to reshape industries, this certification offers professionals a distinct advantage, positioning them for leadership roles.

Course Curriculum

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

Learning Objectives

  • The AI+ Data certification equips professionals with vital skills for data science.
  • It covers key concepts likeData Science Foundations, Statistics, Programming, and Data Wrangling. Participants delve into advancedtopics such as Generative AI and Machine Learning, preparing them for complex data challenges.
  • Theprogram includes a hands-on capstone project focusing on Employee Attrition Prediction.
  • Emphasis isplaced on Data-Driven Decision-Making and Data Storytelling for actionable insights.
  • Personalizedmentorship, immersive projects, and cutting-edge resources ensure a transformative learning journey,preparing individuals for success in AI and data science.

Resource Center

  • Videos, Use cases, Workshops, E-books and tools.

Target Audience

  • Robotics Engineers Enhance robotic system design and functionality using AI for automation and control.
  • Mechanical Engineers.
  • AI Specialists.
  • IT Specialists & System Integrators.
  • Students & New Graduates.

Job Roles & Industry Outlook 

Robotics Engineer with Al Expertise:
Designs and develops advanced robots, integrating Al algorithms to enhance autonomy, decision- making, and overall robotic functionality.
Al Intelligent Robotics Specialist:
Specializes in developing intelligent robots that utilize Al for advanced tasks, such as navigation, manipulation, and human interaction.
Al Robotics Integration Expert:
Integrates Al technologies into existing robotic systems, enhancing their performance and enabling new functionalities and applications.
Al Robotics System Developer:
Creates complex robotic systems incorporating Al, focusing on enhancing capabilities like perception, learning, and adaptive behavior.

Exam Information

Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Fees include
One year of access to course content, including continuous updates. Certification exam. One exam re-take.

Exam Blueprint:

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%

Explore our Schedules

Oct 4 - Oct 8
GMT 09:00 AM - 05:00 PM
In-person
Mecca
880.5$
5 Days
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Oct 25 - Oct 29
GMT 09:00 AM - 05:00 PM
In-person
Abu Dhabi
880.5$
5 Days
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Jul 12 - Jul 16
GMT 09:00 AM - 05:00 PM
In-person
Kuwait
880.5$
5 Days
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Sep 1- Sep 14
GMT 06:00 PM- 10:00 PM
LVT
Zoom
643.2$
10 Days
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Certificate of Completion

AI+ Robotics.

$174.50

Intermediate
AI+ Robotics.
40h
1 Year.
$174.50
Training 5 or more people?
Get a Quote

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