AI+ Robotics™ - eLearning (exam included)
448,00 EUR
- 40 hours
The AI+ Robotics Certification provides an immersive exploration of the intersection between Artificial Intelligence (AI) and Robotics. Tailored for professionals aiming to excel in this field, it covers foundational concepts, advanced Deep Learning (DL), and Reinforcement Learning (RL) techniques applied specifically to robotics.
Key Features
Language
Course and material in English
Level
Intermediate level (Category: AI+ Technical)
1 year platform access
and Virtual Hands-on Lab included
40 hours of video lessons & multimedia
50 hours of study time recommendation
Material
Video, PDF Material, audio eBook, Podcasts, quizzes and assessments.
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included. Valid for 1 year
Tools You’ll Master
OpenAI Gym, GreyOrange, Neurala, Dialogflow
About the course
Shape Tomorrow with Intelligent Robotics
- AI-Powered Automation: Implement AI in Deep Learning, Reinforcement Learning, and smart robotic systems
- Practical Applications: Work with autonomous systems and intelligent agents
- Ethical Innovation: Learn responsible AI practices and industry-aligned strategies
- Hands-On Experience: Design, optimize, and deploy real-world robotics solutions
The program emphasizes autonomous systems, intelligent agents, and generative AI, combining theory with hands-on exercises and real-world case studies. Ethical considerations and policy frameworks are included to promote responsible AI use. Upon completion, participants gain the knowledge and practical skills required to drive innovation and navigate ethical challenges in AI-driven robotics.
Why This Certification Matters
Companies seek certified professionals to integrate AI into robotics, boosting automation and operational efficiency.
Learning Outcomes
At the end of this course, you will be able to:
Algorithm Development & Implementation
Build expertise in Deep Learning and Reinforcement Learning to create intelligent, adaptive robotic systems.
Generative AI for Robotics
Apply generative AI techniques to enable robots to generate innovative solutions for various challenges.
Human-Robot Interaction
Use NLP and other tools to improve communication between humans and robots.
Practical Robotics Applications
Gain hands-on experience by applying AI to real-world robotic projects.
Course timeline
Introduction to Robotics and Artificial Intelligence (AI)
Lesson 1
- 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
Understanding AI and Robotics Mechanics
Lesson 2
- 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
Autonomous Systems and Intelligent Agents
Lesson 3
- 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)
AI and Robotics Development Frameworks
Lesson 4
- 4.1 Python for Robotics and Machine Learning
- 4.2 TensorFlow and PyTorch for AI in Robotics
- 4.3 Introduction to Other Essential Frameworks
Deep Learning Algorithms in Robotics
Lesson 5
- 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
Reinforcement Learning in Robotics
Lesson 6
- 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
Generative AI for Robotic Creativity
Lesson 7
- 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
Natural Language Processing (NLP) for Human-Robot Interaction
Lesson 8
- 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
Practical Activities and Use-Cases
Lesson 9
- 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
Emerging Technologies and Innovation in Robotics
Lesson 10
- 10.1 Integration of Blockchain and Robotics
- 10.2 Quantum Computing and Its Potential
Exploring AI with Robotic Process Automation
Lesson 11
- 11.1 Understanding Robotic Process Automation and its use cases
- 11.2 Popular RPA Tools and Their Features
- 11.3 Integrating AI with RPA
AI Ethics, Safety, and Policy
Lesson 12
- 12.1 Ethical Considerations in AI and Robotics
- 12.2 Safety Standards for AI-Driven Robotics
- 12.3 Discussion: Navigating AI Policies and Regulations
Innovations and Future Trends in AI and Robotics
Lesson 13
- 13.1 Latest Innovations in Robotics and AI
- 13.2 Future of Work and Society: Impact of AI and Robotics
AI Agents for Robotics
Optional Module
- 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
Who Should Enroll in this Program?
Robotics Engineers: Boost robotic system design and automation using AI.
Mechanical Engineers: Apply AI to enhance robotics performance in production and manufacturing.
AI Specialists: Improve the intelligence and autonomy of robotic systems with AI.
IT Specialists & System Integrators: Deploy AI-driven solutions to optimize robotics infrastructure and communication.
Industry Growth
Driving Data-Driven Innovation Across Sectors
- The global AI robotics market is expected to grow at a CAGR of 39.1% from 2023 to 2030. (Source: Grand View Research)
- AI-powered robotics is transforming manufacturing, healthcare, and logistics, enhancing automation and efficiency.
- Adoption of AI-driven robotics is increasing, enabling real-time monitoring and autonomous operations.
- AI automation is crucial in industries like automotive and aerospace, boosting productivity, safety, and cost-effectiveness.
- Robotics with AI is revolutionizing sectors such as agriculture, healthcare, and warehousing, optimizing processes and decision-making.
More Details
Prerequisites
- Basic understanding of Artificial Intelligence (AI) concepts; no advanced technical skills required.
- Willingness to explore innovative ideas and effectively use AI tools.
- Ability to think critically and assess the impact of AI and Robotics technologies.
- Preparedness to tackle real-world problems using AI techniques.
Exam Details
- Duration: 90 minutes
- Passing :70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
- Language: English
Licensing and accreditation
This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Questions
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