AED
UAD Dirham
Code: AED
Self Paced
AI for Autonomous Systems: Overview
Building Intelligent Machines That Sense, Decide, and Act Independently
Early access to the e-LMS platform is included
About This Course
The AI for Autonomous Systems: Overview course is a free, beginner-friendly self-paced program designed to introduce learners to how artificial intelligence enables machines to operate independently without constant human control.
The course explains how AI is used in systems such as self-driving cars, drones, robots, and smart devices. Learners will explore key concepts such as perception, decision-making, navigation, and automation in autonomous systems. This course is ideal for beginners who want to understand how intelligent systems interact with the real world.
Aim
The aim of this course is to introduce learners to the core concepts, technologies, and applications of Artificial Intelligence in autonomous systems, enabling them to understand how intelligent machines operate with minimal human intervention.
Program Objectives
- Understand the meaning and importance of autonomous systems.
- Explain the role of AI in enabling autonomy.
- Identify major components of autonomous systems such as sensors, perception, planning, control, and decision-making.
- Understand how machine learning and computer vision are used in intelligent systems.
- Explore applications of AI in autonomous vehicles, robotics, drones, smart manufacturing, and defense systems.
- Recognize the challenges related to safety, reliability, ethics, regulation, and real-time deployment.
- Develop a foundational understanding of future trends in autonomous technologies.
Program Structure
Module 1: Introduction to Autonomous Systems
- What are Autonomous Systems?
- Role of AI in Autonomous Systems
- Examples: Self-Driving Cars, Drones, Robots
- Applications in Industry and Daily Life
Module 2: Perception and Data in Autonomous Systems
- Understanding Sensors and Data
- Introduction to Computer Vision and Sensor Data
- How Machines Perceive the Environment
- Importance of Real-Time Data
Module 3: Decision-Making and Control
- How Autonomous Systems Make Decisions
- Basic Idea of Path Planning and Navigation
- Role of Machine Learning in Decision-Making
- Examples of Automated Control Systems
Module 4: Applications of Autonomous Systems
- Autonomous Vehicles and Transportation
- Robotics and Industrial Automation
- Drones and Smart Surveillance
- AI in Smart Cities and Infrastructure
Module 5: Future Scope and Challenges
- Challenges in Autonomous Systems: Safety and Reliability
- Ethical and Regulatory Considerations
- Future Trends in AI and Automation
- Career Opportunities in AI and Robotics
Who Should Enrol?
- Students from engineering, computer science, robotics, electronics, electrical, mechanical, aerospace, data science, and related disciplines.
- Ph.D. scholars and researchers working in AI, robotics, autonomous vehicles, drones, intelligent systems, automation, or smart technologies.
- Faculty members and academicians interested in teaching or researching autonomous systems.
- Industry professionals working in AI, robotics, automation, automotive technology, IoT, embedded systems, smart manufacturing, or defense technologies.
- Beginners with basic awareness of computers, programming, or AI who want to explore autonomous technologies.
Program Outcomes
- Describe how autonomous systems sense, think, and act.
- Differentiate between manual, automated, and autonomous systems.
- Explain the AI workflow used in autonomous platforms.
- Understand the role of sensors, data, algorithms, and control mechanisms.
- Identify real-world use cases of AI-powered autonomous systems.
- Discuss safety, ethical, and technical challenges in autonomous system design.
- Build readiness for advanced learning in autonomous vehicles, robotics, drones, and intelligent mobility systems.
Fee Structure
Discounted: ₹199 | $20
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- One-on-one project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
★★★★★
Cancer Drug Discovery: Creating Cancer Therapies
Mario Rigo • ★★★★★
Power BI and Advanced SQL Mastery Integration Workshop, CRISPR-Cas Genome Editing: Workflow, Tools and Techniques
Silvia Santopolo • ★★★★★
Artificial Intelligence for Cancer Drug Delivery
G Jyothi • ★★★★★
Artificial Intelligence for Cancer Drug Delivery
RAVIKANT SHEKHAR • View All Feedbacks →