Programme Parameters
Foundation
4 Weeks (40 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI for Autonomous Systems: Overview gives you a clear map of how machines are made to sense, decide and act without a human in the loop. You learn the building blocks common to all autonomy — perception, localisation, planning, decision-making and control — and how they combine across domains from robots and drones to self-driving vehicles. The course introduces the key AI methods at an accessible level and confronts the safety, reliability and ethical questions autonomy raises. You finish with a grounded overview of autonomous-systems AI. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This overview course covers AI for autonomous systems — how perception, decision-making and control combine to let machines act on their own across robotics and vehicles.
📋 Course Objectives
1. Explain the autonomy stack: perceive, decide, act.
2. Understand perception and localisation.
3. Grasp planning and decision-making.
4. See how control closes the loop.
5. Weigh safety, reliability and ethics.
👥 Who Should Enroll?
• Engineers and developers new to autonomy
• Robotics and vehicle professionals
• Technical managers
• Students of autonomous systems
🚀 Key Learning Outcomes
• A grounded overview of autonomous systems.
• The ability to follow the field’s concepts.
• A springboard to deeper study.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
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
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
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
Applications of Autonomous Systems
Autonomous Vehicles and Transportation • Robotics and Industrial Automation • Drones and Smart Surveillance • AI in Smart Cities and Infrastructure
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
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Autonomous Systems |
| Covered Tool / Platform | Robotics Basics |
| Covered Tool / Platform | Computer Vision Concepts |
| Covered Tool / Platform | Decision-Making Systems |
Frequently Asked Questions
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