Master Certification Program in AI & Robotics

6–9 Months | 30 Weeks | 400–500+ Hours — Design • Build • Fly • Program • Automate • Analyse. UAV design, aerodynamics, mechanical/CAD, electronics, flight control, embedded systems, autonomous navigation, computer vision, GIS/photogrammetry, industry applications, regulations awareness and capstone industry projects. Classroom + electronics lab + CAD lab + flight lab + simulation + field projects.

Program objective: Develop industry-ready UAV engineers capable of designing, assembling, programming, testing, operating and analysing drone systems for real-world applications — not just learning to fly a drone.

Student journey: Understand UAV → Design Airframe → Select Motors & Propellers → Design Power System → Integrate Flight Controller → Configure Sensors → Program UAV → Simulate Flight → Build & Calibrate → Fly Safely → Capture Data → Process Data → Automate Mission → Build Industry Solution.

Core promise: Don't just fly drones. Learn to engineer intelligent aerial systems.

6–9 Months | 30 Weeks | 400–500+ Hours — Robotics • Medical Devices • AI • Computer Vision • Surgical Systems • Rehabilitation • Healthcare Automation. Theory + robotics lab + medical simulation + CAD + electronics + programming + AI + healthcare case studies + capstone.

Program objective: Develop industry-ready engineers who understand healthcare context and can design, build, program, simulate, validate and innovate intelligent robotic systems for clinical workflows — not just build generic robots with healthcare examples.

Student journey: Understand Healthcare → Anatomy & Physiology → Medical Devices → Robotics → Design Mechanisms → Integrate Sensors → Program Robot → Control Systems → Computer Vision & AI → Medical Data → Simulation → Safety Validation → Healthcare Application → Clinical-Workflow Simulation.

Core promise: Don't just build robots. Engineer robotic systems that interact safely with healthcare environments and assist clinicians and patients.

6–9 Months | 32 Weeks | 450–550+ Hours — PLC • SCADA • HMI • Robotics • Drives • Industrial IoT • Machine Vision • AI • Smart Factory. Theory + automation lab + PLC lab + robotics lab + electrical lab + SCADA lab + IIoT lab + industry project.

Program objective: Develop industry-ready automation engineers capable of designing, programming, commissioning, troubleshooting and optimizing automated industrial systems using PLCs, HMIs, SCADA, drives, robotics, industrial networks, machine vision, IIoT and Industry 4.0 technologies — not just PLC programming.

Student journey: Industrial Process → Electrical System → Sensors → Actuators → PLC → HMI → SCADA → Drives → Servo → Industrial Network → Robotics → Machine Vision → IIoT → MES → Digital Twin → AI → Smart Factory.

Core promise: Don't just learn PLC programming. Learn to engineer the connected factory.

6–9 Months | 32 Weeks | 450–550+ Hours — PLC • Embedded C • Microcontrollers • Industrial Automation • IoT • Robotics • CAN • RTOS • Edge AI. Theory + PLC lab + electronics lab + embedded lab + industrial automation lab + robotics + IoT + capstone.

Program objective: Develop engineers who can design, program, integrate and commission complete control systems — from industrial PLCs to intelligent embedded controllers — not just PLC programming or Arduino projects in isolation.

Student journey: Electrical Fundamentals → Digital Electronics → Microcontrollers → Embedded C → Sensors & Actuators → PLC → Industrial Control → HMI → Industrial Communication → Embedded Communication → RTOS → IoT → Edge Computing → Robotics → AI → Integrated Industrial System.

Core promise: Don't just program controllers. Learn to engineer intelligent control systems.

6–9 Months | 32 Weeks | 500–650+ Hours — RTL Design • Verification • FPGA • ASIC • Physical Design • DFT • SoC • Semiconductor Engineering. Theory + digital design lab + HDL lab + FPGA lab + verification lab + ASIC flow + physical design + capstone.

Program objective: Develop industry-ready semiconductor engineers who understand the complete design flow from specification to silicon — not just Verilog syntax in isolation.

Student journey: Electronics Fundamentals → Digital Logic → Computer Architecture → CMOS & VLSI → Verilog → SystemVerilog → RTL Design → Simulation → Functional Verification → FPGA → Synthesis → STA → Physical Design → DFT → Physical Verification → ASIC/SoC → AI-Assisted EDA → Tape-Out-Oriented Capstone.

Core promise: Don't just learn Verilog. Learn the complete semiconductor design flow from specification to silicon.

Discover Python's full potential for robotics and AI development. Learn how to handle, analyze, and visualize data effectively, and build automation scripts for robotic systems.

Build a strong foundation in electronics and circuit design. Understand the fundamental principles that power all electronic devices and robotic systems.

Master C++ programming for embedded systems and robotics. Learn efficient programming techniques for microcontrollers and real-time applications.

Master Arduino development for robotics applications. Learn to interface sensors, control actuators, and build autonomous systems using Arduino microcontrollers.

Develop IoT and wireless robotics applications using ESP32 and ESP8266. Learn WiFi, Bluetooth connectivity, and cloud integration for smart robotic systems.

Master IoT communication protocols for connected robotic systems. Learn to build networked robots that can communicate and collaborate.

Master STM32 microcontrollers for advanced embedded robotics applications. Learn ARM Cortex-M architecture and real-time operating systems.

Develop advanced robotics applications using Raspberry Pi. Learn GPIO programming, computer vision, and IoT integration for intelligent robotic systems.

Explore the basics of machine learning and AI, where algorithms learn from data to make predictions and support well-informed decisions for robotic systems.

Explore the immersive realm of deep learning, a technology that utilizes neural networks to mimic the functions of the human brain in order to process and make sense of intricate information for robotic applications.

Master computer vision techniques for robotic perception. Learn image processing, object detection, and visual navigation for autonomous systems.

Discover the innovative realm of Generative AI, in which machines are taught to independently produce fresh content, art, and concepts for robotic applications.

Extend Generative AI into Agentic systems for robotics — agents that plan tasks, call tools and sensors, and coordinate multi-step robot behaviours with evaluation and safety loops.

Master ROS for building complex robotic systems. Learn to integrate sensors, actuators, and AI algorithms into unified robotic applications.

Build and validate robots in high-fidelity simulation with NVIDIA Isaac Sim — synthetic environments, sensor simulation, ROS 2 integration and sim-to-real workflows before physical deployment.

Master edge AI development on NVIDIA Jetson platforms. Learn to deploy deep learning models for real-time robotic applications with optimized performance.

Earn industry-recognized NVIDIA certification by mastering edge AI development on Jetson platforms. This certification validates your expertise in deploying AI models on edge devices.

Demonstrate your abilities by putting them into practice. Engage in a practical, real-life project to exhibit your understanding of the course material, incorporating multiple hardware platforms including NVIDIA Jetson for edge AI deployment.

Enhance your career path by acquiring knowledge, expertise, and approaches to progress in the evolving industries of AI and Robotics.