AI Architecture
Master core concepts of artificial intelligence and neural networks.
Practical Development
Hands-on experience with AI development through real-world projects.
Machine Learning
Learn to implement and train advanced machine learning models.
Industry Applications
Explore real-world applications and industry-standard AI practices.
Program Structure
In the first semester, students are introduced to the fundamentals of AI and robotics, focusing on core principles and concepts. This includes hands-on training in graphical engineering design, where they learn to create and manipulate 2D and 3D graphics. Simultaneously, they build a strong foundation in Python programming, a crucial skill for AI and robotics applications.
Introduction to Robotics
Fundamentals of robotics systems and architectures
Python Programming
Core programming concepts with Python
Graphical Engineering Design
2D and 3D design for robotics applications
AI Fundamentals
Basic concepts and principles of artificial intelligence
In the second semester, the program delves into more advanced topics. Machine learning takes center stage, with students studying various algorithms and their applications in robotics and AI. Students also explore the Robot Operating System (ROS), learning to develop, simulate, and control robotic applications. Advanced Robotics Projects enable students to work on real-world projects and apply their knowledge.
Machine Learning
Algorithms and applications in robotics
Robot Operating System (ROS)
Development and control of robotic applications
Advanced Robotics Projects
Capstone project with real-world applications
AI Ethics & Applications
Ethical considerations and real-world use cases
48
Weeks Program
12
Training Phases
100%
Placement Assistance
Live
Industry Projects
About the Program
Diploma in AI & Robotics
Build intelligent robots. Begin your journey in AI, Robotics & Automation.
The Diploma in Artificial Intelligence & Robotics is a one-year, industry-focused program designed to develop strong skills in AI, Machine Learning, Data Science, Embedded Systems, Industrial Robotics and 3D Designing. The curriculum covers Electronics, C++, Python, ROS (Robot Operating System) and Industrial Robotics, with hands-on training in designing, programming and building intelligent robotic systems.
The program also introduces modern AI and robotics technologies — GPU-accelerated computing, edge AI, computer vision and real-time AI model deployment. Students gain practical exposure through live projects and internships, supported by expert mentorship and 100% placement assistance.
Why Choose This Program?
Learn What Teams Need
Job-oriented training in AI, Robotics & Automation.
AI + Robotics Together
Build smart robots, not just theory.
Modern Tech Exposure
Hands-on with GPU computing, edge AI & computer vision.
Real Projects & Internship
Work on live industry projects with real deliverables.
Career & Placement Support
Expert mentors plus 100% placement assistance.
Strong Technical Foundation
Master Python, C++, Electronics & ROS.
Learning Pathway
Roadmap & Syllabus
12 phases, taught with hands-on labs and projects.
Phase 1 · Weeks 1–4 Electronics Fundamentals
- Electrical quantities: voltage, current, resistance, power, energy
- Basic circuit components, symbols and circuit element types
- Ohm’s Law and applications
- Series and parallel resistive circuits, voltage & current division
- Kirchhoff’s Current Law (KCL) and Voltage Law (KVL)
- Introduction to transistors and the IC 555 timer
Phase 2 · Weeks 5–8 Digital Electronics & PCB
- Energy band theory; conductors, insulators and semiconductors
- Intrinsic and extrinsic semiconductors, PN junction and V–I characteristics
- Zener diode and applications
- Number systems, logic gates and universal gates
- Boolean algebra laws, half adder and full adder
- PCB types, layout preparation, etching, soldering & desoldering
Phase 3 · Weeks 9–12 C++ Programming (Core Programming Skill)
- Program structure, keywords, variables, data types and operators
- Conditional statements, loops, switch–case and ternary operator
- Functions and recursion
- Arrays, strings, pointers and references
- Dynamic memory management, structures and enumerations
- Object-Oriented Programming: classes, objects, constructors, destructors
Phase 4 · Weeks 13–16 Embedded Systems Fundamentals
- Introduction to embedded systems and applications
- Microcontroller vs microprocessor; types and features
- ARM and AVR architecture overview
- Arduino platform, architecture and pin configuration
- Digital and analog I/O concepts
- Arduino IDE and basic programming
Phase 5 · Weeks 17–20 Sensors, Actuators & Hardware Control
- Sensor and actuator fundamentals
- IR, ultrasonic, DHT11, flame, PIR and touch sensors
- Joystick, water level, soil moisture, rain drop and MQ gas sensors
- Servo motors, pumps, buzzers, LED matrix and OLED displays
- LCD with I2C and HC-05 Bluetooth module
- Hardware testing and debugging
Phase 6 · Weeks 21–24 RTOS, Communication & IoT
- RTOS fundamentals, task management and scheduling
- Inter-task communication, RTOS timers and memory management
- UART, SPI, I2C and CAN protocols
- Wi-Fi communication using ESP8266 & ESP32
- IoT fundamentals, Blynk integration, device control & monitoring
- OTA updates, Ethernet and IP module basics
Phase 7 · Weeks 25–28 Python Programming (Core Skill)
- Python syntax, data types, operators and control flow
- Functions, modules and modular programming
- Data structures: lists, tuples, sets and dictionaries
- File handling and exception handling
- Object-Oriented Programming in Python
- Automation scripting for hardware and data tasks
Phase 8 · Weeks 29–32 Data Handling & Visualization
- NumPy arrays: creation, indexing, slicing and reshaping
- Mathematical operations using NumPy
- Pandas series and dataframes; reading CSV and Excel datasets
- Data manipulation, cleaning and analysis
- Matplotlib: line plots, bar charts, scatter and histogram plots
- Presenting insights through graphs and dashboards
Phase 9 · Weeks 33–36 Artificial Intelligence & Machine Learning
- AI, Machine Learning and Deep Learning concepts
- Supervised learning: regression and classification
- Unsupervised learning and clustering
- Feature engineering and data preprocessing
- Model training, evaluation and performance metrics
- Applied AI mini projects
Phase 10 · Weeks 37–40 Deep Learning, Computer Vision & NLP
- Neural networks, activation and loss functions
- CNNs and transfer learning
- Computer vision with OpenCV: image processing and object detection
- Natural Language Processing fundamentals
- Generative AI tools and applications
- Real-time AI model deployment
Phase 11 · Weeks 41–44 Industrial Boards & Vision Systems
- STM32 and industrial-grade controller boards
- Raspberry Pi for robotics applications
- Edge AI platforms for robotics
- GPU-accelerated computing fundamentals
- Industrial machine vision pipelines
- Camera interfacing and calibration
Phase 12 · Weeks 45–48 ROS 2, 3D Designing & Projects
- ROS 2 architecture, nodes, topics and services
- Robot modeling and simulation
- Industrial robotics programming
- 3D modeling and engineering graphics for prototyping
- Industry-oriented main project
- Portfolio building and placement preparation
Skills You Will Gain
Electronics & Hardware
- Strong fundamentals in basic electronics, circuit analysis, semiconductors, transistors and ICs
- Hands-on experience in PCB designing, soldering, testing and troubleshooting
- Practical understanding of sensors, actuators and electronic components
Programming Skills (C++ & Python)
- Solid foundation in C++ and Object-Oriented Programming
- Efficient programs using functions, arrays, pointers and memory management
- Strong command over Python for automation, data handling and AI applications
Data Analysis & Visualization
- Hands-on experience with NumPy, Pandas and Matplotlib
- Skills to analyze, clean and visualize real-world datasets
- Ability to represent data using graphs, charts and plots
Embedded Systems & IoT
- Practical knowledge of Arduino, STM32, ARM, AVR and Raspberry Pi
- Sensor interfacing and hardware control using embedded C and Python
- RTOS, communication protocols (UART, SPI, I2C, CAN) and IoT platforms
- Building real-time IoT and automation projects
Artificial Intelligence & Machine Learning
- Clear understanding of AI, Machine Learning and Deep Learning concepts
- Hands-on with regression, classification, clustering and model evaluation
- Exposure to computer vision, NLP and Generative AI tools
Design, Projects & Career Skills
- 3D modeling and engineering graphics for prototyping
- Mini projects and industry-oriented main projects
- Job-ready skills aligned with AI, Robotics, Embedded & Automation careers
Career Paths
Entry-Level & Technician Roles
- AI Technician / AI Operator
- Robotics Technician
- Embedded Systems Technician
- IoT Technician
- Automation & Control Technician
- Electronics & Hardware Support Engineer
Programming & Development Roles
- Python Developer (Junior Level)
- C++ Programmer
- Embedded Software Developer
- IoT Application Developer
- ROS Developer (Junior Level)
Design, Prototyping & Innovation Roles
- Prototype Design Engineer
- Product Development Engineer
- Robotics Prototype Engineer
- 3D Design & Prototyping Assistant
Artificial Intelligence & Data Roles
- AI Support Engineer
- Machine Learning Assistant
- Computer Vision Assistant
- Data Analysis Executive
- AI Lab Assistant / Research Assistant
Robotics & Automation Roles
- Robotics Engineer (Junior Level)
- ROS Engineer
- Mobile Robot Engineer
- Industrial Robot Programmer
- Automation Engineer
Embedded, IoT & Industrial Board Roles
- Embedded Systems Engineer
- STM32 / Arduino Developer
- Raspberry Pi Developer
- Industrial IoT Engineer
- Smart Device Developer