Program Overview

Introduction to the Master's in Robotics Program

The Master's in Robotics program at Purdue University is designed to provide students with a comprehensive education in robotics, covering topics such as applied mathematics, autonomy, and internet of things. The program requires 30 credit hours and offers a wide range of flexibility in course options.

Program Requirements

The program consists of four main components:

• Required Core Courses: 9 credit hours, with students selecting one course from each of the three groups: Applied Mathematics, Autonomy, and Internet of Things.
• Required Major Courses: 9 credit hours, with students selecting three courses from a list of options.
• Required Professional Skills Courses: 9 credit hours, with students selecting three courses from a list of options.
• Required Elective Course: 3 credit hours, with students selecting one course from a list of options.

Applied Mathematics

The Applied Mathematics group offers the following courses:

• MA 51100: Linear Algebra (3 credits)
• MA 52700: Advanced Mathematics for Engineers and Physicists I (3 credits)
• MA 52800: Advanced Mathematics for Engineers and Physicists II (3 credits)
• ME 58100: Numerical Methods in Mechanical Engineering (3 credits)
• STAT 51100: Statistical Methods (3 credits)
• STAT 51200: Applied Regression Analysis (3 credits)
• STAT 51400: Design of Experiments (3 credits)

Autonomy

The Autonomy group offers the following courses:

• AAE 56100: Introduction to Convex Optimization (3 credits)
• AAE 56400: Systems Analysis and Synthesis (3 credits)
• AAE 56800: Applied Optimal Control and Estimation (3 credits)
• AAE 59000: Multi-Agent Autonomy and Control (3 credits)
• AAE 66600: Nonlinear Dynamics Systems and Control (3 credits)
• ECE 50024: Machine Learning (3 credits)
• ECE 57000: Artificial Intelligence (3 credits)
• ECE 59500: Introduction to Deep Learning (3 credits)
• ECE 59500: Reinforcement Learning Theory (3 credits)

Internet of Things

The Internet of Things group offers the following courses:

• CE 56401: Data Science for Smart Cities (3 credits)
• CE 56601: Network Models for Connected and Autonomous Vehicles (3 credits)
• CHE 55400: Smart Manufacturing in the Process Industries (3 credits)
• ECE 50836: Intro to Data Mining (3 credits)
• ECE 50863: Computer Network Systems (3 credits)
• ECE 54700: Introduction to Computer Communication Networks (3 credits)
• ECE 55900: MOS VLSI Design (3 credits)
• ECE 56800: Embedded Systems (3 credits)
• ECE 59500: Computer Vision for Embedded Systems (3 credits)
• ECE 60684: Advanced IoT Design and Applications (3 credits)
• ECE 69500: System-on-Chip Design (3 credits)

Required Major Courses

The Required Major Courses offer the following options:

• AAE 56100: Introduction to Convex Optimization (3 credits)
• AAE 56400: Systems Analysis and Synthesis (3 credits)
• AAE 56800: Applied Optimal Control and Estimation (3 credits)
• AAE 59000: Multi-Agent Autonomy and Control (3 credits)
• AAE 66600: Nonlinear Dynamics Systems and Control (3 credits)
• ECE 56900: Introduction to Robotics Systems (3 credits)
• ECE 58000: Optimization Methods for Systems and Control (3 credits)
• ECE 59500: Reinforcement Learning Theory (3 credits)
• ECE 60200: Lumped System Theory (3 credits)
• ECE 67500: Introduction to Analysis of Non-Linear Systems (3 credits)
• ECE 68000: Modern Automatic Control (3 credits)
• IE 57400: Industrial Robotics and Flexible Assembly (3 credits)
• ME 57500: Theory and Design of Control Systems (3 credits)
• ME 57800: Digital Control (3 credits)

Required Professional Skills Courses

The Required Professional Skills Courses offer the following options:

• AAE 56100: Introduction to Convex Optimization (3 credits)
• AAE 56800: Applied Optimal Control and Estimation (3 credits)
• AAE 59000: Multi-Agent Autonomy and Control (3 credits)
• AAE 66600: Nonlinear Dynamics Systems and Control (3 credits)
• ECE 59500: Reinforcement Learning Theory (3 credits)

Required Elective Course

The Required Elective Course offers the following options:

• AAE 56100: Introduction to Optimization (3 credits)
• AAE 56400: Systems Analysis and Synthesis (3 credits)
• AAE 56800: Applied Optimal Control and Estimation (3 credits)
• AAE 59000: Multi-Agent Autonomy and Control (3 credits)
• AAE 66600: Nonlinear Dynamics Systems and Control (3 credits)
• CE 56401: Data Science for Smart Cities (3 credits)
• CE 56601: Network Models for Connected and Autonomous Vehicles (3 credits)
• CHE 55400: Smart Manufacturing in the Process Industries (3 credits)
• ECE 50024: Machine Learning (3 credits)
• ECE 50836: Intro to Data Mining (3 credits)
• ECE 50863: Computer Network Systems (3 credits)
• ECE 54700: Introduction to Computer Communication Networks (3 credits)
• ECE 55900: MOS VLSI Design (3 credits)
• ECE 56800: Embedded Systems (3 credits)
• ECE 56900: Introduction to Robotic Systems (3 credits)
• ECE 57000: Artificial Intelligence (3 credits)
• ECE 58000: Optimization Methods for Systems and Control (3 credits)
• ECE 59500: Game Theory (3 credits)
• ECE 59500: Introduction to Deep Learning (3 credits)
• ECE 59500: Reinforcement Learning Theory (3 credits)
• ECE 59500: Computer Vision for Embedded Systems (3 credits)
• ECE 60200: Lumped System Theory (3 credits)
• ECE 60584: Advanced IoT Design and Applications (3 credits)
• ECE 67500: Introduction to Analysis of Non-Linear Systems (3 credits)
• ECE 68000: Modern Automatic Control (3 credits)
• ECE 69500: System-on-Chip Design (3 credits)
• IE 57400: Industrial Robotics and Flexible Assembly (3 credits)
• ME 57500: Theory and Design of Control Systems (3 credits)
• ME 57800: Digital Control (3 credits)

Creating Your Plan of Study

After beginning studies at Purdue, an academic advisor will help create an Electronic Plan of Study (EPOS) to best fit educational needs and career goals. The student is ultimately responsible for knowing and completing all degree requirements.