Program Overview

Introduction to the Master's in Internet of Things Program

The Master's in Internet of Things (IoT) program at Purdue University is designed to provide students with a comprehensive understanding of the principles and applications of IoT. The program requires 30 credit hours and is structured to offer flexibility in course options.

Program Structure

The program consists of four main components:

• Required Core Courses: 9 credit hours
• Required Major Courses: 9 credit hours
• Required Professional Skills Courses: 9 credit hours
• Required Elective Course: 3 credit hours

Required Core Courses

Students must select one course from each of the three following groups:

• Applied Mathematics:
  • 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:
  • 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)
• Robotics:
  • 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 Major Courses

Students must select 3 of 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 Professional Skills Courses

Students must select 3 of 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 56800: Embedded Systems (3 credits)
• ECE 59500: Computer Vision for Embedded Systems (3 credits)
• ECE 60684: Advanced IoT Design and Applications (3 credits)

Required Elective Course

Students must select 1 of the following courses:

• 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 60684: 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

The MSE/MS master's program offers a wide range of flexibility in course options. 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.