Internet of Things MSIOT
Degree Awarded: Master of Science in Internet of Things (MSIOT)
Minimum Required Credits: 30.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 14.1001
Standard Occupational Classification (SOC) code: 15-1143
About the Program
Drexel's MS in Internet of Things (IoT) program prepares students for the future of interconnected devices and smart technologies. Students gain expertise in:
- Core concepts and technologies: Wireless communications, networks, sensors, actuators, data analytics, and embedded systems.
- Technical skills: Designing, developing, testing, and debugging IoT systems through hands-on engineering practice.
- Analytical and problem-solving competencies: Applying quantitative and computational methods to address complex IoT applications in domains such as healthcare, energy, mobility, and environmental monitoring.
- Professional attributes: Critical thinking, innovation, and ethical decision-making in deploying secure and efficient IoT solutions that address societal needs.
The program offers a comprehensive and flexible curriculum that can be tailored to individual goals through consultation with an academic advisor. Students complete 30 credits, combining core coursework with opportunities for specialization in key areas of IoT.
Students may engage in up to 6 elective credits of faculty-supervised research. Research and project-based learning foster creativity, problem-solving, and innovation through direct engagement with current challenges in the field.
Full-time on-campus students are eligible for the Graduate Co-op Program, a distinctive Drexel experience that integrates academic learning with a 6-month, full-time professional placement. This hands-on opportunity allows students to apply classroom knowledge in practical settings and gain meaningful industry experience before graduation.
Graduates are equipped for diverse career and research opportunities in areas such as biomedical devices, intelligent buildings, smart power grids, intelligent transportation, and environmental sensing.
Career pathways: Positions include IoT systems engineer, network architect, embedded systems developer, data analytics engineer, and smart infrastructure specialist.
Further education: The program provides an excellent foundation for pursuing doctoral studies in engineering or related fields.
Drexel's MS in IoT program stands out for its integration of technical depth, applied learning, and industry relevance.
Drexel's cooperative education model and opportunities for faculty-led research ensure students gain practical experience alongside academic knowledge.
Individualized advising allows students to tailor their curriculum to match specific professional or research goals.
The program's emphasis on real-world problem-solving across scales—from personal devices to smart cities—positions Drexel graduates at the forefront of technological advancement in an increasingly connected world.
The MS in IoT equips graduates to lead innovation in the connected future through technical mastery, creativity, and hands-on experience.
Additional Information
For more information about this program, please contact the School of Engineering
Admission Requirements
Applicants must meet the general requirements for graduate admission, which include at least a 3.0 GPA for the last two years of undergraduate study and a bachelor's degree in computer engineering, computer science, or electrical engineering. Students holding degrees in other engineering and science disciplines with appropriate coursework or training will also be considered.
The GRE general test is optional for all applicants. TOEFL, IELTS, PTE, or Duolingo is required if the language of instruction of your previous degree was not English.
Degree Requirements
| Core/Foundational Courses | ||
| Select four of the following courses: | 12.0 | |
| Computer Networking | ||
| Digital Systems Design | ||
| Fault-Tolerant Systems | ||
| Wireless Communications | ||
| Software-Defined Radio | ||
| Subject-Area Focused Courses | ||
| Select one of the following courses: | 3.0 | |
| Computer Hardware Design | ||
| Probability and Random Variables | ||
| Select three of the following courses: | 9.0 | |
| Machine Learning and Artificial Intelligence | ||
| Introduction to Radar | ||
| Secure Networking | ||
| Parallel Programming | ||
| Information Theory and Coding | ||
| Optional Thesis | ||
| Select one of the following options: | 6.0 | |
| Non-Thesis | ||
Select any ECE (Electrical and Computer Engineering) 5000-7997 level course 1 | ||
| Thesis | ||
| Master's Thesis | ||
| Optional Co-op Experience | ||
| Co-op is an option for this degree for full-time on-campus students. Students choosing this option will be required to complete COOP 5000 as preparation for their co-op experience. | 0.0 | |
| Total Credits | 30.0 | |
- 1
Elective courses from other subject codes may be taken with department approval.
Program Learning Outcomes
- Apply knowledge of mathematics, science, and engineering
- Design and conduct experiments, as well as to analyze and interpret data
- Design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
- Function on multidisciplinary teams
- Identify, formulate, and solve engineering problems
- Understand professional and ethical responsibility
- Communicate effectively
- Understand the impact of engineering solutions in a global, economic, environmental, and societal context
- Recognize the need for, and an ability to engage in life-long learning
- Attain knowledge of contemporary issues
- Use the techniques, skills, and modern engineering tools necessary for engineering practice