Carnegie Mellon University


The area of concentration provides an opportunity to build upon core course knowledge and to develop expertise in a specific area.  Students choose a focus area (24 units) from the following concentration areas:

  • Data Analytics
  • Politics and Strategy
  • Information Security
  • Software and Networked Systems

Students can further explore their area of concentration, or pursue topics outside of it, through free electives. At least one course (12 units) must be taken from outside the student's focus area.

Students may choose courses for their area of concentration and free electives from amongst the following:

Data Analytics

This concentration focuses on the mastery of techniques such as: machine learning, social network analysis, large-scale data reduction and filtering and the application of these techniques to the development of strategies to advance the organizational mission.

  • 05-820 Social Web (spring)
  • 10-605 Machine Learning Large Data Sets (fall) 
  • 10-606 Mathematical Foundations for Machine Learning (fall 1st half mini/summer 1st half mini) 
  • 10-607 Computational Foundations for Machine Learning (fall 2nd half mini/summer 2nd half mini) 
  • 10-703 Deep Reinforcement Learning and Control (fall) 
  • 10-707 Topics in Deep Learning (spring) 
  • 10-708 Probabilistic Graphics Models (fall/spring) 
  • 10-613/10-713 Machine Learning Ethics and Society (fall, prereq 10-601 or 10-701) 
  • 10-714 Deep Learning Systems: Algorithms & Implementation (fall, prereq 15-513 AND 10-601/701) 
  • 10-718 Machine Learning in Practice (fall/spring)
  • 11-611/711 Natural Language Processing (fall/spring) 
  • 11-641 Machine Learning for Text Mining (fall/spring) 
  • 11-642 Search Engines (fall/spring) 
  • 11-676 Big Data Analytics (fall) 
  • 11-731 Machine Translation and Sequence-to-Sequence Models (fall) 
  • 11-747 Neural Networks for NLP (spring) 
  • 11-777 Multimodal Machine Learning (fall/spring, prereq 10-601 or 10-701) 

  • 11-785 Introduction to Deep Learning (fall/spring) 
  • 15-688 Practical Data Science (spring) 
  • 15-780 Graduate Artificial Intelligence (spring) 
  • 16-735 Ethics and Robotics (spring)
  • 16-824 Visual Learning and Recognition (fall/spring) 
  • 17-634 Applied Machine Learning (spring 1st half mini) 
  • 17-644 Applied Deep Learning (spring 2nd half mini) 
  • 17-645/17-745/11-695 Machine Learning in Production/AI Engineering (fall/spring)
  • 17-685/17-801 Dynamic Network Analysis (spring) 

Politics and Strategy (PS)

This concentration focuses on developing a sound reasoning framework and the critical thinking skills necessary to develop effective policies and strategies for those decision makers who will shape the future of their technology intensive organizations.

Information Security (IS)

This concentration focuses on developing an understanding of cyber-attacks and equipping students to address the threats and consequences of cyber-attacks through sound information security strategies and policies.

  • 05-836 Usable Privacy and Security (spring) 

  • 14-735 Secure Coding (fall/spring) 
  • 14-761 Applied Information Assurance (fall/spring) 
  • 14-814/18-637 Wireless Security (spring, prerequisites 18-631/14-741 or 18-730 AND 18-730 and 18-741 or 15-641) 
  • 14-817 Cyber Risk Modeling (spring) 
  • 14-819 Introduction to Software Reverse-Engineering (spring, prerequisite 15-513) 
  • 14-822 Host Based Forensics (spring, co-requisite 14-761) 
  • 14-823 Network Forensics (fall) 
  • 18-731 Network Security (spring, prerequisite 18-631/14-741 or 18-730) 
  • 18-732 Secure Software Systems (spring, prerequisite 18-631/14-741 or 18-730) 
  • 18-733 Applied Cryptography (spring, prerequisite 18-631/14-741 or 18-730) 
  • 18-734 Foundation of Privacy (fall) 
  • 84-683 Cyber Policy as National Policy
  • 95-810 Blockchain Fundamentals (fall 2nd half mini/summer) 
  • 95-855 Network Traffic Analysis (fall 2nd half mini/summer 2nd half mini) 
  • 95-884 Network Defenses (fall 1st half mini/summer 1st half mini) 

Software and Networked Systems (SN)

This concentration focuses on developing an understanding of systems and software comprising organizational information infrastructure assets to better manage their design, development, and procurement of systems and service, through sound strategies and policies.

  • 11-642 Search Engines (fall/spring)
  • 14-740 Fundamentals of Telecommunication Networks (fall/spring)
  • 14-848 Cloud Infrastructure: Design, Analysis and Implementation (fall)
  • 15-618 Parallel Computer Architecture and Programming (fall/spring)
  • 15-619/15-719/18-709 Cloud Computing (fall/spring)/Advanced Cloud Computing (spring)
  • 15-746 Storage Systems (fall, prerequisite 15-513)
  • 16-720 Computer Vision (fall/spring)
  • 16-722 Sensing and Sensors (fall)
  • 16-761 Mobile Robots (spring)
  • 16-782 Planning and Decision-making in Robotics (fall)
  • 17-610 Risk Management for Software Intensive Projects (spring 2nd half mini/summer 2nd half mini)
  • 17-611 Statistics for Decision Making (fall 1st half mini/summer 1st half mini)


  • 17-626 Requirements for Information Systems (fall 2nd half mini)


  • 17-627 Requirements for Embedded Systems (fall 2nd half mini)
  • 17-614 Formal Methods (fall 1st half mini)


  • 17-622 Agile Methods (fall 2nd half mini)


  • 17-624 Advanced Formal Methods (fall 2nd half mini)
  • 17-616 DevOps: Engineering for Deployment and Operations (fall)
  • 17-623 Quality Assurance (fall 2nd half mini)
  • 17-642 Software Management Theory (spring 2nd half mini) AND 17-643 Quality Management (spring 2nd half mini)
  • 17-645/17-745/11-695 Software Engineering for AI Enabled Systems (fall/spring/summer)
  • 17-648 Sensor Based Systems (spring 2nd half mini, prerequisite 17-636)
  • 17-652 Innovation and Entrepreneurship in Technology (summer 2nd half mini)
  • 17-681 Java for Application Programmers (fall 1st half mini/spring 1st half mini)


  • 17-683 Data Structures for Application Programmers (fall 2nd half mini/spring 2nd half mini)
  • 18-648 Embedded System Software Engineering (fall, prerequisite 15-513)
  • 18-648 Embedded Real Time Systems (fall, prerequisite 15-513)
  • 18-756 Packet Switching & Computer Networks (fall)
  • 18-843 Mobile and Pervasive Computing (fall/spring, prerequisite 15-513)

Please Note: The courses listed on this page are not an exhaustive list. Additional courses may be appropriate. MITS students are encouraged to discuss their course selections with the academic advisor.