Carnegie Mellon University

Area of Concentration

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

To be successful, tomorrow’s leaders in Information Dominance must be proficient in extracting knowledge from large data systems. Such extraction requires mastery in techniques such as machine learning, social network analysis, and large-scale data reduction and filtering.

      • 08-741 Data Science (fall)
      • 10-605 Machine Learning Large Data Sets (fall)
      • 10-703 Deep Reinforcement Learning and Control (fall)
      • 10-707 Topics in Deep Learning (spring)
      • 10-708 Probabilistic Graphics Models (spring)
      • 11-611 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)
      • 11-785 Introduction to Deep Learning (fall/spring)
      • 15-688 Practical Data Science (spring)
      • 15-780 Graduate Artificial Intelligence (spring)
      • 16-824 Visual Learning and Recognition (spring)
      • 17-634 Applied Machine Learning (spring 1st half mini)
      • 17-644 Applied Deep Learning (spring 2nd half mini)

Politics and Strategy (PS)

      • 84-619 U.S. Foreign Policy and Interventions in World Affairs (spring)
      • 84-622 Nonviolent Conflict and Revolution (spring)
      • 84-625 Contemporary American Foreign Policy (spring)
      • 84-627 Repression and Control in Dictatorships
      • 84-661 A4 Leaders and International Security
      • 84-662 Diplomacy and Statecraft (fall)
      • 84-669 Decision Science for International Relations (fall)
      • 84-670 Global Nuclear Politics (fall)
      • 84-672 Space and National Security (spring)
      • 84-673 Emerging Technologies and the Law (spring)
      • 84-680 Grand Strategy in the United States (fall)
      • 84-686 The Privatization of Force (fall)
      • 84-688 Concepts of War and Cyber War (fall 2nd half mini)
      • 84-689 Terrorism and Insurgency (spring)
      • 84-690 Social Media, Technology, and Conflict (spring)
      • 84-720 International Security Graduate Seminar (spring)
      • 84-736 Analytical Social Science and National Security (fall 1st half mini)
      • 88-602 Behavioral Decision Making (spring)
      • 88-605 Risk Perception and Communication (spring)
      • 88-635 Decision Science & Policy (spring)
      • 19-701 Intro to the Theory & Practice of Policy (fall)
      • 19-711 Global Competitiveness: Firms, Nations, and Technological Change (fall)
      • 19-713 Policies of Wireless Systems & the Internet (fall)
      • 19-722 Telecommunications, Technology Policy & Management (spring)

Information Security (IS)

      • 05-836/08-734 Usable Privacy and Security (spring)
      • 14-735 Secure coding (spring)
      • 14-761 Applied Information Assurance (spring)
      • 14-814/18-637 Wireless Security (spring, prerequisites 18-631 or 18-730 AND 18-741 or 15-641)
      • 14-819 Introduction to Software Reverse-Engineering (spring, prerequisite 15-513)
      • 14-822 Host Based Forensics (spring)
      • 14-823 Network Forensics (fall)
      • 18-730 Introduction to Computer Security (fall, cannot take both 18-730 AND 18-631)
      • 18-731 Network Security (spring, prerequisite 18-631 or 18-730)
      • 18-732 Secure Software Systems (spring, prerequisite 18-631 or 18-730)
      • 18-733 Applied Cryptography (spring, prerequisite 18-631 or 18-730)
      • 18-734 Foundation of Privacy (fall)

Software and Networked Systems (SN)

      • 11-642 Search Engines (fall/spring)
      • 14-740 Fundamentals of Telecommunication Networks (spring)
      • 15-618 Parallel Computer Architecture and Programming (fall/spring)
      • 15-619 Cloud Computing (fall/spring)
      • 16-720 Computer Vision (fall/spring)
      • 16-722 Sensing and Sensors (fall)
      • 16-761 Mobile Robot Design (spring)
      • 17-610 Risk Management for Software Intensive Projects (summer 2nd half mini)
      • 17-611 Business & Marketing Strategy (fall 1st half mini)

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

OR    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: Modern Deployment (fall)
      • 17-646 DevOps and Continuous Integration (spring 2nd half mini)
      • 17-632 Software Project Management (spring 1st half mini)
      • 17-642 Software Management Theory (spring 2nd half mini)
      • 17-636 Distributed Systems Fundamentals (spring 1st half mini)
      • 17-648 Sensor-based Systems (spring 2nd half mini)
      • 17-645 Software Engineering for AI Enabled Systems (fall)
      • 17-634 Applied Machine Learning (spring 1st half mini)
      • 17-644 Applied Deep Learning (spring 2nd half mini)
      • 17-623 Quality Assurance (fall 2nd half mini)
      • 17-643 Quality Management (spring 2nd half mini)
      • 17-647 Data-intensive and Scalable Systems (spring 2nd half mini)
      • 17-681 Java for Application Programmers (fall/spring)
      • 17-683 Data Structures for Application Programmers (fall/spring)
      • 18-349 Intro to Embedded Real Time Systems (spring)
      • 18-756 Packet Switching & Computer Networks (fall)
      • 18-843 Mobile and Pervasive Computing (fall)

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.