Intelligence Analysis (IA)

This course presents a holistic understanding of intelligence analysis: its core definition, domains where it is practiced, how it is done by both individuals and teams, relevant reasoning and technological methods, the significance of communication skills, the broader context that shapes the process, and relevant principles of professional ethics and legal compliance. This course is required for students majoring in intelligence analysis and is recommended for those considering the major.

This course provides a knowledge-based introduction to the domains where intelligence analysts work. These domains include, but are not limited to: national security, military, homeland security, law enforcement, competitive, private sector security and technical specialties such as geospatial and cyber. The course also introduces the larger topics in the field, the security problems and - to a lesser extent - what an intelligence analyst in each field does.

Intelligence analysis is a complex, dynamic process that includes determining the intelligence needs, data collection, pre-processing, analysis and production of the customer's product. This is an introduction to the history, structure and practices of the national security intelligence community (IC). The course is team-oriented, project-based and grounded in the relevant legal and ethical context.

Students develop broad technical competencies of current and future technology applications, such as databases, spreadsheets and Internet-of-things. They explore technical-socio-ethical aspects of the cyber world. This hands-on and team-based course supports development of working technical knowledge for accessing, evaluating, modeling and analyzing information and data for problem solving. Students develop a systematic appreciation of computing, network and cyber security.

The course introduces students to data analysis through computer programming. The course will focus on key elements from data science that are critical to the intelligence analyst such as manipulating, processing, cleaning and crunching data. The course will serve as a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This course will introduce the Python language and libraries students need to effectively solve a broad set of data analysis problems. The course is hands-on and places emphasis on practical case studies with a broad scope of techniques useful for the data analyst.

In this course, students will learn how intelligence analysts can produce assessments using a research design framework and communicate those assessments effectively in writing. This includes how intelligence analysts develop research (intelligence) questions, conduct research, evaluate sources, choose methodologies, develop assessments and present those assessments in the form of an argument with an emphasis on precision, clarity and brevity in the written format.

Examines hypothesis testing in national. military, counter and competitive intelligence. By comparing alternate theories in terms of their explanatory power and predictive success, students will learn the most relevant methods for integrating facts into unified theories, assessing theories, and properly qualifying and reevaluating theories to compensate for risk and uncertainty.

This course will examine projects of interest to lower-division students in intelligence analysis not otherwise offered in regular course offerings. They are offered only with the approval of the program director and they may be repeated when course content changes. Students should consult with the instructor prior to enrolling in the course.

This course will focus on important issues in the theory and practice of intelligence analysis. Students will learn about intelligence analysis by examining its purpose, history, methods, processes, context of existing challenges and recommendations for improvement.

Examines causal analysis in national, military, counter- and competitive intelligence. By assessing a factor's amount and kind of efficacy, students will learn the most reliable methods for distinguishing between relevant/irrelevant events and factors, identifying and excluding "pseudo-causes," and anticipating higher order effects of a causal process.

Examines counterfactual reasoning in national, military, counter- and competitive intelligence. By analyzing alternate scenarios and their consequences, students will learn the most relevant methods for employing creative thinking in generating, developing, and assessing possibilities; substantiating "after-action" reports, and structuring futures analysis.

Examines strategy assessment in national, military, counter, and competitive intelligence. By applying probabilities and goals to potential threats and opportunities (short and long-term), students will learn the most relevant methods for formulating and evaluating possible courses of action, and projecting and explaining actions by assessing an agent's strategic interests and circumstances.

Data mining is the nontrivial extraction of previously unknown and potential useful information from (large) data sets to help explain current behaviors and anticipate future outcomes. Students will apply data mining and knowledge discovery methods to data sets from business, industry and government. The course is team oriented, project based and grounded in the relevant legal and ethical context.

System dynamics analysis is a perspective and a set of conceptual and computing tools to help us understand the structure and dynamics of complex systems. This course will apply system dynamics analysis to complex systems (problems) that involve the interplay of physical and social-political factors. The course is team-oriented, project-based and grounded in the relevant legal and ethical context.

Data visualization presents laboratory or simulation data or the results from sensors out in the field in a way that aids reasoning about and hypothesis building in complex data sets. This course will apply data visualization technologies and tools to timely data sets from business, industry and government. The course is team oriented, project based and grounded in the relevant legal and ethical context.

This course introduces artificial intelligence, machine learning and generative AI, focusing on their applications in intelligence analysis. Students will learn to build, train and deploy machine learning models while exploring the latest generative AI techniques, such as prompt engineering, vector databases, retrieval-augmented generation (RAG) and diffusion models. These techniques will be applied to analyze social media data, text messages and images, addressing real-world intelligence challenges. Experience with Python is required.

This course will address key concepts in the study of terrorism, to include definitions, history, justifications, explanations and strategies. It will also address the effectiveness of different kinds of counterterrorism strategies and policies and the role that intelligence analysis plays in the process.

This course traces apocalypticism from its ancient Jewish and Christian roots to its contemporary manifestations in religious groups around the world. Since apocalypticism is a worldview that cuts across religious traditions, the course covers a variety of religious groups. The last half of the course focuses on the complex relationships between apocalyptic thinking and religious terrorism and entails an independent research project.

Cyber intelligence is the acquisition of information to identify and analyze cyber adversaries' capabilities, intentions and activities that can be used to support proactive decision-making. Students will explore common cyber security terminology (lexicon), frameworks and methodologies used to analyze cyber security threats in organizations. Using case studies, they will collect and analyze open source information to identify and monitor evolving threats and understand how adversaries operate.

Competitive intelligence is developing actionable foresight regarding competitive dynamics that can be used to enhance the speed and quality of decision-making. This course teaches students to think and act strategically as a CI professional and to develop students' capacity to think strategically about a company, its business position, how it can gain sustainable competitive advantage and how its strategy can be implemented and executed successfully with the support of CI.

Money laundering involves masking the source of criminally derived financial proceeds so funds appear legitimate. Money laundering permeates almost every regulated market. In the global economy, contracting companies, casinos, banks and other financial institutions are required to implement specific structural arrangements to spot red flags and other concerning indicators to reduce money laundering. Students learn about anti-money laundering and counter-terrorism financing (AML/CTF), applied skills about risk assessment, illicit cash flows, and Report and Country AML/CTF Evaluation Report. Students also gain an opportunity to learn about legislative and regulatory initiatives, laws, and organizations at the micro and macro levels (regional, national and international) as they pertain to AML/CTF. Overall, students gain introductory skills on detection, preventative measures and investigating AML/CTF activities. As part of the course evaluation and to afford students practical opportunities, student will work alongside real-world clients.

Geopolitical conflicts and issues are examined. Concepts such as territoriality, nationalism, religious and ethnic struggle, environmental degradation, and freedom and justice are discussed in the context of political unrest. Significant geopolitical theories, and social and economic processes are explored.

This course will examine ethical and legal issues raised in the practice of intelligence analysis. It will draw on philosophical ethical theories and reasoning to explicate the issues addressed, and will explore the relevant constitutional and other legal constraints on the practice of intelligence analysis, particularly issues of information privacy, civil liberties and limitations on government action.

This course will focus on preparing students for developing team projects in the IA Capstone Seminar. Students will individually identify, analyze, plan and report on a feasible capstone seminar project. Students will then organize teams and develop plans to complete a subset of the most promising projects in the Capstone Seminar.

Building on the Seminar on Issues in Intelligence Analysis students will complete and present solutions for team-based intelligence community or competitive intelligence IA projects. Students will produce written and oral technical reports/briefs of their results.

This course introduces awareness, science and societal impact of weapons of mass destruction (WMD) agents. Students study the development of vaccines and therapeutic and diagnostic drugs used in the detection and treatment of these agents. The course consists of lectures and safety training sessions that introduce tactical and logistical techniques used against chemical, biological and radiological WMD.

Incident Command Systems enables incident management by integration of facilities, equipment, personnel, procedures, and communications operating in a common organizational structure. ICS is used to organize near and long-term operations for a spectrum of emergencies, small to complex incidents, natural and man-made. ICS is used by government, many private and nongovernmental organizations in 5 major functional areas: command, operations, planning, logistics, and finance and administration.

This course will examine topics of interest to upper-division students in intelligence analysis not otherwise offered in regular course offerings. They are offered only with the approval of the program director and they may be repeated when course content changes. Students should consult with the instructor prior to enrolling in the course.

Provides students with opportunities to earn credit for experiential learning as an analyst in a professional internship setting in a variety of fields where they can acquire knowledge and skills consistent with the IA program's learning objectives. Students engage in a period of employment (minimum 120 hours for 3 credits) as an analyst during which time program learning objectives must be addressed.

This is an honors thesis proposal course. It is the first of the three-course sequence intended to satisfy the requirements for the honors program as well as the Intelligence Analysis program. Students will develop a thesis proposal, including objectives, audience, literature review, timeline and deliverables. The goal of the course is for the student to develop a compelling and complete senior thesis proposal.

This is an honors thesis development course. It is the second of the three-course sequence intended to satisfy the requirements for the honors program as well as the Intelligence Analysis program. Most of the course will be jointly administered/taught with IA 440: Senior Seminar in Intelligence Analysis. In addition, students may be required to meet with the instructor to discuss progress on his or her project.

This is an honors thesis completion course. It is the third of the three-course sequence intended to satisfy the requirements for the honors program as well as the Intelligence Analysis program. Most of the course will be jointly administered/taught with IA 450, Capstone Project in Intelligence Analysis. In addition, students may be required to meet with the instructor to discuss progress on his or her project.