Every semester, the school offers special topics courses that are either irregular offerings or have not yet been approved as permanent courses. We encourage students within and outside the school to consider taking these courses, as they offer unique opportunities to explore and develop expertise outside of the standard curriculum. Below, you can find the list of special topics courses the school plans to offer next semester, complete with course descriptions, syllabi where available, and contact information for the instructor if you'd like to learn more.
In Summer and Fall 2026, the school is offering courses focused on:
- Mental Health
- Computation & Cognition
- I-O and People Analytics
- Decision Science
- Learning Science
- Human-Computer Interaction
Check out the information below for more details on each course offering! Note that the syllabi for each course are typically examples from previous semesters. The syllabi for Summer/Fall 2026 might vary from the examples provided.
All courses listed are Fall 2026 courses unless otherwise noted.
Special Topics Courses by Interest:
| Course (code) | Brain | Cognition | People | Technology | Quantitative Methods |
|---|---|---|---|---|---|
| PSYC 2803 – Intro to Counseling and Clinical Psychology [Summer] | ✓ | ✓ | |||
| PSYC 2803 – Resilience Building Strategies | ✓ | ||||
| PSYC 3803 – Programming for Brain & Behavior | ✓ | ✓ | ✓ | ✓ | |
| PSYC 3803 – Math of the Mind | ✓ | ✓ | ✓ | ✓ | |
| PSYC 4803 – AI for Cognitive Science | ✓ | ✓ | ✓ | ||
| PSYC 3803 – People Analytics | ✓ | ✓ | ✓ | ||
| PSYC 4803 – Seminar in Structured Analytical Techniques and Cognitive Modeling | ✓ | ✓ | |||
| PSYC 4803 – Psychology of Lifelong Learning | ✓ | ✓ | |||
| PSYC 4803 – Research Methods for HCI | ✓ | ✓ | ✓ |
✓ indicates the course covers that category.
Mental Health Focused Courses
PSYC 2803 - Intro to Counseling and Clinical Psychology [Summer 2026]
Instructor: Dr. Tiffiny Hughes-Troutman (tiffiny.hughes-troutman@psych.gatech.edu)
Click for example syllabus
Description:
Introduction to Clinical and Counseling Psychology will provide a broad overview of the professional issues and activities of clinical practice in the mental health field, with an emphasis on clinical and counseling psychology. This course is open to all students and is particularly suitable for those interested in or considering a career in the mental health field. Students will develop a rich understanding of clinical practice within the broader field of psychology and gain a strong grasp on available career paths at both the masters and doctoral levels. We will delve into the practical activities and practices of licensed counselors and psychologists, including clinical interviews, various forms of clinical assessment, approaches to therapy (i.e., theoretical orientations), impact of technology on practice, and subfields of clinical practice. My hope is that students will leave this class with a clear understanding of what clinical practice looks like in the "real world", both as a consumer and potential provider of mental health services.
Prerequisites: None
Note: This course is pre-approved to count toward the Minor in the Science of Mental Health and Well-Being
PSYC 2803 - Resilience Building Strategies
Instructor: Dr. Sonia Alvarez-Robinson (sonia@consulting.gatech.edu)
Click here for example syllabus
Description:
Resilience is the ability of an individual, organization, or community to survive, adapt, grow, and thrive through acute shocks and chronic stressors. This course, Resilience Building Strategies, introduces skills, strategies, and tools to prepare for, respond to, and recover from both life-altering events and daily challenges. Grounded in the foundations of personal, social, and organizational psychology, this course uses short lectures, guest presentations, gamified lessons, scenarios/case studies, small group discussions, and a final project. The goal is for every student to complete the course with a customized resilience plan to help them navigate adversity, challenges, and change in their everyday lives. This course is open to all GT students.
Prerequisites: None
Note: This course is pre-approved to count toward the Minor in the Science of Mental Health and Well-Being
Computation & Cognition Focused Courses
PSYC 3803 - Programming for Brain & Behavior
Instructor: Dr. Eunbee Kim (eunbee.kim@gatech.edu)
Click here for example syllabus
Description:
This course will give students a basic toolkit for computationally analyzing data related to brain and behavior using python and R. The course will begin with an introduction to programming in python (variables, control statements, functions) then move on to data manipulation and statistical analysis. The content will be aimed at undergraduate students in psychology, biomedical engineering, and neuroscience. No prior programming skills are required but it would help to have some background in linear algebra. Course meetings will be a combination of lectures, demonstrations, and lab assignments.
Prerequisites: MATH 1553 or similar recommended
Note: This course is pre-approved to count toward the Minor in Computation and Cognition as a Computation Elective.
PSYC 3803 - Math of the Mind
Instructor: Dr. Bob Wilson (rwilson337@gatech.edu)
Click here for example syllabus
Description:
This class offers an introduction to the world of building mathematical and computational models to understand cognitive and neural processes. The philosophy of this course is to have you actually build these models and engage with the data to (re)discover the theories for yourself. To this end you will be deriving mathematical expressions for behaviors in different experiments, building computational models to simulate neural firing, and analyzing real behavioral and neural data. In addition, you’ll have the opportunity to build your own models and experiments in a project that takes the place of the final. While computational methods can be applied to understand any aspect of Cognition, in this course we will focus on the computational modeling of decision making. By focusing on a single topic, the goal is to go deep down the modeling rabbit hole to really see how models are built, tested, and improved upon over time.
Prerequisites: None
Note: This course is pre-approved to count toward the Minor in Computation and Cognition as a Computation or Cognition Elective.
PSYC 4803 - AI for Cognitive Science
Instructor: Dr. Bob Wilson (rwilson337@gatech.edu)
Click here for example syllabus
Description:
In this class you will learn how to build, simulate, and fit computational models to behavioral data. We will focus on two types of modeling. In the first half of the class we will look at the “traditional” approach to computational modeling, building models that try to mimic cognitive computations. In the second half of the class we will investigate more modern approaches with neural networks looking at how feedforward, recurrent and LLM models can learn to reproduce human-like behavior (or not). This is very much a hands-on class and much of your time will be spent coding the models up for yourself in Python. In addition, you’ll have the opportunity to build your own models and experiments in a project that takes the place of the final.
Prerequisites: None
Note: This course is pre-approved to count toward the Minor in Computation and Cognition as a Computation Elective.
I-O & People Analytics Focused Courses
PSYC 3803 - People Analytics
Instructor: Dr. Chris Wiese (chriswiese@gatech.edu)
Click here for example syllabus
Description:
Organizations run on people, but how do we make evidence-based decisions about them? This course introduces the intersection of psychological science and applied data analytics. Students will learn to evaluate workforce metrics to solve real-world organizational challenges, focusing on hiring, employee retention, performance assessment, and workplace well-being.
Prerequisites: PSYC 1101
Decision Science Focused Courses
PSYC 4803 - Seminar in Structured Analytical Techniques and Cognitive Modeling
Instructor: Dr. Rick Thomas (rick.thomas@psych.gatech.edu)
Click here for example syllabus
Description:
This seminar focuses on how people think, make decisions, and sometimes make mistakes—especially in high-stakes, uncertain environments like intelligence analysis. You will learn structured analytic techniques (SATs) that help reduce bias and improve the quality of your reasoning, along with cognitive models that explain how judgment and decision-making actually work. The course is highly applied. Through case studies, hands-on exercises, and group discussions, you will practice using these tools to analyze complex problems, evaluate evidence, and make defensible decisions. By the end of the seminar, you will be able to apply structured methods to real-world challenges in intelligence analysis, risk assessment, and resource allocation.
Prerequisites: None
Learning Science Focused Courses
PSYC 4803 - Psychology of Lifelong Learning
Instructor: Dr. Phil Ackerman (phillip.ackerman@psych.gatech.edu)
Click here for example syllabus
Description:
The study of learning has been a fundamental topic for psychological theories and empirical research for well over 100 years. General theories of learning have been advanced and various techniques developed to identify a variety of important determinants of learning, such as individual differences in traits, motivation and self-regulation, structure of treatments, aids and scaffolding, massed vs. spaced training, and so on. However, learning across the adult lifespan presents important challenges and opportunities for both learning organizations and learners. This course is designed to review what is known about adult learning, and review potential best practices for acquisition and maintenance of knowledge and skills across the adult lifespan.
Prerequisites: PSYC 1101 and research methods (any) recommended
Human-Computer Interaction Courses
PSYC 4803 - Research Methods for HCI
Instructor: Dr. Bruce Walker (bruce.walker@psych.gatech.edu)
Click here for example syllabus
Description:
An overview of many of the research methods, tools, metrics, and analyses used in the human factors, engineering psychology, human-computer interaction, and design fields. Covers qualitative and quantitative approaches to assessing performance, preference, and affective responses as part of the evidence-based design, development, and deployment of systems and services. Some examples include surveys, focus groups, interviews, usability studies, task analysis, modeling, physiological data collection, eye tracking, benchmark tasks, accessibility audits, web analytics, and more.
In this course, you will learn about common methods employed in user-centered and evidence-based design. You will also learn how to choose methods, plan studies, and perform research that is inclusive of users with a range of abilities. The objective of this course is to train you to use the appropriate methods, tools, metrics, and analyses for generating evidence to inform and reflect on design decisions. This course is different from traditional research methods because you will be expected to increase your awareness, understanding, and application of inclusive research practices.
Prerequisites: None
