AI & TECHNOLOGY SERIES

Master practical AI implementation for research and analysis. Learn which tools actually work, common pitfalls to avoid, and hands-on prompting techniques that get reliable results.

Ideal for: Anyone curious about AI but overwhelmed by options and how to get started, teams wanting to incorporate AI safely, or professionals who keep hearing about AI but don't know where to begin.

Level up your AI capabilities with advanced prompting strategies, multi-tool workflows, and quality control methods. Includes AI for data analysis, literature reviews, and scaling qualitative research.

Ideal for: Current AI users hitting limitations, researchers wanting to scale their work, or teams needing to standardize AI workflows across projects.

Build confidence with fundamental statistical concepts that actually matter. Cover descriptive statistics, hypothesis testing, correlation, and when to use which test. No PhD required—just practical understanding. 

Ideal for: Professionals new to statistics, those needing a refresher, or anyone who breaks into a cold sweat when seeing numbers.

Master regression, ANOVA, mediation, and moderation with real-world applications. Learn to handle messy data, validate assumptions, and communicate results to non-technical audiences.

Ideal for: Researchers, practitioners, or any individuals comfortable with basic statistics ready to tackle more complex analyses, or analysts needing to move beyond simple comparisons.

Conquer multilevel modeling, structural equation modeling, and latent variable analysis. Handle nested data, test complex theoretical models, and extract insights from hierarchical structures.

Ideal for: Doctoral students, experienced researchers, and analysts working with complex data structures or testing sophisticated theoretical models.

Explore the psychological mechanisms driving extremism and polarization. Based on cutting-edge research, understand how ideology, identity, and social dynamics create pathways to radicalization.

Ideal for: Security professionals, educators, community leaders, researchers studying polarization, or anyone trying to understand why people embrace extreme beliefs.

Discover how in-groups, out-groups, and identity threats drive decision-making. Essential for anyone working with diverse teams, communities, or trying to understand intergroup conflict. 

Ideal for: Team leaders, organizational managers, conflict mediators, political analysts, or anyone working with diverse groups or trying to understand intergroup dynamics.

Unpack the psychological foundations of moral judgment, political ideology, and value-based conflicts. Learn how moral intuitions shape data interpretation and decision-making. 

Ideal for: Policy makers, political strategists, organizational leaders, researchers studying ideology, or anyone puzzled by how people reach opposite conclusions from the same data.

Create surveys that actually answer your questions. Learn question writing, response scales, sampling basics, and how to avoid the most common (and costly) survey mistakes.

Ideal for: Anyone creating their first survey, program evaluators, or those whose surveys aren't getting useful responses.

Tackle sensitive topics, hard-to-reach populations, and complex constructs. Master multi-wave designs, panel studies, and modern online sampling methods.

Ideal for: Experienced researchers dealing with sensitive topics, longitudinal studies, or difficult-to-reach populations.

Learn to design studies that establish causation, not just correlation. Cover randomization basics, control groups, and simple experimental designs that work in the real world.

Ideal for: Those new to experiments, evaluators wanting to test interventions, or anyone tired of hearing "correlation isn't causation".

Master factorial designs, power analysis, manipulation checks, and dealing with non-compliance. Navigate the replication crisis and design publication-quality experiments.

Ideal for: Graduate students, lab managers, and researchers designing complex multi-factor experiments or field studies.

Master probability and non-probability sampling, calculate sample sizes, conduct power analyses, and handle non-response. Essential for anyone designing studies or evaluating research.

Ideal for: Anyone designing studies, writing grants, or evaluating whether research findings apply to their population.