Program Structure

Module 1: Introduction to AI in Psychology and Behavioral Analysis

• Overview of how AI is applied in psychology.
• Use cases in mental health monitoring, personality detection, and behavioral prediction.
• Ethical considerations in AI for behavioral analysis.

Module 2: Fundamentals of Behavioral Data Collection

• Sources of behavioral data: Social media, surveys, wearables.
• Techniques for collecting and analyzing behavioral data.
• Ethical guidelines for using behavioral data.

Module 3: Natural Language Processing (NLP) for Behavioral Analysis

• NLP techniques for analyzing text-based behavior.
• Sentiment analysis, emotion detection, and personality assessment.
• Case studies: Using social media for mental health signals.

Module 4: AI for Personality Analysis

• Introduction to personality models like the Big Five and Myers-Briggs.
• AI techniques for detecting personality traits from text and social media data.
• Applications in marketing, HR, and psychotherapy.

Module 5: Emotion Recognition with AI

• AI techniques for detecting emotions from text, voice, and video.
• Real-time emotion analysis in AI-driven applications.
• Case studies: AI-driven mental health monitoring.

Module 6: Behavioral Prediction with AI

• Predicting human actions and behaviors with AI.
• Analyzing behavioral data from wearables (Fitbit, smartwatches).
• AI for predicting consumer behavior and decision-making.

Module 7: Facial Recognition and Body Language Analysis

• AI for analyzing facial expressions and body language.
• Deep learning techniques for recognizing human emotions and behaviors.
• Use cases: AI for detecting deception, stress, and anxiety.

Module 8: AI for Mental Health Diagnostics

• AI tools for diagnosing mental health conditions.
• Predicting depression, anxiety, and PTSD from social media and behavioral data.
• Applications of AI in therapeutic interventions.

Module 9: AI and Behavioral Economics

• Using AI to understand human decision-making and preferences.
• Applications of AI in behavioral finance.
• Predicting economic behavior with AI models.

Module 10: AI and Cognitive Science

• Cognitive models and AI techniques for understanding human thought processes.
• AI for modeling cognitive processes like attention, memory, and learning.
• Applications of AI in cognitive behavioral therapy (CBT).

Module 11: Ethics and Privacy in AI-Driven Behavioral Analysis

• Addressing ethical concerns in AI for psychological analysis.
• Privacy considerations in behavioral data collection.
• Understanding AI bias in psychological assessments.

Final Project

• Develop a practical AI system for psychological or behavioral analysis.
• Example projects: Build an AI model for emotion detection from text or predict stress levels using wearable data.