AI Data Storytelling Specialist vs AI Deepfake Detection Specialist

B AI Deepfake Detection Specialist Only

• Adversarial machine learning - understanding generator architectures (GANs, diffusion models, NeRFs) and their failure modes
• Computer vision fundamentals - image forensics, frequency-domain analysis (DCT, FFT), error level analysis (ELA)
• Deep learning for classification - training binary and multi-class detectors using PyTorch/TensorFlow with imbalanced datasets
• Video and audio forensics - temporal consistency analysis, lip-sync verification, spectral audio fingerprinting
• Data pipeline engineering - building scalable ETL pipelines for ingesting, preprocessing, and labeling media at scale
• Explainable AI (XAI) - generating interpretable heatmaps and attribution maps that show why a model flagged specific content
• Dataset curation and synthetic data generation - creating high-quality training sets that keep pace with evolving forgery techniques
• Technical writing and expert testimony - producing forensic reports that withstand legal scrutiny and communicate findings clearly