Interview Guide

Preface
Module 1 - Mathematical Foundations
- 1 Statistics & Mathematics
- 2 Statistical Analysis & Testing
Module 2 - Algorithms & Data Engineering
Module 3 - Classical Machine Learning
- 6 Machine Learning Models
- 7 Time-Series Analysis and Models
Module 4 - Deep Learning
- 8 Neural Network
- 9 Computer Vision and Visual Intelligence
Module 5 - Deep Reinforcement Learning
- 10 Deep Reinforcement Learning
Module 6 - Large Language Models
- 11 Large Language Models
- 12 Fine-Tuning and Adaptation of LLMs
Module 7 - Model Compression & Deployment
- 13 Model Compression, Deployment, and Efficiency
- 14 Scalability & Optimization
Module 8 - Research Design & Evaluation
- 15 Model Evaluation and Analysis
Module 9 - Trustworthy & Robust AI
- 16 Trustworthy & Secure AI
Module 10 - Emerging Topics
- 17 Multimodal
- 18 Causality
References
Appendices

Appendix E — Analysis of precipitation extremes and climate projections

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