Artificial Intelligence & Data Science · 1.8

Research Scientist (AI)

Advance the state of the art in AI through novel research, publishing papers, and pushing boundaries.

12–18 months (often alongside a graduate program)5 phases25 skills

Phase 01 · 16h

Mathematical Foundations

Multivariate calculus

Probability and statistics

Information theory

Phase 02 · 12h

ML Theory

Statistical learning theory

Graphical models

Online learning

Phase 03 · 25h

Deep Learning Theory & Practice

Neural network theory

Architecture deep dives

Training dynamics

Generative models

Reinforcement learning

Research Methods

Literature review

Experiment design

Reproducibility

Phase 05 · 47h

Specialization & Publication (Weeks 37–52+)

Choose a specialization

Reproduce 2–3 influential papers in your chosen area — match the reported results, understand every design choice

Identify a research gap by analyzing limitations sections of recent papers, design experiments, iterate on hypotheses

Write and submit a paper to a top venue (NeurIPS, ICML, ICLR for general ML; ACL, EMNLP for NLP; CVPR, ECCV for vision; AAAI for AI broadly)

Present at reading groups, lab seminars, and workshop poster sessions

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