All 17 phases from math foundations to production MLOps.
Cover the 17 most-asked AI/ML interview concepts: math intuition, model evaluation, classical baselines, neural nets, and transformer/RAG essentials.
Go from NumPy to a deployed classical model: data tooling, feature engineering, the model zoo, and evaluation hygiene in 14 focused days.
Build real deep-learning intuition from tensors to transformers: training mechanics, CNNs/RNNs, attention, and the generative model landscape.
Become an LLM engineer: tokenization to RLHF, prompting to RAG, fine-tuning to agents, with evaluation and deployment throughout.
The zero-to-job program: math foundations, ML engineering, deep learning, LLMs, MLOps, and two portfolio capstones in six months.