Deep Learning · TEE · section

Coverage and examination structure

TEE preparation and examination plan

The TEE route covers all five units of course 702AI0C036: introduction and neural-network foundations, optimization and regularization, CNNs and their architectures, and recurrent models including BPTT, LSTM and GRU. Machine-learning prerequisites are explained within the course. Basic algebra and calculus are assumed, with a concise revision chapter available when required.

The supplied course policy specifies a three-hour, 100-mark TEE: Q1 is compulsory, followed by any four of Q2–Q7; each main question carries 20 marks. TEE marks are scaled to 50. Read the instructions printed on the actual examination paper.