Wellington, Plimmer Towers

Level 31, 2-6 Gilmer Terrace, Wellington, new zealand, 6011

Located in the heart of Wellington’s CBD, Plimmer Towers is in one of Wellington’s most desirable locations; situated in the north-east of Gilmer Terrace and Boulcott Street, down Plimmer Step. With a short walk to Lambton Quay and immediate vehicle access to the Terrace and motorways and being well serviced by public transport, it’s hard to find a better positioned office, with an impressive street perspective, and panoramic views over Wellington and harbour. Overlooking the waterfront and the Golden Mile, the centre is a pivotal hub surrounded by some of the best cafés, restaurants and bars, and offering access to the premier retail strip and links to Boulcott Street. The shopping precincts; Chew’s Lane, Old Bank Arcade and Kirkcaldie & Stains are all a short walk away. Plimmer Towers includes retail, a 4 Star Travelodge Hotel, and multi-level car parking with 24/7 access. Plimmer Towers is classified as a low earthquake risk under NZSEE Rating and includes sustainable features such as energy efficient lighting and intelligent lighting controls. Centre occupants reap the benefits of first-class on-site facilities and amenities including meeting rooms, business lounge, onsite bike racks, shower and bathroom facilities, and secure lockers.

Explore Our Courses

Computer Vision with Google Colab and TensorFlow

21 Hours

Deep Learning with TensorFlow in Google Colab

14 Hours

Applied AI from Scratch

28 Hours

Deep Learning for NLP (Natural Language Processing)

28 Hours

Deep Learning for Vision

21 Hours

Fraud Detection with Python and TensorFlow

14 Hours

Deep Learning with TensorFlow 2

21 Hours

TensorFlow Serving

7 Hours

Deep Learning with TensorFlow

21 Hours

TensorFlow for Image Recognition

28 Hours

TensorFlow Extended (TFX)

21 Hours

TPU Programming: Building Neural Network Applications on Tensor Processing Units

7 Hours

Natural Language Processing (NLP) with TensorFlow

35 Hours

Understanding Deep Neural Networks

35 Hours

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Provisional Upcoming Courses (Require 5+ participants)

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