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.

Subcategories (3)

Explore Our Courses

Introduction to LLMs and AI Tools for Senior Management

2 Hours

Introduction to LLMs and AI Tool Integration

7 Hours

Large Language Models Meta AI

21 Hours

Generative AI and Large Language Models (LLMs)

14 Hours

Ethical Deployment of LLMs

7 Hours

Cross-Lingual LLMs

14 Hours

LLMs for Financial Market Prediction

14 Hours

LLMs for Environmental Modeling

14 Hours

LLMs for Virtual Reality (VR) and Augmented Reality (AR)

14 Hours

LLMs in Multimodal Applications

14 Hours

LLMs for Cybersecurity

14 Hours

LLMs for Predictive Analytics

14 Hours

Large Language Models (LLMs) and Reinforcement Learning (RL)

21 Hours

LLMs for Content Generation

14 Hours

LLMs for Personalized Education

14 Hours

Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

14 Hours

LLMs for Speech Recognition and Synthesis

14 Hours

LLMs for Automated Customer Support

14 Hours

Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

14 Hours

Fine-Tuning Large Language Models Using QLoRA

14 Hours

LLMs for Sentiment Analysis

21 Hours

LLMs for Code Generation and Documentation

14 Hours

LLMs for Business Intelligence

14 Hours

LlamaIndex: Developing LLM Powered Applications

42 Hours

Ollama for Responsible AI and Governance

14 Hours

LlamaIndex: Enhancing Contextual AI

14 Hours

Ollama & Data Privacy: Secure Deployment Patterns

14 Hours

Prompt Engineering and Few-Shot Fine-Tuning

14 Hours

Prompt Engineering Mastery with Ollama

14 Hours

LangGraph for Legal Applications

35 Hours

Ollama Scaling & Infrastructure Optimization

21 Hours

LangGraph Applications in Finance

35 Hours

Multimodal Applications with Ollama

21 Hours

Advanced Ollama Model Debugging & Evaluation

35 Hours

LangGraph in Healthcare: Workflow Orchestration for Regulated Environments

35 Hours

Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs

35 Hours

Fine-Tuning and Customizing AI Models on Ollama

14 Hours

Generative AI with Large Language Models (LLMs)

21 Hours

LLMs and Agents in DevOps Workflows

14 Hours

Building Private AI Workflows with Ollama

14 Hours

Building Secure and Responsible LLM Applications

14 Hours

LangGraph for Marketing Automation

14 Hours

Deploying and Optimizing LLMs with Ollama

14 Hours

Fine-Tuning Models and Large Language Models (LLMs)

14 Hours

Building Dynamic Workflows with LangGraph and LLM Agents

14 Hours

LLMs for Code Understanding, Refactoring, and Documentation

14 Hours

Advanced LLMs for NLP Tasks

21 Hours

Introduction to Claude AI: Conversational AI and Business Applications

14 Hours

LangGraph Foundations: Graph-Based LLM Prompting and Chaining

14 Hours

Introduction to Large Language Models (LLMs)

14 Hours

Getting Started with Ollama: Running Local AI Models

7 Hours

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Provisional Upcoming Courses (Require 5+ participants)

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