Online Data Science Training in New Zealand

This instructor-led, live training in New Zealand (delivered either online or on-site) is designed for beginner-level professionals who wish to understand the concept of pre-trained models and learn how to apply them to solve real-world problems without building models from scratch.

By the end of this training, participants will be able to:

• Understand the concept and benefits of pre-trained models.
• Explore various pre-trained model architectures and their use cases.
• Fine-tune a pre-trained model for specific tasks.
• Implement pre-trained models in simple machine learning projects.

This instructor-led, live training in New Zealand (online or on-site) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 to streamline their data science workflows.

By the end of this training, participants will be able to:

• Set up a data science environment in AWS Cloud9.
• Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
• Integrate AWS Cloud9 with AWS data services such as S3, RDS, and Redshift.
• Use AWS Cloud9 for developing and deploying machine learning models.
• Optimise cloud-based workflows for data analysis and processing.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using Apache Airflow.

By the end of this training, participants will be able to:

• Set up Apache Airflow for machine learning workflow orchestration.
• Automate data preprocessing, model training, and validation tasks.
• Integrate Airflow with machine learning frameworks and tools.
• Deploy machine learning models using automated pipelines.
• Monitor and optimise machine learning workflows in production.

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner-level data scientists and IT professionals who wish to learn the fundamentals of data science using Google Colab.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and manage datasets.
• Create visualisations using Python libraries.

This instructor-led, live training in New Zealand (available online or on-site) is tailored for data scientists and developers who aspire to learn and advance their careers in data science using Kaggle.

By the end of this training, participants will be able to:

• Gain a solid understanding of data science and machine learning.
• Explore the fundamentals of data analytics.
• Learn how Kaggle operates and leverage its features effectively.

Python is a programming language that has gained immense popularity within the financial sector. Adopted by leading investment banks and hedge funds, it is now used to build a broad spectrum of financial applications, ranging from core trading systems to risk management platforms.

In this live, instructor-led training, participants will learn how to leverage Python to develop practical solutions for a variety of finance-specific challenges.

By the conclusion of this course, participants will be able to:

• Grasp the fundamentals of the Python programming language
• Download, install, and maintain the most effective development tools for creating financial applications in Python
• Select and apply the most appropriate Python packages and programming techniques to organise, visualise, and analyse financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Build applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimise Python applications

Audience

• Developers
• Analysts
• Quants

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

• This training is designed to address some of the key challenges faced by finance professionals. However, if you have a specific topic, tool, or technique you would like to explore further, please contact us to arrange.

This course explores practical approaches to Data Science and AI using Python, equipping professionals with the skills to explore data, build machine learning models, and deploy AI-driven applications in business contexts. It covers CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with Tensorflow, natural language processing, big data with Spark, and data-driven storytelling. Ideal for beginners seeking a Python data science certification and career-ready analytics training.

KNIME Analytics Platform is a leading open-source option for data-driven innovation, helping you uncover the potential hidden in your data, mine fresh insights, or predict new futures. With over 1,000 modules, hundreds of ready-to-run examples, a comprehensive suite of integrated tools, and the widest range of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.

This course on KNIME Analytics Platform offers an ideal opportunity for beginners, advanced users, and KNIME experts to get introduced to KNIME, learn how to use it more effectively, and create clear, comprehensive reports based on KNIME workflows.

This instructor-led, live training (available online or on-site) is designed for data professionals who want to leverage KNIME to address complex business challenges.

It is tailored for audiences without programming experience who wish to utilise cutting-edge tools to implement analytics scenarios.

By the end of this training, participants will be able to:

• Install and configure KNIME.
• Build data science scenarios.
• Train, test, and validate models.
• Implement the end-to-end value chain of data science models.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live lab environment.

Course Customisation Options

• To request customised training for this course or to learn more about the program, please contact us to arrange.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data analysts, developers, or aspiring data scientists who wish to apply machine learning techniques in Python to extract insights, make predictions, and automate data-driven decisions.

By the end of this course, participants will be able to:

• Understand and differentiate key machine learning paradigms.
• Explore data preprocessing techniques and model evaluation metrics.
• Apply machine learning algorithms to solve real-world data problems.
• Use Python libraries and Jupyter notebooks for hands-on development.
• Build models for prediction, classification, recommendation, and clustering.