Python Training in Wellington

Python is the core language powering the development and orchestration of autonomous AI agents. This course focuses on practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who wish to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This course teaches practical engineering techniques to design, build, test, and deploy agentic (autonomous) systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

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

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to extend agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

Artificial Intelligence with Python involves building intelligent systems by leveraging Python’s rich ecosystem of AI and machine learning libraries.

This instructor-led, live training (available online or on-site) is designed for intermediate-level Python programmers who want to design, implement, and deploy AI solutions using Python.

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

• Implement AI algorithms using Python’s core AI libraries.
• Work with supervised, unsupervised, and reinforcement learning models.
• Integrate AI solutions into existing applications and workflows.
• Evaluate model performance and optimise for accuracy and efficiency.

Course Format

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

Course Customisation Options

• To request a customised version of this course, please contact us to arrange.

This instructor-led, live training in Wellington (online or onsite) is designed for intermediate-level Python developers who wish to enhance their Python development skills using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for Python development.
• Understand the AWS Cloud9 IDE interface and its features.
• Write, debug, and deploy Python applications within AWS Cloud9.
• Collaborate with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployment scenarios.

This instructor-led, live training in Wellington (online or on-site) is designed for expert-level data analysts seeking to harness Python's data analysis capabilities within Power BI, thereby enhancing their ability to analyse and visualise data effectively.

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

• Understand how Python can be integrated into Power BI for data analysis.
• Use Python scripts to load, clean, and preprocess data within the Power BI environment.
• Enhance data visualisation capabilities by creating custom and interactive visualisations using Python.
• Acquire advanced data analysis skills using Python.

Python is a versatile programming language widely used for data manipulation, automation, and analytics. Libraries such as Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (available online or on-site) is designed for professionals at a beginner to intermediate level who wish to apply Python to everyday data analysis, file processing, and process automation using Pandas and Polars.

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

• Use Python to read, transform, and write CSV and Excel files.
• Perform common data cleaning and transformation tasks using Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow best practices for project management.

Course Format

• Interactive coding demonstrations and short lectures.
• Hands-on exercises supported by guided code examples.
• Practical mini-projects focused on automating real-world tasks.

Course Customisation Options

• To request a customised version of this course, please contact us to make arrangements.

This intensive, hands-on course covers advanced Python techniques, engineering best practices, and commonly used design patterns to build maintainable, testable, and high-performance Python applications. It emphasises modern tooling, typing, concurrency models, architecture patterns, and deployment-ready workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level Python developers who wish to adopt professional practices and patterns for production-grade Python systems.

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

• Apply Python typing, dataclasses, and type-checking to increase code reliability.
• Use design patterns and architecture principles to structure robust applications.
• Implement concurrency and parallelism correctly using asyncio and multiprocessing.
• Build well-tested code with pytest, property-based testing, and CI pipelines.
• Profile, optimise, and harden Python applications for production.
• Package, distribute, and deploy Python projects using modern tools and containers.

Course Format

• Interactive lectures and short demos.
• Hands-on labs and coding exercises each day.
• Capstone mini-project integrating patterns, testing, and deployment.

Course Customisation Options

• To request a customised training or focus area (data, web, or infra), please contact us to arrange.

This instructor-led, live training in Wellington (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

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

• Understand the basics of the Python programming language.
• Implement Python code within the Google Colab environment.
• Use control structures to manage the flow of a Python program.
• Create functions to organise and reuse code effectively.
• Explore and utilise basic libraries for Python programming.

This instructor-led, live training (available online or on-site) is designed for developers eager to harness the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Establish the essential development environment integrating FastAPI, React, and MongoDB.
• Grasp the core concepts, features, and advantages of the FARM stack.
• Learn how to construct REST APIs using FastAPI.
• Master the art of designing interactive applications with React.
• Develop, test, and deploy both front-end and back-end applications using the FARM stack.

This instructor-led, live training in Wellington (available online or on-site) is designed for beginner to intermediate-level, and potentially advanced-level, robotics developers who wish to learn how to use ROS to program mobile robots using Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshoot and debug ROS applications.

This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python powers businesses and is used by scientists around the world – it is one of the most popular programming languages.

The course can be delivered using the latest Python version 3.x, with practical exercises that make full use of its capabilities. It can be run on any operating system (all flavours of UNIX, including Linux and macOS, as well as Microsoft Windows).

Practical exercises make up approximately 70% of the course time, while demonstrations and presentations account for around 30%. Participants are encouraged to ask questions and engage in discussions throughout the course.

Note: The training can be customised to meet specific needs upon prior request before the proposed course date.

This instructor-led, live training in Wellington (online or on-site) is designed for developers seeking to master advanced Python programming techniques, including how to leverage this versatile language to address challenges in distributed applications, data analysis and visualisation, UI development, and maintenance scripting.

This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.

This instructor-led, live training in Wellington is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code that dramatically boosts office productivity.

By the end of this training, participants will be able to program in Python and apply this new skill to:

• Automate tasks by writing simple Python programs.
• Create programs that perform text pattern recognition using "regular expressions".
• Programmatically generate and update Excel spreadsheets.
• Parsе PDFs and Word documents.
• Crawl websites and extract information from online sources.
• Build programs that send email notifications.
• Use Python's debugging tools to quickly resolve bugs.
• Programmatically control the mouse and keyboard to click and type on your behalf.

In this instructor-led, live training in Wellington, participants will explore the most relevant and cutting-edge machine learning techniques in Python by building a series of demo applications that incorporate image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques to tackle complex problems.
• Apply deep learning and semi-supervised learning approaches to applications involving image, music, text, and financial data.
• Maximise the potential of Python algorithms.
• Utilise libraries and packages such as NumPy and Theano.

This instructor-led, live training in Wellington (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

The aim of this course is to equip participants with practical proficiency in applying Machine Learning methods. Using the Python programming language and its diverse libraries, and drawing on numerous real-world examples, the course covers the core components of Machine Learning, guiding learners through data modelling decisions, interpretation of algorithm outputs, and validation of results.

Our goal is to empower you with the confidence to understand and apply the most essential tools from the Machine Learning toolbox, while helping you avoid common pitfalls encountered in Data Science applications.

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.

Applied AI from Scratch in Python equips programmers and data analysts with foundational techniques for building machine learning solutions from the ground up using Python. Covers core principles of supervised learning classification and regression, unsupervised learning clustering and anomaly detection, and advanced neural network architectures. Examines proven methods for working with scikit-learn, Apache Spark MLlib, and Jupyter notebooks for hands-on AI development. Helps professionals implement practical ML models, evaluate algorithm limitations, and complete applied projects for real-world problem solving.

Selenium is an open-source framework for automating web application testing across different browsers. With Selenium 4, enhanced WebDriver APIs, native relative locators, and improved grid support are available. Python offers simplicity and strong integration with testing frameworks like Pytest, making it a powerful choice for developing scalable and maintainable test automation suites.

This instructor-led, live training (online or on-site) is aimed at beginner-level to intermediate-level testers and developers who wish to use Selenium with Python to automate web application testing in real-world environments.

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

• Install and configure Selenium with Python in a test environment.
• Build robust test automation scripts using Selenium WebDriver and Pytest.
• Apply the Page Object Model (POM) to create maintainable test frameworks.
• Run tests across multiple browsers using Selenium Grid.
• Integrate automated tests with CI/CD pipelines.
• Troubleshoot common issues and apply best practices for automation stability.

Course Format

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

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Wellington (delivered either online or on-site) is designed for Matlab users who wish to explore and/or transition to Python for data analytics and visualisation.

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

• Install and configure a Python development environment.
• Understand the key differences and similarities between Matlab and Python syntax.
• Use Python to extract insights from a variety of datasets.
• Migrate existing Matlab applications to Python.
• Integrate Matlab and Python applications seamlessly.

This instructor-led, live training in Wellington (online or on-site) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..

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

• Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
• Analyse data from sources such as Excel, CSV, JSON files and databases.
• Clean data to improve its usefulness before analysing it.
• Perform simple statistical analysis.
• Generate reports that present the desired data in just the right format, from straight numbers to data visualisations.
• Gain valuable insight from data, including trends in performance, problematic areas.

Course Overview

This practical training is tailored for professionals with a data engineering background who wish to develop hands-on expertise in artificial intelligence, Python, and large language models. The curriculum emphasises real-world applications, encompassing model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will navigate through progressive exercises that transition from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom-based training

• Instructor-led sessions featuring guided practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

• Comprehend core AI and machine learning concepts pertinent to contemporary applications

• Enhance Python skills for AI development and data workflows

• Gain an understanding of how large language models function and how to utilise them effectively

• Design and optimise prompts to ensure reliable outputs

• Construct end-to-end AI solutions using APIs and frameworks

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Wellington (online or on-site) is designed for developers who wish to leverage FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly.

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

• Set up the necessary development environment to build APIs using Python and FastAPI.
• Create APIs more quickly and easily using the FastAPI library.
• Learn how to define data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication mechanisms in APIs using FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Wellington (available online or on-site) is designed for data scientists who wish to leverage TensorFlow to analyse potential fraud data.

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

• Develop a fraud detection model using Python and TensorFlow.
• Construct linear regressions and linear regression models to predict fraudulent activity.
• Build an end-to-end AI application for analysing fraud data.

This instructor-led, live training in Wellington (delivered online or on-site) is designed for network engineers who wish to maintain, manage, and design computer networks using Python.

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

• Optimise and leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Use GNS3 and Python for network programming.

This instructor-led, live training in Wellington (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyse business data, and generate dynamic Excel-based reports.

Computer Vision is a field focused on automatically extracting, analysing, and interpreting valuable information from digital media. Python is a high-level programming language renowned for its clear syntax and readability.

In this instructor-led, live training, participants will learn the fundamentals of Computer Vision while building a series of simple Computer Vision applications using Python.

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

• Understand the fundamentals of Computer Vision
• Use Python to implement Computer Vision tasks
• Build their own face, object, and motion detection systems

Audience

• Python programmers interested in Computer Vision

Course Format

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

This practical course is tailored for Unix and shell users looking to boost their automation capabilities by harnessing Python. Although shell scripting is still effective for straightforward tasks, Python offers far greater flexibility, readability, and scalability for complex automation, system administration, and DevOps workflows.