Python Training in Canberra

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks, such as LangChain and AutoGen, to construct, link, and manage agent workflows.

This instructor-led, live training (available online or onsite) 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.
• Utilise 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 Customization Options

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

This course imparts practical engineering strategies for designing, constructing, testing, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-ready considerations.

Delivered as instructor-led, live training (available online or onsite), this program is tailored for intermediate to advanced-level ML engineers, AI developers, and software engineers looking to create robust, production-ready autonomous agents using Python.

Upon completion of this training, participants will be equipped to:

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

Course Format

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customisation Options

• To request tailored training for this course, please contact us to make arrangements.

Artificial Intelligence with Python involves the creation of intelligent systems leveraging Python's comprehensive ecosystem of AI and machine learning libraries.

This instructor-led, live training (available online or onsite) is designed for intermediate-level Python programmers who wish 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.

Format of the Course

• Interactive lecture and discussion.
• Ample exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

This instructor-led, live training in Canberra (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience 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 features.
• Write, debug, and deploy Python applications in AWS Cloud9.
• Collaborate with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployments.

This instructor-led, live training in Canberra (online or onsite) is designed for expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyse and visualise data effectively.

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

• Learn 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 like Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to apply Python for 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 with Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow best practices for projects.

Format of the Course

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customization Options

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

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 emphasizes 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, optimize, and harden Python applications for production.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Canberra (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 Python programming language.
• Implement Python code in Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

This instructor-led, live training (online or onsite) is designed for developers wishing to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Canberra (online or onsite) is aimed at beginner-level 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 tailored for individuals eager to master the Python programming language. The curriculum places a strong emphasis on the Python language itself, its core libraries, and the selection of the most effective and valuable libraries contributed by the Python community. Python is a dominant force in the business world and is widely utilised by scientists globally, ranking as one of the most popular programming languages.

The course is delivered using the latest Python 3.x version, incorporating practical exercises that leverage the language's full capabilities. It is compatible with any operating system, including all variants of UNIX (such as Linux and Mac OS X) as well as Microsoft Windows.

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

Please note: The training content can be customised to meet specific organisational requirements, provided a request is made prior to the proposed course date.

This instructor-led, live training in Canberra (online or onsite) is aimed at developers who wish to learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.

This course is tailored for individuals keen on mastering the Python programming language. It focuses primarily on the Python language itself, its core libraries, and the curation of the most valuable and effective libraries contributed by the Python community. Python is a powerhouse in the business world and is widely utilised by scientists globally, cementing its status as one of the most popular programming languages today.

This instructor-led, live training in Canberra is rooted in Al Sweigart’s best-selling book, "Automate the Boring Stuff with Python". Designed for beginners, the course explores fundamental Python programming concepts through interactive discussions and practical, hands-on exercises. The primary objective is to equip learners with the ability to write code that significantly boosts office productivity.

Upon completing this training, participants will be proficient in Python programming and able to apply their new skills to:

• Automate routine tasks by writing simple Python scripts.
• Create programs capable of text pattern recognition using "regular expressions".
• Programmatically generate and update Excel spreadsheets.
• Parse PDFs and Word documents.
• Crawl websites and extract data from online sources.
• Develop programs that send email notifications.
• Utilise Python's debugging tools to swiftly resolve bugs.
• Programmatically control the mouse and keyboard to click and type on your behalf.

In this instructor-led, live training in Canberra, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques for solving complex problems.
• Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Push Python algorithms to their maximum potential.
• Use libraries and packages such as NumPy and Theano.

This instructor-led, live training in Canberra (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.

This course aims to build practical proficiency in applying Machine Learning techniques. Utilising the Python programming language and its extensive library ecosystem, alongside numerous hands-on examples, the programme teaches how to leverage the essential components of Machine Learning, make informed data modelling decisions, interpret algorithm outputs, and validate results.

Our objective is to equip you with the confidence to use the most fundamental tools from the Machine Learning toolbox and help you avoid common pitfalls associated with Data Science applications.

Python has surged in popularity within the financial sector, adopted by major investment banks and hedge funds to build diverse financial applications, from core trading systems to risk management tools.

Through this instructor-led live training, participants will learn to leverage Python to develop practical applications that address specific finance-related challenges.

Upon completing this course, participants will be able to:

• Grasp the fundamental concepts of the Python programming language
• Download, install, and manage the optimal development tools for building financial applications in Python
• Choose and employ the most appropriate Python packages and programming techniques to organise, visualise, and analyse financial data from various sources (such as CSV, Excel, databases, and web interfaces)
• Develop applications that resolve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimise Python applications

Audience

• Developers
• Analysts
• Quantitative analysts (Quants)

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• This training aims to provide solutions for key problems faced by finance professionals. If you have a specific topic, tool, or technique you would like to add or explore further, please contact us to arrange accordingly.

This course explores practical applications of Data Science and Artificial Intelligence leveraging Python. It empowers professionals with the necessary skills to analyse data, construct machine learning models, and implement AI-driven solutions within business environments. Key topics include CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with Tensorflow, natural language processing, big data management using Spark, and data-driven storytelling. It is an ideal choice for beginners pursuing a Python data science certification and career-focused analytics training.

Applied AI from Scratch in Python provides programmers and data analysts with the essential techniques required to construct machine learning solutions from the ground up using Python. It covers the fundamental principles of supervised learning, including classification and regression, as well as unsupervised learning methods such as clustering and anomaly detection, alongside advanced neural network architectures. The course examines effective strategies for utilising scikit-learn, Apache Spark MLlib, and Jupyter notebooks for practical AI development. It assists professionals in implementing functional ML models, assessing algorithmic limitations, and completing applied projects to solve real-world problems.

Selenium is an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users benefit from enhanced WebDriver APIs, native relative locators, and improved grid support. Python is chosen for its simplicity and robust integration with testing frameworks like Pytest, making it an ideal language for creating scalable and maintainable test automation suites.

This instructor-led live training, available either online or onsite, targets beginner to intermediate testers and developers looking to leverage Selenium with Python for real-world web application test automation.

Upon completing this training, participants will be able to:

• Install and configure Selenium with Python within a testing environment.
• Develop robust test automation scripts using Selenium WebDriver and Pytest.
• Implement the Page Object Model (POM) to create maintainable test frameworks.
• Execute tests across multiple browsers using Selenium Grid.
• Integrate automated tests into CI/CD pipelines.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

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

This instructor-led live training in Canberra (online or onsite) is designed for MATLAB users who wish to explore or transition to Python for data analytics and visualization.

Upon completing this training, participants will be able to:

• Install and set up a Python development environment.
• Grasp the key differences and similarities between MATLAB and Python syntax.
• Leverage Python to derive insights from diverse datasets.
• Transform existing MATLAB applications into Python.
• Integrate MATLAB and Python applications effectively.

This instructor-led, live training in Canberra (online or onsite) 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 visualizations.
• Gain valuable insight from data, including trends in performance, problematic areas.

Course Overview

This practical training is tailored for data engineering professionals looking to develop hands-on expertise in artificial intelligence, Python, and large language models. The course centres on real-world applications, encompassing model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises that advance from foundational concepts to the construction of deployable AI workflows.

Training Format

• Face-to-face classroom training

• Instructor-led sessions with guided practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

• Grasp core AI and machine learning concepts pertinent to modern applications

• Enhance Python proficiency for AI development and data workflows

• Understand how large language models function and how to leverage them effectively

• Design and optimise prompts to ensure reliable outputs

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

• Integrate AI into data engineering pipelines

This instructor-led, live training in Canberra (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Canberra (online or on-site) is targeted at data scientists who wish to utilise TensorFlow to analyse potential fraud data.

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

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

This instructor-led, live training in Canberra (online or onsite) is aimed at network engineers who wish to maintain, manage, and design computer networks with Python.

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

• Optimize 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 Canberra (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyze business data, and generate dynamic Excel-based reports.

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

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

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

• Grasp the core concepts of Computer Vision
• Utilise Python to execute Computer Vision tasks
• Develop their own systems for face, object, and motion detection

Audience

• Python programmers keen on exploring Computer Vision

Course Format

• A blend of lectures, discussions, exercises, and intensive hands-on practice

This practical course is tailored for Unix and shell users seeking to boost their automation capabilities through Python. Although shell scripting remains effective for straightforward tasks, Python offers substantially more flexibility, readability, and scalability for handling complex automation, system administration, and DevOps workflows.