FinOps Training Course

This instructor-led, live training in New Zealand (available online or on-site) is designed for advanced-level professionals who wish to deepen their understanding of machine learning models, refine their skills in hyperparameter tuning, and learn how to deploy models effectively using Google Colab.

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

• Implement advanced machine learning models using popular frameworks such as Scikit-learn and TensorFlow.
• Optimise model performance through hyperparameter tuning.
• Deploy machine learning models in real-world applications using Google Colab.
• Collaborate on and manage large-scale machine learning projects within Google Colab.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data scientists and healthcare professionals who wish to leverage AI for advanced healthcare applications using Google Colab.

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

• Implement AI models for healthcare using Google Colab.
• Use AI for predictive modelling in healthcare data.
• Analyse medical images with AI-driven techniques.
• Explore ethical considerations in AI-based healthcare solutions.

This instructor-led, live training in New Zealand (on-site or remote) is designed for engineers who wish to deploy and manage IoT devices on AWS.

By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on AWS.

This instructor-led, live training in New Zealand (online or on-site) is designed for developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to build applications for a variety of devices.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices.

This instructor-led, live training in New Zealand (on-site or remote) is designed for developers who wish to leverage AWS Lambda to build and deploy services and applications to the cloud, without concerning themselves with provisioning the execution environment (servers, virtual machines, containers, availability, scalability, storage, and so on).

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

• Configure AWS Lambda to execute a function.
• Understand FaaS (Functions as a Service) and the benefits of serverless development.
• Build, upload, and execute AWS Lambda functions.
• Integrate Lambda functions with various event sources.
• Package, deploy, monitor, and troubleshoot Lambda-based applications.

This instructor-led, live training in New Zealand (delivered either online or on-site) is designed for intermediate-level data scientists and engineers who wish to leverage Google Colab and Apache Spark for big data processing and analytics.

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

• Set up a big data environment using Google Colab and Spark.
• Process and analyse large datasets efficiently with Apache Spark.
• Visualise big data within a collaborative environment.
• Integrate Apache Spark with cloud-based tools.

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.

Google Colab Pro is a cloud-based environment designed for scalable Python development, providing access to high-performance GPUs, extended runtimes, and increased memory to support demanding AI and data science workloads.

This instructor-led, live training (delivered either online or on-site) is tailored for intermediate-level Python users who wish to leverage Google Colab Pro for machine learning, data processing, and collaborative research within a powerful notebook interface.

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

• Set up and manage cloud-based Python notebooks using Colab Pro.
• Access GPUs and TPUs for accelerated computation.
• Streamline machine learning workflows using popular libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Integrate with Google Drive and external data sources to support collaborative projects.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and hands-on practice.
• Real-time 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 New Zealand (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualise and interpret the results of image classification models.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.

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

• Set up and navigate Google Colab for deep learning projects.
• Understand the fundamentals of neural networks.
• Implement deep learning models using TensorFlow.
• Train and evaluate deep learning models.
• Utilise advanced features of TensorFlow for deep learning.

This instructor-led, live training in New Zealand (available online or on-site) is designed for advanced-level professionals seeking to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilise source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

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

• Understand the fundamentals of serverless architecture.
• Set up AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications using AWS Lambda.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3.
• Optimise serverless applications for performance and cost efficiency.

This instructor-led, live training in New Zealand (online or on-site) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualisations.

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

• Set up and navigate Google Colab for data visualisation.
• Create various types of plots using Matplotlib.
• Utilise Seaborn for advanced visualisation techniques.
• Customise plots for better presentation and clarity.
• Interpret and present data effectively using visual tools.

Overview:

• Foundations of IoT architecture and core functions
• Understanding 'Things', 'Sensors', the Internet, and how they align with business functions
• Essential components of IoT software stacks: hardware, firmware, middleware, cloud, and mobile applications
• Key IoT capabilities: fleet management, data visualisation, SaaS-based fleet management and visualisation, alerting and alarms, sensor onboarding, 'thing' onboarding, and geo-fencing
• Basics of IoT device communication with the cloud using MQTT.
• Connecting IoT devices to AWS via MQTT (AWS IoT Core).
• Integrating AWS IoT Core with AWS Lambda for computation and storing data in DynamoDB.
• Connecting Raspberry Pi to AWS IoT Core for simple data exchange.
• Practical workshop: building a smart device using Raspberry Pi and AWS IoT Core.
• Visualising sensor data and enabling communication via a web interface.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply machine learning algorithms efficiently using the Google Colab environment.

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

• Set up and navigate Google Colab for machine learning projects.
• Understand and apply various machine learning algorithms.
• Use libraries like Scikit-learn to analyse and predict data.
• Implement supervised and unsupervised learning models.
• Optimise and evaluate machine learning models effectively.