AI-Driven Process Optimization in Chip Fabrication Training Course

This instructor-led, live training in New Zealand (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

This instructor-led, live training in New Zealand (online or on-site) is aimed at participants with varying levels of expertise who wish to leverage Google's AutoML platform to build customised chatbots for various applications.

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

• Understand the fundamentals of chatbot development.
• Navigate the Google Cloud Platform and access AutoML.
• Prepare data for training chatbot models.
• Train and evaluate custom chatbot models using AutoML.
• Deploy and integrate chatbots into various platforms and channels.
• Monitor and optimise chatbot performance over time.

This instructor-led, live training in New Zealand (online or onsite) introduces participants to the field of pattern recognition and machine learning. It explores practical applications across statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.

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

• Apply core statistical methods to pattern recognition.
• Use key models such as neural networks and kernel methods for data analysis.
• Implement advanced techniques to tackle complex problem-solving challenges.
• Improve prediction accuracy by combining different models.

This instructor-led, live training in New Zealand (online or on-site) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
• Develop and optimise AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Use tools and techniques for model conversion and optimisation.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led live training in New Zealand (online or on-site) is designed for developers and data scientists aiming to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow in on-premise and cloud settings.
• Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
• Run complete machine learning pipelines across diverse architectures and cloud environments.
• Use Kubeflow to spawn and manage Jupyter notebooks.
• Create ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level data analysts who want to learn how to use RapidMiner to estimate and forecast values, and to leverage analytical tools for time series forecasting.

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

• Apply the CRISP-DM methodology, select appropriate machine learning algorithms, and improve model construction and performance.
• Use RapidMiner to estimate and forecast values, and utilise analytical tools for time series forecasting.

This instructor-led, live training in New Zealand (online or on-site) is designed for advanced-level professionals seeking to explore state-of-the-art XAI techniques for deep learning models, with a particular focus on building interpretable AI systems.

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

• Understand the challenges of explainability in deep learning.
• Implement advanced XAI techniques for neural networks.
• Interpret decisions made by deep learning models.
• Evaluate the trade-offs between performance and transparency.