Introduction to AI in Semiconductor Manufacturing Training Course

This live, instructor-guided training session in Thailand (online or onsite) caters to participants from diverse professional backgrounds who aim to utilize Google’s AutoML platform to construct customized chatbots for a wide range of applications.

By the end of this session, participants will be equipped to:

• Grasp the core principles of chatbot engineering.
• Explore the Google Cloud Platform ecosystem and utilize AutoML.
• Curate and prepare data for training chatbot models.
• Train and assess custom chatbot models using AutoML.
• Integrate and deploy chatbots across multiple platforms and channels.
• Track and refine chatbot performance for sustained effectiveness.

This live, instructor-led training in Thailand (available online or onsite) provides an introductory overview of pattern recognition and machine learning. It explores practical applications within statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.

By the end of this program, participants will be prepared to:

• Apply core statistical methods to pattern recognition scenarios.
• Utilize key models, including neural networks and kernel methods, for data analysis.
• Implement advanced techniques to solve complex problems.
• Enhance prediction accuracy by integrating various models.

This instructor-led, live training in Thailand (online or onsite) is tailored for intermediate-level professionals seeking to leverage AI-driven predictive maintenance in semiconductor manufacturing to boost production efficiency and curb unexpected equipment failures.

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

• Deploy AI models to forecast equipment failures in semiconductor manufacturing.
• Analyze maintenance data to detect patterns and trends that indicate potential issues.
• Integrate AI-driven predictive maintenance into existing manufacturing workflows.
• Lower downtime and maintenance costs through proactive equipment management.

This live, instructor-led training, conducted in Thailand (either online or on-site), targets intermediate data analysts aiming to master the use of RapidMiner for value estimation and projection, and for employing analytical tools in time series forecasting.

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

• Implement the CRISP-DM methodology, select optimal machine learning algorithms, and refine model construction and performance outcomes.
• Utilize RapidMiner to estimate and project values, and apply analytical tools for time series forecasting.