You will learn methods to identify anomalies and failures from time series data based on AI, as well as how to estimate the remaining useful life of the relevant parts.
■Goals - Using time series data, it is possible to predict outcomes with an XGBoost-based machine learning classification model. - By using an LSTM-based model, it is possible to predict equipment failures. - Utilizing anomaly detection with a time series autoencoder, it is possible to predict failures when limited failure case data is available. ■Target Audience System engineers and developers who develop and provide predictive maintenance systems in the industrial sector. ■Prerequisite Knowledge - Completion of the course "Introduction to Python from Scratch - Focusing on Data Analysis" or equivalent knowledge. - Completion of the course "NVIDIA Deep Learning Institute (DLI) Certified Course Fundamentals of Deep Learning" or equivalent knowledge.
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basic information
■Content 1. Orientation 2. Learning XGBoost models using RAPIDS and predicting component failures 3. Time series data component failure prediction using LSTM models with Keras/TensorFlow 4. Autoencoders for anomaly detection ■By agreeing to the contents described in "Regarding Personal Information Protection," we will use your information within the scope of the intended purpose. - Regarding Personal Information Protection https://www.hitachi-ac.co.jp/utility/privacy/ - Purpose of Use 1. Information on events, seminars, and product/service offerings 2. Use for sales information regarding our services and campaign information via email *Please feel free to contact us. *Please refer to the Digital Transformation (DX) course curriculum. *Please refer to the Manufacturing course curriculum. *Also, please take a look at our company brochure.
Price information
¥93,500 (including tax)
Price range
P2
Delivery Time
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Applications/Examples of results
- This course will be held from 10:00 AM to 5:30 PM. - Please create an NVIDIA Developer Program account and be prepared to log in by the day of the event at the following URL: https://courses.nvidia.com/join. - Please ensure you have a PC environment that allows the use of Google Chrome for participation. - If you are applying for the online training (virtual classroom), please make sure to confirm your connection in advance. 【Connection confirmation here】 https://www.hitachi-ac.co.jp/pdf/service/opcourse/VirtualClassroom/d_vc_flow.pdf
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Company information
With the three pillars of "Consulting," "Training," and "Training Management," we provide comprehensive support for our clients' human resource development. For many years, we have been committed to offering effective and efficient training, as well as highly specialized training, utilizing IT. Moving forward, we will consolidate and integrate the achievements (strengths) of our training institutions to expand and enhance training services that respond to trends in society across various fields, including IT, OT*, and management/business. *OT: Operational Technology (Control and Operational Technology) *Manufacturing Training System https://www.hitachi-ac.co.jp/service/opcourse/theme/making.html