Holistic applied AI in engineering – launch of the micro-degree

The online course series "Holistic Applied AI in Engineering" includes three modular online courses that provide an in-depth introduction to the application of machine learning and process informatics in production. After completing all the courses in the micro-degree, you will receive your transcript of records here. First, click the "Go to course/Enrol" button and then the "Your certificate" tile. There you can download your certificate.

In the 3 online courses of the Micro-Degree, you can expect

• Insight into the methods of Machine Learning and Deep Learning.
• Application of ML methods with Python scikit-learn.
• Application of recurrent deep learning methods with TensorFlow.
• Fundamental concepts for the correct implementation of Machine Learning.
• Development of a prototype pipeline for data collection.
• Data collection using OPC UA and MQTT.
• Storage and visualisation via a dashboard.
• Framework aspects such as methodological approaches and security aspects.

Upon completion of the micro-degree, you will be able to...

• explain various objectives – regression, classification, clustering and outlier detection – and the corresponding ML methods.
• apply and compare ML methods to practical examples.
• implement ML projects in the engineering sector.
• explain the difference between machine learning and deep learning.
• describe the elements and characteristics of recurrent neural networks.
• build and apply a neural network in TensorFlow using different layer concepts (RNN, LSTM, dense, dropout).
• describe interface protocols OPC UA and MQTT.
• build a pipeline for data collection, storage and visualisation.
• identify essential framework conditions to be considered from the perspective of safety and methodology.

To complete the micro-degree, learners must have completed the online courses Holistic Applied AI in Engineering – Machine Learning in Production, Deep Learning for Sequential Process Data, and Process Informatics. The transcript of records will be awarded to those who achieve at least 60% of the total score in all courses by completing the exercise tasks.