RWTH Certificate Course Data Scientist
Sustainable implementation of machine learning in production
Discover what Data Science is all about. You will learn basic methods of preprocessing data and will be able to evaluate them using artificial intelligence approaches. You will develop an understanding for the application of machine learning and master practical applications in production successfully.

Course Contents
▶ Preprocessing and provision of data for analysis
▶ Data Mining & Knowledge Discovery in Databases
▶ Artificial Intelligence and Deep Learning
▶ Machine learning with data from industrial practice
▶ Case study: Optimizing Industrial Applications with Machine Learning
Group of Participants
You are an engineer, decision-maker or head of department from the fields of production, manufacturing technology, automation, process technology, maintenance and quality management. The course is also aimed in particular at executives and (middle) management to acquire a basic understanding of terms such as „digital transformation“, „machine learning“ and „(Industrial) Big Data“.
Motivation
In the context of industrial manufacturing, continuous improvement of running processes is increasingly important, e.g. for predictive maintenance of machines or sustainable improvement of production processes.
Methodology
The course takes place on five consecutive days and ends with an exam. Course content is developed and consolidated in interactive lectures, group work, presentations and case studies.
Further information regarding the RWTH certificate course "Data Scientist"
On the first day of the course the following topics will be taught:
- Data-driven Factory
- Real-world Data from CPS and industrial Robots, Coping with real world Data in CPS and robotic Environments
- Pre-processing of Data (e.g. dimensionality reduction)
On the second day of the course the following topics will be taught:
- Data Acquisition and Storage
- Introduction to heuristics & rule-based Programming and Expert Systems & Business Intelligence (BI)
- Data Mining and Knowledge Discovery in Data-bases (KDD)
On the third day of the course the following topics will be taught:
- Practical Use Case: Data Mining with Production Data
- Introduction to Artificial Intelligence and Machine Learning
- Supervised & Unsupervised Learning
On the fourth day of the course the following topics will be taught:
- Reinforcement Learning and artificial Neural Networks
- Introduction to Use Case Scenario, building a first Solution for the Use Case
- Development of solutions and prediction model
On the fifth day of the course the following topics will be taught:
- Building a Solution for the Use Case
- Exam and discussion
- Awarding of Certificates