Nowadays, enterprises have a data enriched view on many areas of their business like finance, sales, or human resources. In many of these areas, specialized software tools exist that allow managers and planners to get the big picture, drill down through the details, and generate potential for insight-profit and optimization.
Nevertheless, regarding manufacturing and R&D data, there is a lack of such standardized and well-established tools or methods. Turning raw data of manufacturing or R&D into insight is a hard challenge that is not covered by such tools, mainly because it differs from sales or finance data. Oftentimes, such data is either very sparse and each experiment is executed under specific conditions, a case usually encountered in highly specialized R&D departments, or, regarding specific machine data, a torrent of data with low variance is generated and there is no easy way to interpret it without process and domain knowledge.
During this certification course, you will learn the basic concepts of data science for production and manufacturing data as well as the essential steps to get started. First, you get to know appropriate approaches and processes as well as different tasks you need to enact. Second, we present tools and languages to execute these tasks and get the most out of your data. Thereby, we focus entirely on the special challenges related to manufacturing and R&D data. During hands-on practical sessions, you work with these tools and analyse real-world data. This process is carried out by starting with cleansing, pre-processing and finally performing the analysis to identify patterns and hidden treasures within the data.
As a graduate of this certificate course, you know about the analytic processes and tasks that you need to enact to generate insights from your manufacturing and R&D data. Further, you are familiar with necessary tools and their application. Because you have worked with these tools on real-world data, you will gain not just the theoretical knowledge, but also practical experience.
Tip: Combine this course with any of our engineering courses to further your knowledge on Cyber-Physical Systems and Intelligent Robotics. For more information and courses to choose from, please click here.