Data Science Master with RapidMiner
The title of this learning path says it all. This track is pushing skills to an advanced level in machine learning, deployment, operationalization, data engineering, installation and administration.
To master data science is not an easy task but we think this learning path will help you quite a long way with it. We address all aspects which we think will be interest to a data scientist. This means we are not only going into advanced machine learning topics like ensemble methods or how to including scripting into your process design but we also address things like platform deployment, reporting, web services, time series analysis and the details of feature engineering.
If you complete this track and all its related certificates then you can say with confidence: "yes I am familiar with data science"
Sections
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Data Preparation Master
Data Engineering Master
Elective
Course
OpenThis course is about advanced methods of handling, preparing and enriching data. It addresses data cleansing but also processing of unstructured text data. Commonly known methods like loops and branches are discussed but also the use of variables, error handling and different options to use scripting.Data Engineering Master Certification
Elective
Certification Exam
OpenTake a quiz to verify your knowledge and understanding Data Engineering in RapidMiner -
Machine Learning Master
Machine Learning Master
Elective
Course
OpenThis course is all focused on machine learning and core data science topics. It covers advanced classification and regression models as well as time series handling, scripting and feature engineering. Model selection, validation and optimization are other key topics.Machine Learning Master Certification
Elective
Certification Exam
OpenTake a quiz to verify your knowledge and understanding of Machine Learning and RapidMiner -
Applications & Use Case Master
Applications & Use Cases Master
Elective
Course
OpenWhen machine learning and data science is addressed it is often overlooked that there is a great gap between producing a good model and having it run in production. No matter if it is used to do a scoring on a weekly basis or trigger by an action in real time, the challenges of monitoring, model deployment and management are always important to consider. With deployment often the visual representation of result is a big topic so we are addressing web apps here as well.Applications & Use Cases Master Certification
Elective
Certification Exam
OpenTake a quiz to verify your knowledge and understanding of Applications and Use Cases in RapidMiner Studio and AI Hub at the Master level. -
Optional - Administration
Platform Administration Master
Elective
Course
OpenThe Platform Administration Master is focused on classical administration knowledge such as installation and configuration of the RapidMiner AI Hub and its components. Other topics which are addressed are security, scalability, job scheduling, user management, license management, extensions and connections.Platform Administration Master Certification
Elective
Certification Exam
OpenTake a quiz to verify your knowledge and understanding of how to administer the entire RapidMiner platform in an enterprise environment.
We offer free access to micro-modular learning content through our Catalog.
The content is grouped into the general topics, 'Applications & Use Cases' 'Machine Learning', 'Data Engineering' and 'Administration and Deployment’. These topics form the basic structure for the majority of our Courses. They are designed with our users' role-based learning requirements in mind.
The same structure is also used for naming the Certification Exams which we provide to you for assessment and proof of your skills and to celebrate your learning progress.
For additional guidance, we have created Learning Paths.