Data Science Professional with RapidMiner

Te Professional level path covers the full breath of knowledge required to succeed with Data Science for beginners and intermediate users.

The starting point of this path is an introduction to the terms and methodologies of Analytics, Machine Learning, Data Science and AI. It covers some of the most commonly required skills in machine learning, including 'mapping problems to use cases' and 'how to do data extraction, transformation and loading'. Also, we introduce you to the most used machine learning algorithms and tech you the skills to get started with text and web mining.  
We obviously keep banging the "Validation-drum" because without proper validation nothing in supervised machine learning can be considered properly done.

Sections

  • Applications & Use Cases

    Applications & Use Cases Professional

    Elective
    Course
    AI, machine learning and data science can become a competitive advantage and so everyone is interested to see if they can be applied on their problems. Identifying good problems and mapping them to machine learning types is the key step here and since that also requires some general understanding of the frequent terms used, we cover and introduce those basics as well.
    Open

    Applications & Use Cases Professional Certification

    Elective
    Certification Exam
    Take a quiz to verify your knowledge and understanding of Applications and Use Cases in RapidMiner Studio and AI Hub at the Professional level.
    Open

  • Data Preparation & Engineering

    Data Engineering Professional

    Elective
    Course
    Data Engineering is about all aspects of data and so is this course. We address how to access and load data, how to transform it and how to do calculations. Handling and joining multiple data tables is topic which is covered here as well as data types and how to convert them. Finally we address the basics of handling text data.
    Open

    Data Engineering Professional Certification

    Elective
    Certification Exam
    Take a quiz to verify your knowledge and understanding Data Engineering in RapidMiner
    Open

  • Machine Learning

    Machine Learning Professional

    Elective
    Course
    The topics of this course form the foundation of data science and machine learning. Classification, clustering and regression and the relevant common models are addressed here. Further, validation, scoring, weights and are a part of this course and we have also added in association analysis.
    Open

    Machine Learning Professional Certification

    Elective
    Certification Exam
    Take a quiz to verify your knowledge and understanding Machine Learning in RapidMiner
    Open
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Learning Path Runs: Feb 11th 2022

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RapidMiner Academy Overview

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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.

Go to Catalog