RapidMiner provides free Data Science courses and certification online – Professional and Master level.

The RapidMiner Academy provides comprehensive courses in Data Science with two learning paths, Data Science Professional and Master.

Each learning path consists of three courses + certifications in:

Applications and Uses Cases
Data Engineering
Machine Learning

In total, to reach master level, you need to complete 6 courses and pass 6 certification exams – all are free. Exams are time limited to 60 minutes and contain 20 multiple choice questions. (There is 1 additional course Platform Administration Master – to reach the ultimate grand master level)

Why do these courses?

If you’d like to learn how a machine learning model works, how parameters effect a model and how to build validated machine learning models (very important step!), then these courses are for you.

Courses are a combination of videos and learning materials. General format provides concepts first and then application of concepts with RapidMiner.

Machine Learning Professional content: Unsupervised vs Supervised Learning, KNN, Normalisation, Linear and Logistic Regression, Naive Bayes, Decision Tree, Neural Nets, Confusion matrix, Validation, Scoring, Correlation, Clustering, Association Analysis, Feature Engineering, Auto ML and deployment.

Machine Learning Master content: Ensembles, Bagging, Random Forest, Boosting, Stacking, Support Vector Machines, Deep Learning, Cross Validation, Parameter Optimisation, Model Performance, Model Selection, Feature Generation, Feature Selection, PCA, Time-Series and Integrating RapidMiner with Python and R.

Each certification, provides a badge that you can share/add to your LinkedIn account.

The dashboard provides metrics on courses and certifications completed.

How to get started?

Step 1: Download RapidMiner Studio open source version

Step 2: Start with Data Science Professional learning path and sign up!

Alternatively, if your preference is instructor-led live online training courses, please click on the link or send us your details below.

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