RapidMiner Certification program helps you to kickstart your career in data science. If you are looking to get into the data science field, or want to stand out against the competition, RapidMiner Certification can be key. The certification allows you to develop and validate the essentials skills required by data science field such as data engineering, machine learning, applications and use cases.
The RapidMiner certifications can enhance your profile with verified skills by professional bodies. On completion, you will be awarded a certification file for framing, but more importantly you will receive a badge. The RapidMiner certification badges are enriched with meta data following the open badge standard. This means they can be verified and you can share them through business network sites and social media to get acknowledgment. You are proven to be embedded with data science knowledge and skills. Then, you can say with confidence: “Yes, I am familiar with data science!”
The RapidMiner Certification program offers role-based certification for different knowledge domains and levels. To be certified as a RapidMiner Data Scientist, you will need to pass 7 certification exams offered by RapidMiner as below:
In the Professional level, you need to complete 3 certification exams:
The Professional level path covers the full breath of knowledge required to succeed with Data Science for beginners 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.
In the Master level, you need to complete 2 certification exams:
The Master level is entering an intermediate level in data engineering and machine learning.
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 cover the main aspects which a data scientist should have. This means we are going into advanced data engineering and machine learning topics like ensemble methods, scripting, time series analysis and the details of feature engineering.
In the Advance level, you need to complete 2 certification exams:
The Advance level is pushing skills to an advanced level in deployment, operationalization, installation and administration.
We address all aspects which we think will be interest to a data scientist. This means we are not only going into more operationalization topics such as platform deployment, reporting, web services, and administration. If you complete this track and all its related certificates then you can say with confidence: “Yes, I am familiar with data science!”
We offer courses to prepare you to be certified!
Applications and Use Cases Professional
Data Engineering Professional
Machine Learning Professional
Data Engineering Master
Machine Learning Master
Application and Use Cases Master
Platform Administration Master
Value-added services for exam preparation:
- Sample exam questions
- Exam tips and tricks