Authors: Giuseppe Di Fatta (University of Reading, UK) and Stefan Helfrich (KNIME)
Are you an expert in KNIME Analytics Platform? There is now an official way to answer this question and share it with the world: You can test your KNIME proficiency with a new certification program developed by a collaboration between academia and industry.
Professional certifications are particularly useful in the employment process to help identify key skills relevant to the job profile sought by employers. They facilitate matching the demand for skills with the offer at an earlier stage and also promote the need for the right skills. They help prospective applicants to understand the requirements in the current job market to plan their training and development more effectively. Employers can also use certifications to engage current employees in Continuous Professional Development (CDP) relevant to critical needs. While Higher Education degrees are evidence of a solid knowledge of a subject area (e.g., BSc Computer Science, MSc Data Science), certification programs tend to focus on very specific expertise and skills on industry-relevant tools and processes. Certification programs can help to ensure the right competence level is clearly identified and communicated. Certification tests are used to assess skills and knowledge for this purpose.
Today, skills in the field of data science, machine learning, and analytics are in more demand than ever. KNIME Analytics Platform is one of the leading platforms.The Data Science with KNIME Software certificates from the KNIME Certification Program are testimony of your proficiency in the open source platform for data driven innovation: they show your ability to develop, execute and deploy data analytics projects. Certificate-holders will boost their professional credibility; employers will more easily identify the right candidates to gain a competitive advantage.
About the collaborators
KNIME has teamed up with the University of Reading to develop the KNIME Certification Program. The motivation was to draw on the experience and know-how from academia and apply it to build an effective certification program. With research expertise in Data Science, Machine Learning, Big Data Analytics, and High Performance Computing for Computational Science, the Department of Computer Science of the University of Reading, headed by Dr. Giuseppe Di Fatta, was an ideal partner. The University of Reading awarded their first degree in Computer Science exactly 50 years ago in 1969. The Department of Computer Science has many years of experience in teaching Data Analytics, Data Mining, and Machine Learning, and moreover they have adopted KNIME Analytics Platform in teaching Data Analytics and Data Mining for over 10 years at undergraduate level and more recently at postgraduate level as well.
KNIME Certification Program
The certification program will consist of five levels (L1 to L5). Each level highlights a person’s expertise with different aspects and practical skills on KNIME Software as well as most current data science concepts and know how, such as data integration, data exploration, visualization, reporting, machine learning, and deployment of analysis workflows. We currently offer certificates for the first two levels of Data Science with KNIME Software: L1 and L2. To cater to every practitioner’s needs, we are in the process of specifying/defining different profiles for higher levels . While we will include profiles (and thus individual certification examinations) for a generalist data science professional, there will also be certificates covering more specific topics like text mining, big data applications and management of KNIME Server. Pass marks for the certification tests are at 70% (this is based on the grade boundary typically set in the UK undergraduate degree classification system for first-class honors degrees) and awarded certificates will be valid for 2 years. In this way employers can be reassured that an applicant with a KNIME Certificate is up to date with the latest developments in KNIME and in Data Science.
- Proficiency in KNIME Analytics Platform for ETL, Data Analytics, and Visualization within the KNIME Certification Program for Data Science
- Examination: 45 minute multiple-choice questionnaire
- Advanced proficiency in KNIME Analytics Platform and Basic Machine Learning within the KNIME Certification Program for Data Science
- Examination: 45 minute multiple-choice questionnaire and a data science project (up to 6 hours of work over one week)
How to study?
To prepare yourself for these certification exams, we recommend the following methods of study:
- KNIME E-Learning Course
- KNIME Online Courses for Beginners and Advanced Users
- KNIME User Training
- University of Reading Data Science courses at UG or PGT level (e.g., CS3DM16 and CSMDM16).
Where can I take the exam?
To celebrate the start of this certification program, the first set of examinations for L1 and L2 will be offered on March 22, 2019, in Berlin. The two certification examinations have undergone testing by a cohort of BSc Computer Science students (see this website for more details) before the formal launch in Berlin.
Sign up to take either the L1 or L2 examinations here.
About the authors:
Dr. Giuseppe Di Fatta, Associate Professor of Computer Science
Giuseppe joined the University of Reading (UK) in 2006 and has been the Head of the Department of Computer Science since 2016. After his graduation at the University of Palermo (Italy) he ventured into the academic world at EPFL (Lausanne, CH), ICSI (Berkeley, CA), ICAR-CNR (Italy) and at the beautiful University of Konstanz, where he joined the initial KNIME development team until the first release of KNIME 1.0 in 2006. He has been adopting KNIME to teach data analytics and mining for over 10 years. His research interests include data mining algorithms, distributed and parallel computing, and data-driven multidisciplinary applications..
Dr. Stefan Helfrich, Academic Alliance Manager
Stefan is responsible for academic relations at KNIME. Before, he was working as a Bioimage Analyst at the University of Konstanz, supporting users of the local light microscopy facility with image and data analysis. Already during that time he realized that it will be crucial for the job market that people need to build up the right set of skills, which also is a major motivation for him to teach data literacy skills (using KNIME).