KNIME has launched the third edition of the Machine Learning student challenge at the University of Milano-Bicocca with sponsorship by The Information Lab.
What is the ML student challenge?
The challenge encourages student data scientists to use KNIME Analytics Platform to build visual workflows for training and deploying machine learning based solutions.
Competition deliverables include KNIME workflows and a technical report. The assessment committee jury will appraise the report for technical merit, clarity of expression, and communication of ideas. The workflows will also be evaluated for complexity, cleanness, and usability.
The three finalist teams will be invited to present their projects at a KNIME Data Connect event in Italy in May with the winning team being announced during the event.
Students develop real-world skills using real-world examples
This year's challenge topic focuses on a banks’ loan approval process and is based on the Kaggle Loan Approval dataset. Students will form teams of three and will explore and transform the data, and train and deploy machine learning models, to minimize the risk of granting loans to customers likely to default.
One of the best ways to gain industry-level practical knowledge is to participate in data science competitions. The Machine Learning Challenge is designed by Prof. Fabio Stella and KNIME to implement and experience the basic concepts and best practices in data science applications.
The challenge concentratesfocuses on real world problems so students can have experience working on the types of challenges they may experience in industry. Last year’s challenge encouraged teams to train a machine learning model to identify smokers.
KNIME and The Information Lab
This year The Information Lab – a European consulting company – will sponsor the challenge. They will participate in the project evaluation and will sponsor the internship for the winning team in their office in Madrid.
KNIME, the open source data science company, will participate again as part of the assessment committee and as coordinator of the challenge logistics.
Internship at The Information Lab office in Madrid
The 1st-ranked team will be awarded a summer internship at The Information Lab’s office in Madrid. The 1st and 2nd-ranked winners are also offered a place on a data science specialization course.
All three winning teams will receive a digital badge and trophy. Lastly, all three teams will be given the chance to publish their work in Low Code for Data Science, KNIME’s community publication on Medium.
The experience has been truly wonderful and incredibly stimulating on both a professional and personal level. I have gained a wealth of practical knowledge through working on projects, explored innovative topics, and had the privilege of collaborating with inspiring colleagues in a dynamic environment.
Sergio Verga, Masters student in Data Science at the University of Milano-Bicocca, and member of the winning team of the Machine Learning Challenge, Spring 2024.
KNIME Educators Alliance collaborates regularly with educators to compile tailored resources, offer guidance and provide support for teaching data science with KNIME.