What is a learnathon? It's between a hackathon and a workshop. It's like a workshop because we'll learn more about the data science cycle - data access, data blending, data preparation, model training, optimization, testing, and deployment. It's like a hackathon because we'll work in groups to hack a workflow-based solution to guided exercises. The tool of choice for this learnathon is KNIME Analytics Platform.
KNIME Analytics Platform is an open, open-source, GUI driven, data analytics platform, that covers all your data needs from data import to final deployment. Being open, KNIME Analytics Platform offers a vast integration and IDE environment for R, Python, SQL, and Spark.
After an initial introduction to the tool and to the data science cycle, we will split in groups. Each group will focus on one of three aspects of the data science cycle:
- Group 1. Working on the raw data. Data access and data preparation.
- Group 2. Machine Learning. Which model shall I use? Which parameters?
- Group 3. I have a great model. Now what? The model deployment phase.
We will provide a few datasets, jump-start workflows and final solutions for the proposed tasks, and of course data science experts. Please bring your own laptop with KNIME Analytics Platform pre-installed. To install KNIME Analytics Platform, follow the instructions provided in these YouTube videos:
If you would like to get familiar with KNIME Analytics Platform, you can explore the content of our E-learning course.
Please also download the workshop material (jump-start workflows and instructions) from here. We will import this material during the learnathon.
- 18:00 – 18:20 - Reception
- 18:20 – 18:30 - Welcome by Dominique Genoud (Professor, HES-SO Valais-Wallis)
- 18:30 – 18:50 - Introduction to KNIME Anayltics Platform (Jérôme Treboux, PhD Student, HES-SO Valais-Wallis)
- 18:50 – 19:10 - Presentation: The Data Science Cycle: From raw data to deployment (Rosaria Silipo, KNIME)
- 19:10 - 19:20 - Data sets and task presentation; group formation
- 19:20 - 22:00 - Let's work and learn!
- 22:00 - Networking