Data Science Learnathon: From Raw Data to Deployment

- Atos, Regent's Place, 1 Triton Square, Kings Cross, London NW1 3HG, UK

This will be a Learnathon kind of workshop! During this workshop we will cover the whole data science cycle, from the raw data to the final application on a production machine. That is: data access, data blending, data preparation, model training, optimization, testing, and finally deployment. 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.

Register Now

We will provide some 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.

Here's a more detailed agenda of the event.

  • 6:00-6:20 PM Reception, with food & drinks served
  • 6:20-6:30 PM Welcome by Atos
  • 6:30-6:50 PM Introduction to KNIME Analytics Platform
  • 6:50-7:10 PM Presentation: The Data Science Cycle: From raw data to deployment
  • 7:10-7:20 PM Data sets & task presentations; group formation
  • 7:20-10:00 PM Let's work & learn!
  • 10:00 PM Networking

Are you ready to learn? Then sign up for the course right here!