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KNIME Spring Summit 2020 - Online

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Visit our website for all the information and regular updates!


We would have loved to have met everyone in Berlin but unfortunately that isn’t possible this year. We’ve therefore done our best to move the Summit online and have just published a revised program. Despite this situation, we’re really looking forward to connecting all those home offices out there and creating a special summit spirit together with the KNIME community.

Overview

Starting with a week of courses and talks, our digital summit format will continue throughout the month of April with presentations by KNIME customers and users, as well as workshops.

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The Virtual KNIME Summit

Welcome to our virtual conference room. The following KNIME talks, including the keynote presentation by Dean Abbott, will be run as a free webinar for everyone to attend1.

Wednesday, April 1, 3:00 PM - 6:00 PM (CEST) - Berlin.

  • The Future of Data Science: Integrated Deployment by Michael Berthold - slides, video
  • Create and Productionize Data Science Solutions by Cynthia Padilla - slides, video
  • Community, Partners, and Teaching: the KNIME Family by Rosaria Silipo and Paul Treichler - Community/Education slides, Partner slides, video
  • What's New and Cooking in KNIME Analytics Platform by Bernd Wiswedel - slides, video
  • What's New and Cooking in KNIME Server by Jim Falgout - slides, video
  • Keynote Presentation by Dean Abbott (Smarter HQ) - video

Talk to the KNIMErs: Q&A Sessions

The following sessions will be run as a free webinar for everyone to attend1.

Thursday, April 2, 3:00 PM - 6:00 PM (CEST) - Berlin.

  • 3:00 PM - Workflow Doctor KNIME Analytics Platform by Iris Ada and the KNIME Team
  • 4:00 PM - Workflow Doctor KNIME Server by Roland Burger and the KNIME Team
  • 5:00 PM - KNIME Developer Session by Bernd Wiswedel and the KNIME Team

These sessions are intended to be very interactive – think of the coffee breaks at a physical KNIME Summit. That means we need your questions! You will be able to enter your questions or vote up other questions to get them answered by the experts. If we run out of time, we will take the remaining questions and get them answered later.


KNIME Courses in the Online Classroom

Our virtual classroom doors open on March 30. Courses are split into four one-hour sessions. In between these sessions you'll have time to work on some exercises - during which we'll be available to answer questions and help you. At the end of each break, we'll present the solution workflow2.

Monday, March 30:

[L1-DS] KNIME Analytics Platform for Data Scientists: Basics

Time (Europe class): 9:30 AM - 5:15 PM (CEST) - Berlin

Time (Americas class): 11:30 AM - 7:15 PM (EDT) - New York

Designed for those who are just getting started on their data science journey with KNIME Analytics Platform. The course starts with a detailed introduction of KNIME Analytics Platform - from downloading it through to navigating the workbench. It then introduces you to KNIME Analytics Platform covering the whole data science cycle from data import, manipulation, aggregation, visualization, model training, and deployment. Learn how to export your data and create a report for sending to your colleagues. View (CEST) agenda. View (EDT) agenda.

[L1-DW] KNIME Analytics Platform for Data Wranglers: Basics

Time: 9:30 AM - 5:15 PM (CEST) - Berlin

Designed for those who are just getting started on their data wrangler journey with KNIME Analytics Platform. The course starts with a detailed introduction of KNIME Analytics Platform. It focuses on accessing, merging, transforming, fixing, standardizing, and inspecting data from different sources. It dives into data cleaning and aggregation, using methods such as advanced filtering, concatenating, joining, pivoting, and grouping. View agenda.

[L4-BD] Introduction to Big Data with KNIME Analytics Platform

Time: 9:30 AM - 5:15 PM (CEST) - Berlin.

Focuses on how to use KNIME Analytics Platform for in-database processing, predicting values with KNIME, and writing/loading data into a database. Get an introduction to the Apache Hadoop ecosystem and learn how to write/load data into Hadoop. Learn about the KNIME Spark Executor, preprocessing with Spark, machine learning with Spark, and how to export data back into KNIME/Hadoop. View agenda.


Tuesday, March 31:

[L2-DS] KNIME Analytics Platform for Data Scientists: Advanced

Time (Europe class): 9:30 AM - 5:15 PM (CEST) - Berlin

Time (Americas class): 11:30 AM - 7:15 PM (EDT) - New York

Builds on the KNIME Analytics Platform for Data Scientists: Basics by introducing advanced data science concepts. Learn all about flow variables, different workflow controls such as loops, switches, and error handling. Explore advanced data mining techniques and learn how to create models in KNIME Analytics Platform. View (CEST) agenda. View EDT agenda.

[L2-DW] KNIME Analytics Platform for Data Wranglers: Advanced

Time: 9:30 AM - 5:15 PM (CEST) - Berlin

Builds on the KNIME Analytics Platform Course for Data Wranglers: Basics by introducing advanced concepts for building and automating workflows. Learn all about flow variables, different workflow controls such as loops, switches, and how to catch errors. And lastly learn how to visualize your data and look beyond data wrangling towards data science, training your first classification model. View agenda.

[L3-PC] KNIME Server Course: Productionizing and Collaboration

Time: 9:30 AM - 5:15 PM (CEST) - Berlin.

Dives into the details of the commercial KNIME Server and KNIME WebPortal - discussing them from three different points of view: the power user, the administrator, and the end user. All tools and features designed for each one of these three personas are shown in detail. Find out how to exchange workflows and data between the server and the client, how to take advantage of the many server dedicated nodes and features when implementing a workflow, how to set access rights on workflows, data, and metanodes, share metanodes, execute workflows remotely and from the KNIME WebPortal, how to schedule report and workflow executions, and more. View agenda.


Thursday & Friday, April 2 & 3:

The following courses are run over two half days in order to compensate for both the EU and US time zones.

[L4-ML] Introduction to Machine Learning Algorithms

To cater for high demand, this course will be starting at the following times on both April 2 and April 3. Select which time you'd like to join when you register.

9:00 AM - 1:00 PM CEST - Berlin.

3:00 PM - 7:00 PM CEST - Berlin (9:00 AM - 1:00 PM EDT - New York).

Introduces you to the most commonly used machine learning algorithms in data science applications. This course will explore different supervised algorithms for classification and numerical problems such as decision trees, logistic regression, and ensemble models. We'll also look at recommendation engines and neural networks and investigate the latest advances in deep learning. In addition, we'll examine unsupervised learning techniques, such as clustering with k-means, hierarchical clustering, and DBSCAN. We'll also discuss various evaluation metrics for trained models and a number of classic data preparation techniques, such as normalization or dimensionality reduction. View (9AM) agenda. View (3PM) agenda

[L3-PC] KNIME Server Course: Productionizing and Collaboration

This course is being offered at the following time:

Time: 3:00 PM - 7:00 PM CEST - Berlin (9:00 AM - 1:00 PM EDT - New York).

Dives into the details of the commercial KNIME Server and KNIME WebPortal - discussing them from three different points of view: the power user, the administrator, and the end user. All tools and features designed for each one of these three personas are shown in detail. Find out how to exchange workflows and data between the server and the client, how to take advantage of the many server dedicated nodes and features when implementing a workflow, how to set access rights on workflows, data, and metanodes, share metanodes, execute workflows remotely and from the KNIME WebPortal, how to schedule report and workflow executions, and more. View agenda.

Register now

Monday, April 6:

[L1-DS] KNIME Analytics Platform for Data Scientists: Basics

Time: 9:30 AM - 5:15 PM (CEST) - Berlin. Access to this course is via a dedicated ticket, when you register.

Designed for those who are just getting started on their data science journey with KNIME Analytics Platform. The course starts with a detailed introduction of KNIME Analytics Platform - from downloading it through to navigating the workbench. It then introduces you to KNIME Analytics Platform covering the whole data science cycle from data import, manipulation, aggregation, visualization, model training, and deployment. Learn how to export your data and create a report for sending to your colleagues. View agenda.

Tuesday, April 7:

[L2-DS] KNIME Analytics Platform for Data Scientists: Advanced

Time: 9:30 AM - 5:15 PM (CEST) - Berlin. Access to this course is via a dedicated ticket, when you register.

Builds on the KNIME Analytics Platform for Data Scientists: Basics by introducing advanced data science concepts. Learn all about flow variables, different workflow controls such as loops, switches, and error handling. Explore advanced data mining techniques and learn how to create models in KNIME Analytics Platform. View agenda


Keep Connected: Online Learning in April

We want to keep you, the community, connected throughout the month of April. Dial in to see presentations given by our summit speakers and take part in virtual workshops. Sign up here to be notified as soon as dates are released.

User Presentations

Speakers invited to the on-site summit are hosting webinars during the month of April. A complete program is listed on our Extended KNIME Summit page.

  • Conformal Prediction: Enhanced Method for Understanding the Prediction Quality. Artem Ryasik (Redfield)
  • Automatically Detecting Data Science Pitfalls in KNIME using KNIME. Gopi Krishnan Rajbahadur (Queen's University)
  • Bringing Data Manipulation from KNIME into TIBCO Spotfire. Maxime Guitet, Lionel Colliandre (Discngine)
  • Use of KNIME to Automate Data Transfer from Sharepoint to PerkinElmer Inventory. Fabio Rancati (Chiesi Farmaceutici)

Workshops

A selection of the workshops scheduled for the on-site summit will be run as webinars. Our online tutors have hands-on exercises that get discussed at the end of each webinar. A complete program, including links to register, is listed on our Extended KNIME Summit page.

  • Time Series Analysis Workshop - Corey Weisinger, Maarit Widmann (KNIME)
  • Behind the Scenes of Machine Learning - Kathrin Melcher, Rosaria Silipo (KNIME)
  • Working with the RDKit in KNIME Analytics Platform - Daria Goldmann, Greg Landrum (KNIME)
  • Text Mining on Biomedical Literature - Today: Topic Modeling - Martyna Pawletta (KNIME)
  • Deep Learning for Image Analysis - David Kolb, Benjamin Wilhelm (KNIME)
  • KNIME Text Mining with NER Modeling and Deep Learning - Julian Bunzel & Andisa Dewi (KNIME)
  • Sharing & Deploying Data Science with KNIME Server - Roland Burger, Marten Pfannenschmidt (KNIME)
  • Guided Labeling: Human-in-the-Loop Label Generation with Active Learning & Weak Supervision - Paolo Tamagnini, Adrian Nembach (KNIME)
  • Building a Drug Discovery Workflow in 8+1 steps with KNIME - Dora Barna, Norbert Sas (ChemAxon)
  • KNIME Big Data Workshop - Björn Lohrmann (KNIME)
  • GDPR Compliance through Advanced Anonymization Techniques - Artem Ryasik, Jan Lindquist (Redfield)


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