Upcoming Events

This online course introduces the basic functionalities of KNIME Analytics Platform.

Mode: Interactive learning sessions and exercises, which are assigned at the end of each session and discussed at the beginning of the following session.
Who: This course has been designed for KNIME newbies who wish to know more about the basic functionalities of the platform. The four one-hour online lessons stretching over four weeks are ideal for aspiring KNIME experts whose time is limited.
Duration: One hour per week over 4 weeks, plus a one 15-minute course at the end
Location: Online
Dates: May 9, May 16, May 23, May 30, June 6 always at 6pm CET
Price: EUR 250

KNIME is hosting a Course for KNIME Analytics Platform in Zurich, Switzerland on May 22-23, 2018.

Course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows.

Data visualization is a powerful part of data science and advanced BI. It allows you to not only see hidden patterns in your data, but also communicate the results more clearly and efficiently.

You're welcome to join this workshop on data visualization techniques. Jeany from KNIME will demonstrate how to efficiently summarize data groups or data transitions in a composite interactive and controlled view from within KNIME Analytics Platform as well as from a web browser. It will be a bit like a learnathon - after a brief introduction to the nodes and techniques, we'll work in small teams on use cases and guided exercises.

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.

The KNIME Analytics Platform Introductory Course focuses on introducing KNIME to beginners and people that are first touching workflow-based systems. It covers everything from installing KNIME, to learning key words and concepts, through to creating a simple workflow, analyzing the results, and deploying it. It's designed for those taking their very first steps into the world of data analytics and is ideal for those who have been using tabular or scripting-based tools and simply want to up their data blending and wrangling, or analytics capabilities.

Our partner Atos is hosting a meetup in London where you can build your own sentiment analysis application.

Interested in knowing what your customers, users, contacts, or relatives really think about you?

Find out, by building your own sentiment analysis application. In this workshop we'll work to build this type of application step by step. That is: data access, text cleaning, stemming, dictionary tagging, and text visualization techniques.

We'll also reserve the last 30 minutes of the workshop for a Q&A session with Vincenzo, one of the authors of the book “From Words to Wisdom” which is all about text mining. So, if you have a burning question about text mining, this will be your chance to ask the expert!

This course dives into the details of KNIME Server and KNIME WebPortal and discusses 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 and illustrated by means of interactive sessions and hands-on exercises.

Attendees learn 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 meta-nodes, share meta-nodes, execute workflows remotely and from the KNIME WebPortal, and how to schedule report and workflow executions, and more.

The course is designed not only for customers, partners, and the community, but also for anyone interested in finding out more about the KNIME commercial platform and its functionalities.

Extend your stay in by attending the KNIME Analytics Platform Introductory Course on June 4. We're also hosting a user meetup (where you'll learn about sentiment analysis) on June 5.

KNIME is hosting a one day IoT Analytics Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on June 11, 2018.

Sensors, machine-to-machine, and network data will play a leading role in analytics as the Internet of Things becomes a reality. In this course you are introduced to the most important methodologies, algorithms and ideas in IoT Analytics. You will learn to access sensor-based data sources, understand the fundamentals of digital signal processing, realize the importance of smart feature engineering, and use advanced methodologies to uncover underlying patterns or concepts contained in IoT data streams. All exercises are based on real-world IoT datasets.

Who should attend: Data scientists, signal processing engineers, statisticians, mathematicians, computer scientist and information technology professionals who need to get started with IoT Analytics and want to make better use of their data.

KNIME is hosting a Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on June 12-13, 2018.

Course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows.

KNIME is hosting a Course for KNIME Server at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on June 14, 2018. We recommend combining this course with the 2-day Course for KNIME Analytics Platform held June 12-13, 2018.

Course for KNIME Server dives into the details of KNIME Server and KNIME WebPortal and discusses 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 and illustrated by means of interactive sessions and hands-on exercises.

Attendees learn 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 meta-nodes, share meta-nodes, execute workflows remotely and from the KNIME WebPortal, and how to schedule report and workflow executions, and more.

The course is designed not only for customers, partners, and the community, but also for anyone interested in finding out more about the KNIME commercial platform and its functionalities.

KNIME is hosting a Big Data Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on June 15, 2018.

This one day Big Data Course for KNIME Analytics Platform focuses on processing and mining databases with Hadoop and Spark through KNIME. Learn how to interact with these tools based on an example: eliminating missing values by predicting their values based on other attributes.

Are you already familiar with the basics of the KNIME Analytics Platform and now want to learn more? What about learning how to control a workflow by using workflow parameters and loops? Or how to find the best parameter settings for your machine learning model automatically in a deep dive session of advanced machine learning? Then this is the perfect option to learn all those things and more in our KNIME Online Course for Advanced Users.

This event is co-organized with the DoData meetup group by Quantum Analytics.

Do you want to know what your customers, users, contacts, relatives really think?

Find out by building your own sentiment analysis application. In this workshop we will work together to build such an application, step by step, in KNIME Analytics Platform. That is: data access, text cleaning, stemming, dictionary tagging, text visualization and machine learning techniques.

Questo Learnathon è organizzato in partnership con Miriade Srl.

Perché un Learnathon?

Il learnathon è un evento gratuito aperto a tutti. E’ a metà strada tra un hackathon e un workshop: è un workshop perché si impara di più sul processo di lavoro del data scientist - dall’accesso al dato al data blending, dalla preparazione del dato al training del modello, dall’ottimizzazione alla fase di test fino al deployment. Ma è anche un hackathon, perché si lavora in gruppi, attraverso esercizi guidati, per mettere a punto una soluzione basata su un workflow.

KNIME is hosting a one day IoT Analytics Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on October 8, 2018.

Sensors, machine-to-machine, and network data will play a leading role in analytics as the Internet of Things becomes a reality. In this course you are introduced to the most important methodologies, algorithms and ideas in IoT Analytics. You will learn to access sensor-based data sources, understand the fundamentals of digital signal processing, realize the importance of smart feature engineering, and use advanced methodologies to uncover underlying patterns or concepts contained in IoT data streams. All exercises are based on real-world IoT datasets.

Who should attend: Data scientists, signal processing engineers, statisticians, mathematicians, computer scientist and information technology professionals who need to get started with IoT Analytics and want to make better use of their data.