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: September 11, September 18, September 25, October 2, October 9 always at 6pm CEST
Price: EUR 250

Our trusted partner EPAM are hosting a KNIME Meetup in September in their offices in Poland. It's free and open for anyone who is interested in learning more about data science, or simply wants to meet and network with some like-minded people.

To begin with, there'll be a short introduction to KNIME Analytics Platform, followed by a couple of talks. Krzysztof Żarna, who helped plan the very first Polish Meetup in Poznan, will discuss machine learning in KPI management. Olgun Aydin, a Senior Data Scientist at EPAM, has a guided analytics use case to share.

After the presentations there'll be an informal networking session over pizza before the meetup comes to a close.

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.

Am Mittwoch, den 26.09.2018 ab 18.00 Uhr ist es soweit, die IHK Region Stuttgart lädt gemeinsam mit KNIME und DATATRONiQ zum KNIME Meetup nach Stuttgart ein. Die Veranstaltung findet im Rahmen der Themenwoche zur digitalen Zukunft und Innovation im Mittelstand „100 Stunden Morgen“ im Gebäude der Industrie- und Handelskammer Region Stuttgart in der Jägerstraße 30 statt.

We're hosting a series of meetups around sentiment analysis, involving NLP, machine learning, deep learning, and of course text processing.

These meetups - Sentiment Analysis: Deep Learning, Machine Learning, Lexicon Based? You Choose! - will be happening in the following cities:

• Boston on September 27: CIC Cambridge, Cloud City 14th Floor, 101 Main Street, Cambridge, MA (Thank you to CIC Cambridge for the sponsorship of the Boston location)
• New York on October 2: Microsoft Technology Center, 11 Times Square, New York, NY
• San Diego on October 4: Teradata, 17095 Via Del Campo Conference Room K02, San Diego, CA

Join us at the next Data Science Learnathon! This time on September 27, 2018, in Madrid, Spain.

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 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.

KNIME is hosting a Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on October 9-10, 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.

During this one-day, hands-on training you’ll learn to build interactive cheminformatics workflows using KNIME Analytics Platform and its Cheminformatics Extensions. This training contains several units where we'll cover a diverse set of topics such as data manipulation and interactive filtering, descriptors and fingerprints, machine learning and clustering, data set visualization and exploration. After completing this session you'll have a set of fully functional workflows and will have learned how to start from scratch to build your own.

Our trusted partner, Redfield, are hosting their first Meetup in Stockholm, Sweden with a focus on accelerated machine learning, customer intelligence, data anonymization, and inventory optimization - all with KNIME Analytics Platform.

Data blending, data cleansing, data visualization, and machine learning enhancement are all tasks you can do with KNIME - regardless of whether you're an experienced Python/R programmer or a business analyst - and at this meetup, you'll find out how.

KNIME is hosting a Course for KNIME Server at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on October 11, 2018. We recommend to combine this course with the 2-day Course for KNIME Analytics Platform held October 9-10, 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.

KNIME is hosting a Big Data Course for KNIME Analytics Platform at the AdvancedAnalytics.Academy offices in Stuttgart, Germany on October 12, 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.

KNIME is hosting a Course for KNIME Analytics Platform in Bern, Switzerland on October 15-16, 2018.

In this course we’ll take you through everything you need to get going - from installation, to navigating around the various sections, through to fully utilizing KNIME Analytics Platform. Learn how to read and manipulate data, data visualization techniques, and how to export and deploy workflows. We’ll explore advanced data mining techniques and generate reports based on KNIME workflows. Finally, we’ll dive into controlling workflows with Loops and Flow Variables. You’ll also get the chance to test everything you learn in the hands-on session. We’ll go through a full churn prediction use case and take a look into the future weather as well. This course nicely compliments the KNIME Server course. This course is designed primarily for those have little to no previous experience with KNIME, but is also useful for those who simply want to fine tune their knowledge.

KNIME is hosting a Course for KNIME Server in Bern, Switzerland on October 17, 2018. We recommend to combine this course with the 2-day Course for KNIME Analytics Platform held October 15-16, 2018.

In this course we’ll dive into the details of KNIME Server and KNIME WebPortal from three different points of view: data scientist, business analyst, and IT administrator. All tools and features designed for each of these personas will be shown in detail and illustrated through hands on exercises. You’ll 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 metanodes, share metanodes, execute workflows remotely and from the KNIME WebPortal, how to schedule workflow execution and to generate reports, and more. We’ll also make a workflow for the WebPortal so that non experts can use it.

We’ll use an example of a customer segmentation use case to show how the KNIME Server features can help you with many aspects of model building, data access, and deployment. This course nicely compliments the KNIME Analytics Platform Course and is designed not only for customers, partners, and the community, but also for anyone interested in finding out more about KNIME Server and its functionalities.