KNIME Analytics Platform for Data Scientists: Basic, 1-Day Course

Quantum Analytics AG

Hands-on course providing  introduction to KNIME Analytics Platform. 
Day 1 (Basics) of 2-day course.

Technopark Zürich

Thank you for registering! We look forward to seeing you on May 11th.

This course is designed for those who are just getting started on their data science journey with KNIME Analytics Platform. It starts with a detailed introduction of KNIME Analytics Platform - from downloading it through to navigating the workbench. The course then introduces you to KNIME Analytics Platform covering the whole data science cycle from data import, manipulation, aggregation, visualization, model training, and deployment. Find out how to integrate external tools like Python, R, Google Sheets, and others. And lastly, learn how to export your data and create a report for sending to your colleagues. During the course there’ll be hands-on sessions based on real-world use cases.NOTE: This course replaces our previous two-day KNIME Analytics Platform Course, which is now split into two one-day courses - [L1-DS] KNIME Analytics Platform for Data Scientists: Basics and [L2-DS] KNIME Analytics Platform for Data Scientists: Advanced. Please be sure to register for both courses!Price CHF 850 (incl. 7.7% MwSt.)

Agenda:9:00 – 9:30 Registration, Coffee9:30 – 10:00	 Introduction to KNIME:Introduction / The KNIME Workbench / Preview of the “Next Best Offer” Workflow10:00 – 10:45 Importing Data:Data Source Node / Reading Files / Connecting to a Database10:45 – 11:00	Break	11:00 – 12:00	Data Manipulation &amp; Data Aggregation:Data Integration (Join &amp; Concatenate) / Data Manipulation Nodes / Data Aggregation (GroupBy)12:00 – 13:00	Lunch13:00 – 13:45	Data Visualization:Visualization Nodes / Interactivity / Interactive View Nodes13:45 – 14:30	Data Mining I:Process Overview / Learner/Predictor Motif / Creating Test and Training Sets / Classification Problem &amp; Decision Tree / Regression Problem &amp; Linear Regression14:30 – 15:00	Data Mining II:Clustering &amp; K-means / Python and R Integration15:00 – 15:15	 Break15:15 – 16:15	Data Export &amp; ReportingFile Writer Nodes / Database Write, Update / Reporting16:15 – 17:00	Summary &amp; Catch-upSummary of Materials Covered / Q&amp;A Session

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