Level: Beginner to Intermediate
Prerequisite: None
The easiest way to begin making practical and profitable use of machine learning in your organization is with no-code/low-code machine learning. The KNIME Analytics Platform is an easy-to-learn, easy-to-use, open source option that is a great place to start. Its wealth of extensions and its ability to use Python and other languages within the environment ensure that you won’t outgrow it.
In this course, we’ll navigate the entire machine-learning lifecycle, from data ingestion to data integration and preparation to modeling and beyond. Throughout, there will be an emphasis on best practices in terms of effective machine learning applications and the efficient use of KNIME. KNIME will provide a practice environment, but much of what you learn can be applied to other platforms as well.
You Will Learn
- The advantages of using a codeless environment with your team
- How to ingest various data sources into KNIME
- How best to leverage the wealth of practice examples in the KNIME Hub
- Data preparation and integration in KNIME
- Modeling basics in KNIME
- How to migrate solutions out of KNIME
Geared To
- Anyone who is interested in machine learning concepts and wants an easy-to-learn environment in which to practice
- Data scientists who are interested in KNIME Analytics Platform
- Data engineers who are interested in KNIME Analytics Platform
- Analytics leaders who want an opportunity to see and practice machine learning concepts in action
No prior knowledge of KNIME is required.
Laptop Setup
Students must bring their laptops to class.
Setup:
Instructions will be emailed to registrants prior to the event to prepare your laptop before the conference.
There is no time allotted in class for laptop preparation.
* Enrollment is limited to 40 attendees.