STAR*NET Certification October 2026
type: Product
description: STAR*NET Online Training Please join us this fall for a MicroSurvey STAR*NET Certification online training session. This course will prepare you to use most aspects of STAR*NET. Attendees at this session will gain experience using converters, setting up a STAR*NET project, selecting or computing appropriate apriori values (Instrument Settings), will discuss field procedures and will practice a variety of troubleshooting techniques. Techniques will be practised using total station, RTK GNSS, static GNSS and levelling data but the principles learned will apply regardless of the type of sensor your organization uses. There will be a link to video recordings of past classes included in the materials page, so students can either preview or review the sessions at their leisure. If you are concerned that you may miss one session this is an attractive option. There will be 16 hours of online instructional time. The training is spread over 2 separate weeks. There is an introductory session to show how the online training tools will work. Sample files and PDF manuals will be provided. No long distance charges will apply, as we will transmit audio over the internet. A PDF Certificate of completion will be mailed at the end of the course. Topics: Tim McCall, the certified instructor engaged for this event is a long time user of STAR*NET and related products who specializes in geodetic topics and the use of GNSS technology. Tim provides a wealth of background knowledge and a new perspective on using STAR*NET to combine all types of data and resolve geospatial problems. Tim is the author of STAR*NET 6: Combining Data, a course offered at our Online School. This program will cover most aspects of using STAR*NET and will cover strategies and techniques for working with levelling data, conventional traverse data and GNSS data. Pick here for a more detailed list of topics. Attendees who complete the course will be prepared to: Configure STAR*NET for a range of equipment types Derive …
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