Virtual Classroom Training: Applied Method Development for GC & GC-MS

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Module 9 of the Complete GC & GC-MS and part 1 of The GC & GC-MS Clinic courses.

Course summary

Course approval

This course has been approved by the Royal Society of Chemistry (RSC) for purposes of Continuing Professional Development (CPD). RSC members and Community for Analytical Measurement Science (CAMS) members receive a discount of 10% for this course (membership number required).

What will you learn on this course?

This module looks at the method development process, the parameters to optimise and the order to do them in. How to validate the method and method optimisation are examined in detail. This knowledge, along with the basic knowledge of GC & MS acquired in previous modules is then put to the test in working out best techniques and methods in case studies.

Learning outcomes

  • You will learn strategies for method development.
  • You will learn how to optimise for sensitivity or to reduce carryover.
  • You will learn how to break the method down into tasks.
  • You will learn about the parameters and how to optimise them for each method task.

Who is this course for?

Before attending this course you should have a good knowledge of gas chromatography and the techniques covered in the Practical Essentials of GC & GC-MS.

How does the virtual classroom training work?

You will be provided with a link to access the virtual classroom and the training course will be presented live at the scheduled time through video conferencing. You will have the opportunity to ask questions during the live course. If for any reason you miss the live broadcast, you will be provided with a one-time link to access a recording of the course and can submit any questions via email.

To gain the full knowledge of gas chromatography it is highly recommended to attend the full Complete GC & GC-MS course.

Course feedback

Just some of the feedback from attendees of our face-to-face classroom course:

"The most useful thing was learning where to start, especially with unknown samples, and how to optimize from there."

"All the basics were explained really well and illustrated with practical examples. I feel that I am better able to make decisions when analysis or trying to adjust a current method."