3 Days Left to Grab the Early Bird Price at Cadmium Spark

Only 3 days left to catch early bird pricing to Cadmium Spark! Click here to catch the discount before June 19th.

Already registered? Share your discount code with up to 5 additional people from the same organization to register at a 50% discount.

Want a closer look at what the conference has in store before deciding? Check out the full schedule or peruse some highlights below:

Creating Course Relationships in EthosCE
Presentor: Nicholas Torres, MS, A-CSM, Cadmium

In this Learning Lab, EthosCE team members will lead participants through a hands-on workshop on creating both simple and complex course relationships. Participants will also see analytics in action as the learning lab dives into course reports that can be leveraged to make data-driven decisions. Attendees will have the opportunity to build their own course relationships in either their own EthosCE site or a sandbox environment and get feedback from EthosCE experts.

EthosCE Rapid Fire Ideas Exchange
Moderator: Kristin Sergi, Cadmium
Presenter: Aubrey Shoe, MA, CHCP, CME Institute

EthosCE is chock full of features and functionality aimed at streamlining processes and creating engaging learning experiences for end users. In this rapid fire ideas exchange, we’ll hear from three EthosCE clients about innovative ways they are utilizing the EthosCE platform. This rapid fire format is meant to inspire creative and innovative uses of EthosCE technology. It’s a not to miss for any EthosCE client, whether new or a seasoned pro.

Automatic CME Activity and Credit Reporting in EthosCE
Presenter: Devin Zuczek, Cadmium

EthosCE can automatically report CME activities and credit to ACCME PARS, JA-PARS, and CPE Monitor. This session will provide an in-depth look at how the two systems communicate and and how you can use them to streamline the reporting process. We will go over best practices for activity creation and learner data collection to ensure that activities and credits are seamlessly reported in near real time.

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