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Courses

  • 1 Request Info

    Compliance for Computer Systems Regulated by FDA - 2017

    Overview: The Webinar will focus on the importance of ensuring that electronic record/electronic signature (ER/ES) capability built into FDA-regulated computer systems meets compliance with 21 CFR Part 11. This includes development of a company philosophy and approach, and incorporating it into the overall computer system validation program and plans for individual systems that have this capability. FDA's 21 CFR Part 11 was enacted in the late 1990s and implementation success across the pharmaceutical and other regulated industries has been mixed.
  • 2 Request Info

    Webinar On Conducting a Software Validation of Medical Device to Meet FDA Requirements

    This course will teach how to conduct a software validation program that will satisfy FDA requirements and produce a safe product. We will explain the role of risk analysis in validation. How software requirements are used in validation will be described. This course is not a programming course. We will discuss what must be done but will not discuss methods to execute necessary testing.Price:$250.00. Contact info : OnlineCompliancePanel Phn. no. +1-510-857-5896 Fax-+1-510-509-9659 info@onlinecompliancepanel.com Event link http://onlinecompliancepanel.com/webinar/SOFTWARE-VALIDATION-MEDICAL-DEVICE-501884/NOVEMBER-2016-ES-TRAININGREGISTRY
  • 3 Request Info

    Performing Data Analysis with Multiple Tools: Pandas, R and Deedle (F#/C#)

    The seminar will begin with an over view of data science and many the steps required for collecting, cleaning, organizing and deriving information out of data. The steps are common to all of the tools and will form the foundation for analyzing, comparing and utilizing the tools used in the remainder of the seminar: R, pandas and Deedle. Topics covered in the foundation are: • Organizing information into data frames • Mutating data frame objects • Indexing data frames • Data alignment between data frames • Handling missing data • Joining data • Reading and writing data from files and databases • Accessing data from web services • Reshaping of data (ie: pivoting and melting) • Slicing and subsetting data • Grouping of data • Deriving aggregate results from data • Handling of time series information • Resampling time series data into other frequencies • Shifting time series data • Moving and sliding windows statistics • Data visualization
  • 4 Request Info

    An SPSS Class, Private Training, or Statistics Analysis Consultation