Bangalore is known as the technology capital of India. In India's booming economy, the technological sector is poised to play a major role. You can give your career a substantial boost by taking Clinical Research Courses In Bangalore.
What Types of Courses Can I Take?
Clinical research courses in Bangalore should give you a well rounded overview of what research entails. Here are some descriptions of major Clinical research courses in Bangalore.
* Analysis Dataset Development: Data is the heart of research, and this course will allow you to be a developer. Develop analysis datasets, the first part of clinical trials analytics. Write SAS code within given guidelines and clinical datasets to create analysis datasets from raw clinical data.
* Analysis Dataset Validation: Accuracy of data is absolutely essential in clinical research. Many studies hire independent validators, who create their own code and compare the analysis dataset they come up with to the one obtained in the study. This course will allow you to be an independent validator. From the given raw clinical dataset and analysis dataset, you will write your independent code to validate the data.
* Report Generation: At the end of a clinical research study, you must write up your results in a report to be published and shared with other scientists. You will use given analysis datasets, mock shells, and guidelines to create your own summary reports and listings to interpret the data and make inferences from the statistics and clinical data.
* Report Validation: Like analysis datasets, reports must be validated. In this course, you will do what an independent report validator hired by a study would do: write code from given analysis datasets and RTF (Rich Text Format) Reports.
* Graph Generation: A graph will help you visualize, format, and analyze your data. In this course, you will be given analysis to create your own graphs. Graphs are helpful for the people who will read your report, usually regulatory officials, who will be able to see from the graph broad trends of data.
* Merging of Datasets for PK Analysis: PK stands for Pharmacokinetic. PK analysis involves PK Data integration, which combines PK concentration data and datasets created from this data in the database, involving factors such as blood collection, demographics, dose administration, and vital signs. You will have to create a PK analysis dataset, based on the raw PK datasets and clinical datasets.
ClipLab offers Clinical Research Courses in Bangalore to help your clinical research career take off. To learn more, please visit http://www.cliplab.co.in/.