SAS Clinical Master Program

SAS Clinical Master's training will prepare you for Base SAS, Advance SAS and SAS Clinical programming. The combination of coursework and hands-on learning helps you build a foundation of clinical research theory and data manipulation and analysis skills – which can open doors to new opportunities.

What will i learn?
  • Extracting the data from various internal and external databases (Oracle, MS Access, Excel spreadsheets) using SAS/ACCES...
  • Developing programs for converting the Oracle data into SAS datasets using SQL Pass Through Facility
  • Clinical trial data analysis with different Statistical Procedures
  • Creating the statistical reports using Proc Report, Proc Tabulate and SAS Macro
  • Analyzing the data and creating tables according to the Statistical Analysis Plan (SAP). Generating the demographic tabl...
  • Using the SAS procedures (MEANS, FREQ, SUMMARY, TRANSPOSE, TABULATE, REPORT etc) and SAS/STAT procedures (REG, CORR, GLM...
  • Manipulation of SAS datasets using SET, MERGE, UPDATE, MODIFY and Conditional statements. Generating Graphs and Figures...
  • Extensive Applications in SAS/SQL, SAS/ACCESS, SAS/CONNECT and SAS Macros
  • Providing programming support for the creation and maintenance of programs used in Data Management, Data Validation, Dat...
  • Working with datasets such as DM (Demographics), LB (Laboratory), MH (Medical History), AE (Adverse Events), VS (Vital S...

BIT’s SAS Clinical Master’s Training Program will help you master SAS Base and Advance Programming with advanced analytics techniques using SAS Clinical. In this SAS Clinical training course, you will learn SAS macros, Machine Learning, PROC SQL, procedure, statistical analysis decision trees and SAS Clinical programming as well.

Clinical SAS is the application of SAS technology to clinical domain for clinical trial data analysis in pharmaceutical or biotech and clinical research companies. Familiarity with clinical trial aspects combined with knowledge of SAS can lead to a challenging and rewarding career that also positively impacts & transforms patients’ lives. SAS programmer with the Clinical knowledge always have an competitive edge over a purely SAS programmer as he/she will be in a position to take decisions while programming. One can start a career in Clinical SAS Programming as clinical programmer whose primary responsibility is writing programs in SAS to generate the output (tables, listings, and figures) needed for the analysis and reporting of the clinical study. A Clinical SAS Programmer having CDISC (standard specifications for electronically submitted clinical data) expertise would have extensive opportunities. SAS Clinical training course provides insights on developing the SAS programming to conduct analysis for the different types of clinical trials and new drug applications. With best Practical Hands on Clinical SAS Programming Training, Analysts play predominant role in evaluation of drugs in clinical studies.

For more inquiries, visit our near BIT Training center or e-mail on or visit one of the BIT Training Centers located in Vadodara (Manjalpur, Sayajigunj, Waghodiya).

  • Knowledge of Base SAS. Deep understanding of clinical programming concepts Basic understanding of statistics.
Other related courses
BIT's SAS CLINICAL Training Course provides insights into clinical trials and their aspects. The course deals with designing, analysing and generating reports and explained them in support of real-time data.
The data science with SAS training program is suited for data scientists, analytics professionals, as well as managers in decision-making roles.
Base SAS (Statistical Analysis System) training is a good way to enter into the data analytics industry. You will also work on real-life projects and prepare for the SAS Certified Base Programmer certification exam under SAS Base Programming Training.
SAS Advanced Programming Training will help you master advanced analytics techniques using SAS language.
SAS Programming Master's training includes data mining, data analytics, modeling techniques, visualization of data, predictive analysis and extracting insights through real-world case studies.

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