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SAS Clinical Data Management

  • 20 weeks
  • 120 Hours

This is the great exposure for Life Science background students to drive into the tech field. Boost your profession to the next level by evolving your technical familiarity with Industry Standard .

Course Overview

Your career in the sought-after position be a Data Scientist in the Health-Care Industry. This course is for users who want to learn how to write SAS programs and apply in Clinical Research. SAS is the global leader in analytics. Through advanced software and services, SAS enriched and inspires customers round the world to transfigure data into intelligence. In this program you will get to know Base SAS, Advance SAS, SAS Clinical Project Content (CDISC SDTM ADaM TLF).

Advantage

This SAS Clinical Data Management program will help you to build your career as a Clinical Data Manager. We design this course by extensive research on job requirement across the world. Completion of this course will make you job ready as Clinical SAS Manager. Secure your job in less than 6 months. A comprehensive Program – covering complete knowledges on Base SAS, Advanced SAS, Clinical Data Management techniques and efficiencies.

What you'll learn

  • Base SAS
  • Advanced SAS
  • SAS Clinical Data Management

Base SAS

  • Components of the SAS System
  • Data-Driven Tasks
  • Turning Data into Information
  • Introducing to SAS Programs
  • Running SAS Programs
  • Mastering Fundamental Concepts
  • Diagnosing and Correcting Syntax Errors
  • Getting Started with the PRINT Procedure
  • Sequencing and Grouping Observations
  • Identifying Observations
  • Special WHERE Statement Operators
  • Customizing Report Appearance
  • Formatting Data Values
  • Creating HTML Reports
  • Reading Raw Data Files: Column Input
  • Reading Raw Data Files: Formatted Input
  • Examining Data Errors
  • Assigning Variable Attributes
  • Changing Variable Attributes
  • Reading Excel Spreadsheets
  • Reading SAS Data Sets and Creating Variables
  • Conditional Processing
  • Dropping and Keeping Variables
  • Reading Excel Spreadsheets Containing Date Fields
  • Concatenating SAS Data Sets
  • Merging SAS Data Sets
  • Combining SAS Data Sets : Additional Features
  • Introduction to Summary Reports
  • Basic Summary Reports
  • The Report Procedure
  • The Tabulate Procedure
  • Producing Bar and pie Chart
  • Enhancing output
  • Producing Plots
  • Overview
  • Review of SAS basics
  • Review of DATA Step Processing
  • Review of Displaying SAS Data Sets
  • Working with Existing SAS Data Sets
  • Outputting Multiple Observations
  • Writing to Multiple SAS Data Sets
  • Selecting Variables and Observations
  • Writing to an External File
  • Creating an Accumulating Total variable
  • Accumulating Totals for a Group of Data
  • Reading Delimited Raw Data Files
  • Controlling When a Record Loads
  • Reading Hierarchical Raw data Files
  • Introduction
  • Manipulating Character values
  • Manipulating Numeric values
  • Manipulating Numeric values based on Dates
  • Converting variable Type
  • Using the PUT Statemen
  • Using the DEBUG Option
  • Do Loop Processing
  • SAS Array Processing
  • Using SAS Arrays
  • Match-merging Two or more SAS Data Sets
  • Simple Joins Using the SQL Procedure
  • Mastering Fundamental Concepts
  • Diagnosing and Correcting Syntax Errors

Advanced SAS

  • What is SQL?
  • What is the SQL Procedure?
  • Terminology
  • Comparing PROC SQL with the SAS DATA step
  • Note about the Example Table
  • Overview of the select Statement
  • Selecting Columns in a Table
  • Creating New Columns
  • Sorting Data
  • Retrieving rows that satisfy a Condition
  • Summarizing Data
  • Grouping Data
  • Filtering Grouped Data
  • Introduction
  • Selecting Data from More Than One Table by Using joins
  • Using Subqueries to Select Data
  • When to Use Joins and Subqueries
  • Combining Queries with Set Operators
  • Introduction
  • Creating Tables
  • Inserting Rows into Tables
  • >Updating Data Values in a Table
  • Deleting Rows
  • Altering Columns
  • Creating an Index
  • Deleting a Table
  • Using SQL Procedure Tables in SAS Software
  • Creating and Using Integrity Constraints in a Table
  • Introduction
  • Using Proc SQL Options to Create and Debug Quires
  • Improving Query Performance
  • Accessing SAS System Information Using DICTIONARY Tables
  • Using Proc SQL with the SAS Macro Facility
  • Formatting PROC SQL output Using the Report Procedure
  • Accessing a DBMS with SAS/ACCESS Software
  • Overview
  • Computing a Weighted Average
  • Comparing Tables
  • Overlaying Missing Data Values
  • Computing Percentages within Subtotals
  • Counting Duplicate Rows in a Table
  • Expanding Hierarchical Data in a Table
  • Summarizing Data in Multiple Columns
  • Creating a Summary Report
  • Creating a Customized Sort Order
  • Conditionally Updating a Table
  • Updating a Table with Values from Another Table
  • Creating and Using Macro Variables
  • SAS Macro Overview
  • SAS Macro Variables
  • Scope of Macro variables
  • Defining SAS Macros
  • Inserting Comments in Macros
  • Macros with Arguments
  • Conditional Macros
  • Macros Repeating PROC Execution
  • Macro Language
  • SAS Macro Processor

SAS Clinical Project Content (CDISC SDTM ADaM TLF)

  • Introduction to drug development process
  • Drug approval process
  • Introduction about Clinical trials process
  • Introduction of CDISC
  • Why CDISC and DATA standards
  • What are the versions of CDISC
  • Impact of CDISC Standards on Clinical Activities
  • CDISC Models
  • Study Data Tabulation Model (SDTM)
  • Analysis Dataset Models (ADaM)
  • Operational Data Model (ODM)
  • What is SDTM?
  • Observations and Variables in SDTM
  • Special Purpose Datasets
  • General Observation Classes in SDTM
  • SDTM Standard Domain Models
  • DM(Demographics), CO(Comments), SE(Subjects Elements)
  • CM(Concomitant Medication), EX(exposure), SU(Substance Use), EC(Exposure as collected
  • a. AE, MH
  • LB, EG, VS, PE, IE
  • Supplemental Qualifies domains and relrec SDTM Annotation on CRF – Concept

Admission Process

Please call to admission counselor for course fees, registration fees, EMI fecilities,registration form and other formalities. Contact to admission counselor
+91-9831765780
+91-9830247087

Who can join?

Any graduate with knowledge of basic computing.

Requirment

1.Personal computer/laptop with webcam and microphone
2.Stable internet connections

Payment details

Bank Details:
KLMS HANDS-ON SYSTEMS PRIVET LIMITED
Account Number: 19700200000420
IFSC Code: BARB0SALTLA (5th letter is numeric zero)
UPI Payment: [email protected]

SAS Clinical Data Management
This Course Include:
  • Live Instructor-Led Course
  • Project and Case Studies
  • Certificate of completion
  • Learn from Experts
  • Placement Assistance
  • Assistance for Global Certification