Clinical SAS Certification Course in Pune

• Analytical insights that drive value-based healthcare.

• Embedded artificial intelligence (AI), image analytics, and machine learning.+

• Integrating data for improved clinical decisions.

• In-stream analysis of data from the Internet of Medical Things (IoMT).

• With deep industry expertise and healthcare data analytics solutions built for interoperability, SAS increases the value of your time.

• Data Integration: SAS Clinical Data Integration follows the CDISC SDTM standards. Clinical Data Integration includes clinical trial data and information collection, data analytics, reporting, efficiency, and quality during the assessment. SAS Clinical Data integration requires SAS Intelligence platforms, embedded artificial intelligence (AI), image analytics, and machine learning.

• Data-driven root cause analysis: It uses data analytics to improve and ensure product quality, reduce operational costs, and gain actionable insights

• Graduate & Master’s Background in life sciences, IT, Statistics and Biostatistics, Biotechnology, Pharmacy and Pharmacology, Medical and Health Sciences

• Basic understanding of any programming language is preferred, as it will help in grasping core concepts more quickly.

• No prior SAS experience is needed. However, we recommend that you have relevant experience in the pharmaceutical or life science industry – or be a graduate or postgraduate in life sciences, pharmacy, statistics, medical, bio or computer programming.

• Live Web Training

• Face to Face - Minimum of 15 participants required

• Regional Live Web

• India – 8 AM – 12 PM

• Weekend Batch – 9 AM – 1 PM & 2 PM – 6 PM

• Clinical SAS Programmer

• Biostatistician

• Clinical SAS Developer

• Clinical Data Manager

• SAS Clinical Data Analyst

• Statistical Programmer

• Clinical Research Associate (with SAS skills)

• Clinical Trials Specialist

• Clinical Research Coordinator

• Clinical Research Associate

• Principal Clinical Data Science Programmer

• SAS Certified trainers with Clinical SAS Live Web Training Centers (Demonstrate your true SAS skills and understanding.)

• Hands on learning (Learn Clinical SAS Training in Pune with a SAS Certified expert instructor in a traditional classroom setting for an in-depth, hands-on learning experience).

• Software Access (Access the latest software 24*7 on Azure servers)

• Earn Digital Badge (A secure, electronic verification of your achievement.)

• SAS Global Certification Credentials (Earn your SAS Certified Specialist: Base Programming Using SAS9.4 and SAS Certified Professional: Clinical Trials Programming Using SAS 9.4 credentials and be recognized across all industries and geographic locations).

• Programming Concepts for BaseSAS, ProcSQL, and Macros

• Clinical Trials Processes and Working Environment

• Clinical Trial Data Management using Base SAS, Macro Programming and SQL

• Preparing and Classifying Clinical Trial Data

• Implementing CDISC SDTM and ADaM Guidelines

• Clinical Study Reporting using SAS REPORT Procedure

• Data Visualization Using SAS ODS Graphics

• Performing Data Validation

• Statistical Methods for Exploring and Analyzing Data

• SAS Authorized Training Centers are part of the SAS Learning Partner community. Educational Program provides a standardized, supervised, and systematic approach to learning.

• Clinical SAS Training in Pune with placement is offered by SAS Accredited Training Partner Aspire Techsoft. At the same time, thousands of non-institutes are offering SAS Training, where proper facility, as well as quality, cannot be guaranteed. If you are specifically looking for a Clinical SAS Certification course in Pune, no one but SAS can issue a global certificate.

• Whatever the type of educational institution, it largely depends on the core strength and knowledge of the instructor.

• Aspire Techsoft is the top SAS Accredited Clinical SAS Training center in India that provide quality learning experiences to students and professionals. Our comprehensive SAS training courses help you enhance your skills, prepare for certification exams, and achieve your career goals.

• Clinical SAS Certification Course in Pune at Aspire Techsoft Academy you get to choose what you learn – and how you learn it. Find a format that suits your style.

• SAS Clinical Trials Programming Live Web Course:

• Instructor-led Clinical SAS Certification Course in Pune

• Access to SAS software for practice

• SAS training without travel

• Ask questions and get answers in real-time SAS instructors

• Dedicated coach to guide you

• Practical study

• Project work

• SAS instructors virtually in your office

• Our Clinical SAS Course Pune is conducted by globally acclaimed SAS Certified instructors and will not be pre-recorded sessions. SAS instructors encourage you to expand your thinking, discuss, and share with you so that you can master the SAS skills you learn and achieve your goals.

• Virtual Live Web Clinical SAS Certification Course in Pune - Participate remotely from your home or office.

• Ask questions and share ideas during Clinical SAS Live Web class hours and on-demand lab hours.

• SAS Clinical Programming Classes in Pune - Join in person with an instructor right next to you.

• Private team training for your team virtually or at our location or schedule for you.

• Clinical Trials Process Reports

• Clinical Research Projects

• Health Insurance Companies Data (Claims Data)

• Electronic health records of patients

• Tracking of Patients Statistics

• Primary Data Sources - Patient Prescription History

• FDA Research Data

• Administrative Data

• Health Surveys

• Patient / Disease Registries

• Patient Testimonials Data

• Biotech, Life Science Company - Sales Data

• Social Media & Website Records - Patient self-data according to their search health-related data

• Essentials

▪ the SAS programming process

▪ using SAS programming tools

▪ understanding SAS syntax

• Accessing Data

▪ understanding SAS data

▪ accessing data through libraries

▪ importing data into SAS

• Exploring and Validating Data

▪ exploring data

▪ filtering rows

▪ formatting columns

▪ sorting data and removing duplicates

• Preparing Data

▪ reading and filtering data

▪ computing new columns

▪ conditional processing

• Analyzing and Reporting on Data

▪ enhancing reports with titles, footnotes, and labels

▪ creating frequency reports

▪ creating summary statistics reports

• Exporting Results

▪ exporting data

▪ exporting reports

• Using SQL in SAS

▪ using Structured Query Language in SAS

▪ joining tables using SQL in SAS

• Controlling DATA Step Processing

▪ setting up for this course

▪ understanding DATA step processing

▪ directing DATA step output

• Summarizing Data

▪ creating an accumulating column

▪ processing data in groups

• Manipulating Data with Functions

▪ understanding SAS functions and CALL routines

▪ using numeric and date functions

▪ using character functions

▪ using special functions to convert column type

• Creating Custom Formats

▪ creating and using custom formats

▪ creating custom formats from tables

• Combining Tables

▪ concatenating tables

▪ merging tables

▪ identifying matching and nonmatching rows

• Processing Repetitive Code

▪ using iterative DO loops

▪ using conditional DO loops

• Restructuring Tables

▪ restructuring data with the DATA step

▪ restructuring data with the TRANSPOSE procedure

• Array Processing in Data Step

▪ Introduction to table Lookup Techniques

▪ One-Dimensional Arrays

▪ Multidimensional Arrays

▪ Loading a Multidimensional Array from a SAS Data set

▪ Environment and Guiding Principles

▪ Preparing Clinical Trial Data

▪ Classifying Clinical Trial Data

▪ Introduction to Clinical Data Interchange Standards Consortium (CDISC)

▪ Fundamentals of the Study Data Tabulation Model (SDTM)

• The General Observations Class

▪ Interventions Class

▪ Events Class

▪ Findings Class

• Datasets Other than General Observation

Models for Special-Purpose Domains

Trial Design Model (TDM) Datasets

Relationship Datasets

Study Reference Datasets

• Assumptions for Domain Models

• Base SAS Programs for SDTM Conversions

• Building SDTM Datasets

▪ Building the Special-Purpose DM and SUPPDM Domains

▪ Building the AE Events Domain

▪ Building the LB Finding Domain

▪ Fundamentals of ADaM

▪ Subject-Level Analysis Dataset (ADSL)

▪ Basic Data Structure (BDS)

▪ Building the Subject-Level Analysis Dataset (ADSL)

▪ Building the Adverse Events Analysis Dataset (ADAE)

• Introduction

▪ overview of SAS Foundation

▪ course logistics

▪ course data files

▪ introducing the Structured Query Language

• Basic Queries

▪ overview of the SQL procedure

▪ specifying columns

▪ specifying rows

• Displaying Query Results

▪ presenting data

▪ summarizing data

• SQL Joins

▪ introduction to SQL joins

▪ inner joins

▪ outer joins

▪ complex SQL joins

• Subqueries

▪ noncorrelated subqueries

▪ in-line views

• Set Operators

▪ introduction to set operators

▪ the UNION operator

▪ the OUTER UNION operator

▪ the EXCEPT operator

▪ the INTERSECT operator

• Creating Tables and Views

▪ creating tables with the SQL procedure

▪ creating views with the SQL procedure

• Advanced PROC SQL Features

▪ using SQL procedure options

▪ interfacing PROC SQL with the macro language

• Learning More

▪ SAS resources

▪ beyond this course

• Introduction

▪ course logistics

▪ purpose of the macro facility

▪ program flow

• Macro Variables

▪ introduction to macro variables

▪ automatic macro variables

▪ macro variable references

▪ user-defined macro variables

▪ delimiting macro variable references

▪ macro functions

• Macro Definitions

▪ defining and calling a macro

▪ macro parameters

• DATA Step and SQL Interfaces

▪ creating macro variables in the DATA step

▪ indirect references to macro variables

▪ creating macro variables in SQL

• Macro Programs

▪ conditional processing

▪ parameter validation

▪ iterative processing

▪ global and local symbol tables

• Learning More

▪ SAS resources

▪ beyond this course

• Supplemental Materials

▪ program flow

• Use SQL Procedure to create Data sets

▪ Use CREATE TABLE query to create Study Tabulations and Analysis Datasets

▪ Use Join and Union clauses to combine multiple tables

• Use Macro Programming to automate tasks

▪ Create a macro to derive ISO8601 date string from SAS date or datetime component variables

▪ Create a macro to derive SDTM study day variable

▪ Create a macro to calculate change from baseline

• Introduction to Reporting and ODS

▪ Course logistics

▪ Introduction to reporting.

▪ Introduction to ODS.

▪ ODS with the SAS interfaces.

▪ Creating reports with the PRINT procedure

• Getting Started with the TABULATE Procedure

▪ Introduction to the TABULATE procedure.

▪ Creating the structure of the table.

▪ Adding overall summarizations.

▪ Adding additional statistics.

• Doing More with the TABULATE Procedure

▪ Enhancing with labels and formats.

▪ Enhancing with options.

▪ Adding trafficlighting.

▪ Adding additional style attributes.

• Getting Started with the REPORT Procedure

▪ Introduction to the REPORT procedure.

▪ Creating a detail report.

▪ Creating a summary report with the GROUP usage.

▪ Creating a summary report with the ACROSS usage.

▪ Computing an additional column.

• Doing More with the REPORT Procedure

▪ Adding summary lines.

▪ Customizing break lines.

▪ Adding trafficlighting and style attributes.

▪ Using the CALL DEFINE statement.

• Doing More with the REPORT Procedure

▪ Adding summary lines

▪ Customizing break lines.

▪ Adding trafficlighting and style attributes.

▪ Using the CALL DEFINE statement.

• Using ODS Destinations

▪ Introduction to ODS destinations

▪ PRINTER and RTF destinations

▪ CSV and HTML destinations.

▪ Excel and other destinations.

▪ SAS destinations.

• Doing More with ODS

▪ Using ODS options and statements.

▪ Using ODSESCAPECHAR.

▪ Controlling bookmarks and the table of contents.

▪ Using ODS layout

• Introduction to SG Procedures

▪ Introduction to ODS Graphics.

▪ Using the SG procedures.

• Getting Started

▪ Setting up for this course

▪ Data visualization with SAS programming overview.

▪ Layers of a graph.

• SGPLOT Procedure

▪ Introduction

▪ Bar charts.

▪ Dot, line, scatter, and series plots.

▪ Additional basic plots.

▪ Distribution plots.

▪ Fit and confidence plots

• Enhancing Visualization Appearance

▪ Style templates, colors, and fonts.

▪ Group attributes.

▪ Reference lines and text boxes.

▪ Axis appearance.

▪ Legend appearance

▪ User-defined style templates.

▪ Additional statements and examples

• Multi-cell Procedures

▪ Introduction.

▪ SGPANEL procedure

▪ SGSCATTER procedure.

• Additional Procedures

▪ SGPIE procedure.

▪ SGMAP procedure.

• Customizing Visualizations

▪ Introduction to SG annotation.

▪ Drawing space.

▪ LINE and ARROW functions.

▪ TEXT and TEXTCONT functions

▪ SG attribute maps

• More with ODS Graphics

▪ ODS GRAPHICS and destination statements.

▪ ODS layout.

▪ Statistical procedures.

• Graph Template Language

▪ Introduction.

▪ Graph Template Language syntax

▪ Dynamic and macro variables.

▪ Creating Tables

▪ Creating Listings

▪ Output Appearance Options

▪ Common Clinical Trial Graphs

▪ Exporting Data

▪ Define.XML for CDISC SDTM

▪ Define.XML for CDISC ADaM

▪ Programming Considerations

▪ Reviewing Programming Log

▪ Using SAS Programming Procedures for Data Validation

▪ Generate descriptive statistics and explore data with graphs.

▪ Perform analysis of variance and apply multiple comparison techniques

▪ Perform linear regression and assess the assumptions.

▪ Use regression model selection techniques to aid in the choice of predictor variables in multiple regression.

▪ Use diagnostic statistics to assess statistical assumptions and identify potential outliers in multiple regression.

▪ Use chi-square statistics to detect associations among categorical variables.

▪ Fit a multiple logistic regression model.

▪ Score new data using developed models.