Data Science With SAS Training Course Online Course

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Data Science with SAS Training Course

All levels
English

Course Description

This Data Science with SAS training helps you realize your dream of becoming a data scientist. By learning this course, you will already have all the tools needed to be an efficient data scientist. Roles of a data scientist like acquiring data, analytics, exploring and presentation can be handled well using different tools from the SAS suite. BIT’s Data Science with SAS course lets you gain proficiency in Data Science. You will work on real-world projects in Data Science with SAS. In this SAS Certification Training, you’ll become an expert in analytics techniques using the SAS data science tool. SAS course offers a comprehensive learning foundation that you can build your analytics career on. SAS is one of the most popular analytics languages used by a majority of the organizations in the world. Data science has become the currency of business decision-making. Analyzing data to derive meaningful insights allows a business to achieve enhanced efficiency.

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What you’ll learn

Live Class Practical Oriented Training
Timely Doubt Resolution
Dedicated Student Success Mentor
Certification & Job Assistance
Free Access to Workshop & Webinar
No Cost EMI Option
Understand the role of data scientists, various analytics techniques, and widely used tools
Gain an understanding of SAS, the role of GUI, library statements, importing and exporting of data and variable attribut...
Gain an in-depth understanding of statistics, hypothesis testing, and advanced statistics techniques like clustering, de...
Learn the various techniques for combining and modifying datasets like concatenation, interleaving, one-to-one merging a...
Understand PROC SQL, its syntax, and master the various PROC statements and subsequent statistical procedures used for a...
Understand the power of SAS Macros and how they can be used for faster data manipulation and for reducing the amount of...
Gain an in-depth understanding of the various types of Macro variables, Macro function SYMBOLGEN System options, SQL cla...

Covering Topics

Lecture 1: Analytics overview

Lecture 2: Introduction to sas

Lecture 3: Combining and modifying datasets

Lecture 4: Sas operators and functions

Lecture 5 Compilation and execution

Lecture 6: Creation and compilation of sas data sets

Lecture 7: Proc SQL

Lecture 8: Input statement and formatted input

Lecture 9: Sas format

Lecture 10: Sas graphs

Lecture 11: Sas macros

Lecture 12: Basics of statistics

Lecture 13: Statistical procedures

Lecture 14: Data exploration

Lecture 15: Advanced statistics

Lecture 16: Working with time series data

Lecture 17: Designing optimization models

Curriculum

  Lecture 1: Analytics overview
Live Lecture 
·       An introduction to the business analytics

·       The types of analytics

·       The areas of analytics

·       About analytical tools

·       About analytical techniques

·       Practical Exercise

  Lecture 2: Introduction to sas
Live Lecture 
·       An overview of the sas

·       Installation and introduction to sas,

·       Understanding different sas windows,

·       How to work with data sets,

·       Various sas windows like output,

·       Search, editor, log and explorer

·       Understanding the sas functions,

·       Which are various library types & programming files

·       The navigation in the sas console

·       About the sas language input files

·       What is data step? 

·       The proc step and data step

·       All about data step processing

·       The sas libraries

·       How to import and export raw data files,

·       How to read and subset the data sets

·       Practical Exercise

  Lecture 3: Combining and modifying datasets
Live Lecture 
·       Necessity of combining or modifying the data

·       Concatenating the datasets

·       About interleaving method

·       What is data manipulation?

·       Modifying the variable attributes

·       Practical Exercise

  Lecture 4: Sas operators and functions
Live Lecture 
·       Logical operator

·       Comparison operator

·       Arithmetic operator

·       Deploying different sas

·       Conditional statements

·       If/else, do while, do until

·       Practical Exercise

  Lecture 5 Compilation and execution
Live Lecture 
·       Input buffer,

·       Pdv (backend)

·       Missover

·       Practical Exercise

  Lecture 6: Creation and compilation of sas data sets
Live Lecture 
·       Understanding the delimiter,

·       Dataline rules,

·       Dlm,

·       Delimiter dsd,

·       Raw data files and execution

·       List input for standard data

·       Practical Exercise

  Lecture 7: Proc SQL
Live Lecture 
·       What is proc sql?

·       How to retrieve data from a table?

·       How to select columns in a table?

·       Retrieving the data from multiple tables

·       Selecting the data from multiple tables

·       Concatenating query results

·       Practical Exercise

  Lecture 8: Input statement and formatted input
Live Lecture 
·       Reading standard and non-standard numeric inputs

·       Column pointer controls,

·       Controlling while a record loads,

·       line pointer control/absolute line pointer control,

·       Single trailing,

·       Multiple in and out statements,

·       Dataline statement and rules,

·       List input method

·       Comparing single trailing

·       Double trailing

·       Practical Exercise

  Lecture 9: Sas format
Live Lecture 
·       Sas format statements: standard and user-written,

·       Associating a format with a variable,

·       Working with sas format,

·       Deploying it on proc data sets

·       Comparing attrib

·       Format statements

·       Practical Exercise

  Lecture 10: Sas graphs
Live Lecture 
·       Understanding proc gchart,

·       Various graphs,

·       Bar charts pie,

·       Bar and 3d and plotting variables with proc gplot

·       Practical Exercise

  Lecture 11: Sas macros
Live Lecture 
·       Need for sas macros

·       Macro functions

·       Sql clauses for macros

·       The % macro statement

·       The conditional statement

·       Practical Exercise

  Lecture 12: Basics of statistics
Live Lecture 
·       Introduction to the statistics

·       The statistical terms

·       Procedures in the sas for descriptive statistics

·       About hypothesis testing

·       About variable types

·       The hypothesis testing - process

·       The parametric and non - parametric tests

·       What are parametric tests?

·       What are non - parametric tests?

·       Parametric tests – the advantages and the disadvantages

·       Practical Exercise

  Lecture 13: Statistical procedures
Live Lecture 
·       The statistical procedures

·       What do proc means?

·       What is proc freq?

·       About proc univariate

·       About proc corr

·       About proc corr options

·       About proc reg

·       The proc reg options

·       The proc anova

·       Practical Exercise

  Lecture 14: Data exploration
Live Lecture 
·       Data exploration: an overview

·       What is data preparation? 

·       The general comments and observations on data cleaning

·       Data type conversion

·       Character functions

·       What is scan function?

·       About date/time functions

·       Missing value treatment

·       Various functions to handle missing value

·       Data summarization

·       Practical Exercise

  Lecture 15: Advanced statistics
Live Lecture 
·       An introduction to the advanced statistics

·       Introduction to the cluster

·       The clustering methodologies

·       What is k means clustering?

·       About the decision tree

·       The regression

·       The logistic regression

·       Practical Exercise

  Lecture 16: Working with time series data
Live Lecture 
·       An introduction to the working with time series data

·       Need for time series analysis

·       About the time series analysis — options

·       Reading date and datetime values

·       What is the white noise process?

·       The stationarity of a time series

·       The plot transform transpose and interpolating time series data

·       Practical Exercise

  Lecture 17: Designing optimization models
Live Lecture 
·       Introduction to the designing optimization models

·       About the need for the optimization

·       About optimization problems

·       What is proc optmodel?

·       Practical Exercise

Frequently Asked Questions

There is no prerequisite for this course, anyone willing to make their career in data analytics and want to gain expertise on the data science tools should join this course.

The course offers a variety of online training options, including: Live Virtual Classroom Training: Participate in real-time interactive sessions with instructors and peers. 1:1 Doubt Resolution Sessions: Get personalized assistance and clarification on course-related queries. Recorded Live Lectures*: Access recorded sessions for review or to catch up on missed classes. Flexible Schedule: Enjoy the flexibility to learn at your own pace and according to your schedule.

Live Virtual Classroom Training allows you to attend instructor-led sessions in real-time through an online platform. You can interact with the instructor, ask questions, participate in discussions, and collaborate with fellow learners, simulating the experience of a traditional classroom setting from the comfort of your own space.

If you miss a live session, you can access recorded lectures* to review the content covered during the session. This allows you to catch up on any missed material at your own pace and ensures that you don't fall behind in your learning journey.

The course offers a flexible schedule, allowing you to learn at times that suit you best. Whether you have other commitments or prefer to study during specific hours, the course structure accommodates your needs, enabling you to balance your learning with other responsibilities effectively. *Note: Availability of recorded live lectures may vary depending on the course and training provider.