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In this SAS Certification Training, you’ll become an expert in analytics techniques using the SAS data science tool. You’ll learn how to apply data manipulation and optimization techniques; advanced statistical concepts like clustering, linear regression and decision trees; data analysis methods to solve real world business problems and predictive modeling techniques. This SAS Certification course will give you practical knowledge you can apply on your next data analysis job.

Course Advisors

Paul Sharkov
Data Scientist at BMO Financial Group, Member of SAS Canada Community

Paul is lead SAS Data Scientist at Bank of Montreal. As a SAS Certified Predictive Modeler, SAS Statistical Business Analyst, and SAS Certified Advanced Programmer, Paul is passionate about sharing his knowledge on how data science can support data-driven business decisions.

Ronald van Loon
Top 10 Big Data & Data Science Influencer, Director – Adversitement

Named by Onalytica as one of the three most influential people in Big Data, Ronald is also an author for a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. He also regularly speaks at renowned events.


Key Features 

32 hours of instructor-led training (for Live Virtual Classroom)

24 hours of self-paced video

4 real-life industry projects

3 sets of assessment papers

Details of SAS Macros and PROC SQL

Includes a free SAS Base Programmer course

Mode of learning

Online self paced learning:

  • 180 days of access to high-quality, self-paced learning content designed by industry experts


USD 399

Live virtual classroom:

  • 90 days of access to 4+ instructor-led online training classes
  • 180 days of access to high-quality, self-paced learning content designed by industry experts
  • Flexible weekend class weekly


USD 799


What skills will you learn?

This course will enable you to:

  • 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 attributes
  • Gain an in-depth understanding of statistics, hypothesis testing, and advanced statistics techniques like clustering, decision trees, linear regression, and logistic regression
  • Learn the various techniques for combining and modifying datasets like concatenation, interleaving, one-to-one merging and reading. You will also learn the various SAS functions and procedure for data manipulation
  • Understand PROC SQL, its syntax, and master the various PROC statements and subsequent statistical procedures used for analytics including PROC UNIVARIATE, PROC MEANS, PROC FREQ, PROC CORP, and more.
  • Understand the power of SAS Macros and how they can be used for faster data manipulation and for reducing the amount of regular SAS code required for analytics
  • Gain an in-depth understanding of the various types of Macro variables, Macro function SYMBOLGEN System options, SQL clauses, and the %Macro statement
  • Learn and perform data exploration techniques using SAS
  • Understand various time series models and work on those using SAS
  • Model, formulate, and solve data optimization by using SAS and OPTMODEL procedure

Who should take this course?

There is an increasing demand for skilled data scientists across all industries that makes this course suitable for participants at all levels of experience. We recommend this data science training especially for the following professionals:

  • Analytics professionals who want to work with SAS
  • IT professionals looking for a career switch in the fields of analytics
  • Software developers interested in pursuing a career in analytics
  • Graduates looking to build a career in analytics and data science
  • Experienced professionals who would like to harness data science in their fields

Prerequisites: There are no prerequisites for this course. The free SAS Base Programmer course provides some additional coding guidance.

What projects are included in this course?

The SAS Certification training course includes four real-life, industry-based projects. Successful evaluation of one of the following projects is a part of the certification eligibility criteria.

Project 1: Attrition Analysis
Telecommunication: Analyze the employee attrition rate of a leading BPO company. The dataset is maintained for the attrition analysis, and it has records of employee_id, retain_indicator, sex_indicator, relocation_indicator, and marital_status.

Project 2: Retail Analysis
E-commerce: Forecast sales based on the independent variables such as profit, quantity, marketing cost, and expenses using the regression model.

Two additional projects have been provided for practice:

Project 3: Data-driven Macro Calls
Sales: Generate a list of all data sets in SAS which have sales related information and pass it on as the macro variable.

Project 4: Customer Segmentation
Internet: Perform customer segmentation with RFM methodology on an e-commerce website’s customer data set. Segment customers based on frequency, recency, and monetary value.

Course Curriculum

No curriculum found !


Data Science with SAS

0.1 Introduction04:21

1.1 Introduction00:55

1.2 Introduction to Business Analytics02:04

1.3 Types of Analytics

1.4 Areas of Analytics02:46

1.5 Analytical Tools00:50

1.6 Analytical Techniques

1.7 Quiz

1.8 Key Takeaways00:51

2.1 Introduction00:40

2.2 What is SAS02:34

2.3 Navigating in the SAS Console01:47

2.4 SAS Language Input Files01:55

2.5 DATA Step

2.6 PROC Step and DATA Step – Example01:44

2.7 DATA Step Processing03:51

2.8 SAS Libraries03:00

2.9 Demo – Importing Data01:15

2.10 Demo – Exporting Data00:59

2.11 Knowledge Check

2.12 Assignment

2.13 Quiz

2.14 Key Takeaways01:02

3.1 Introduction00:29

3.2 Why Combine or Modify Data00:55

3.3 Concatenating Datasets08:14

3.4 Interleaving Method03:05

3.5 Knowledge Check 1

3.6 One – to – one Reading03:09

3.7 One – to – one Merging02:57

3.8 Knowledge Check 2

3.9 Data Manipulation06:51

3.10 Modifying Variable Attributes03:57

3.11 Assignment 1

3.12 Assignment 1 Solution01:04

3.13 Assignment 2

3.14 Assignment 2 Solution03:50

3.15 Activity

3.16 Quiz

3.17 Key Takeaways00:39

4.1 Introduction00:35

4.2 What is PROC SQL01:56

4.3 Retrieving Data from a Table

4.4 Demo – Retrieve Data from a Table01:44

4.5 Knowledge Check 1

4.6 Selecting Columns in a Table04:28

4.7 Knowledge Check 2

4.8 Retrieving Data from Multiple Tables00:50

4.9 Selecting Data from Multiple Tables03:36

4.10 Concatenating Query Results02:28

4.11 Activity

4.12 Assignment 1

4.13 Assignment 1 Solution01:47

4.14 Assignment 2

4.15 Assignment 2 Solution02:13

4.16 Quiz

4.17 Key Takeaways01:05

5.1 Introduction00:41

5.2 Need for SAS Macros04:39

5.3 Macro Functions01:41

5.4 Macro Functions Examples03:03

5.5 SQL Clauses for Macros00:59

5.6 Knowledge Check

5.7 The % Macro Statement01:27

5.8 The Conditional Statement01:24

5.9 Activity

5.10 Assignment

5.11 Assignment Solution03:29

5.12 Quiz

5.13 Key Takeaways00:44

6.1 Introduction00:42

6.2 Introduction to Statistics02:31

6.3 Statistical Terms02:29

6.4 Procedures in SAS for Descriptive Statistics02:04

6.5 Demo – Descriptive Statistics01:10

6.6 Knowledge Check 1

6.7 Hypothesis Testing01:56

6.8 Variable Types01:56

6.9 Hypothesis Testing – Process

6.10 Knowledge Check 2

6.11 Demo – Hypothesis Testing01:45

6.12 Parametric and Non – parametric Tests00:51

6.13 Parametric Tests03:05

6.14 Non – parametric Tests00:46

6.15 Parametric Tests – Advantages and Disadvantages01:10

6.16 Quiz

6.17 Key Takeaways00:57

7.1 Introduction00:44

7.2 Statistical Procedures00:27

7.3 PROC Means01:12

7.4 PROC Means – Examples04:05

7.5 Knowledge Check 1

7.6 PROC FREQ01:56

7.7 Demo – PROC FREQ01:23


7.9 Demo – PROC UNIVARIATE01:27

7.10 Knowledge Check 2

7.11 PROC CORR01:21

7.12 PROC CORR Options

7.13 Demo – PROC CORR02:21

7.14 PROC REG01:14

7.15 PROC REG Options

7.16 Demo – PROC REG01:43

7.17 Knowledge Check 3

7.18 PROC ANOVA01:30

7.19 Demo – PROC ANOVA02:55

7.20 Activity

7.21 Assignment 1

7.22 Assignment 1 Solution02:36

7.23 Assignment 2

7.24 Assignment 2 Solution01:08

7.25 Quiz

7.26 Key Takeaways00:55

8.1 Introduction00:41

8.2 Data Preparation02:15

8.3 General Comments and Observations on Data Cleaning00:43

8.4 Knowledge Check

8.5 Data Type Conversion04:39

8.6 Character Functions

8.7 SCAN Function01:17

8.8 Date/Time Functions01:52

8.9 Missing Value Treatment01:50

8.10 Various Functions to Handle Missing Value

8.11 Data Summarization01:22

8.12 Assignment

8.13 Assignment Solution02:23

8.14 Quiz

8.15 Key Takeaways00:48

9.1 Introduction00:41

9.2 Introduction to Cluster03:30

9.3 Clustering Methodologies

9.4 Demo – Clustering Method03:07

9.5 K Means Clustering02:06

9.6 Knowledge Check

9.7 Decision Tree04:01

9.8 Regression04:47

9.9 Logistic Regression04:06

9.10 Assignment 1

9.11 Assignment 1 Solution01:44

9.12 Assignment 2

9.13 Assignment 2 Solution01:59

9.14 Quiz

9.15 Key Takeaways00:51

10.1 Introduction00:45

10.2 Need for Time Series Analysis03:43

10.3 Time Series Analysis — Options

10.4 Reading Date and Datetime Values02:47

10.5 Knowledge Check 1

10.6 White Noise Process03:57

10.7 Stationarity of a Time Series03:21

10.8 Knowledge Check 2

10.9 Demo — Stages of ARIMA Modelling05:47

10.10 Plot Transform Transpose and Interpolating Time Series Data

10.11 Assignment

10.12 Assignment Solution02:09

10.13 Quiz

10.14 Key Takeaways00:54

11.1 Introduction00:36

11.2 Need for Optimization02:32

11.3 Optimization Problems02:52


11.5 Optimization – Example 1

11.6 Optimization – Example 2

11.7 Assignment

11.8 Assignment Solution00:32

11.9 Quiz

11.10 Key Takeaways00:57

Project 01 Data-Driven Macro Calls

Project 02 Customer Segmentation with RFM Methodology

Project 03 Attrition Analysis

Project 04 Retail Analysis

Course Feedback



Certified SAS Base Programmer

0.1 Introduction04:35

1.1 Introduction00:57

1.2 SAS Installation and Access01:51

1.3 Opening SAS University Edition03:05

1.4 SAS Input Statements02:15

1.5 DATA Step Statement01:18

1.6 Reading Data05:04

1.7 Options Available in the Input Statement05:43

1.8 SAS Libraries02:38

1.9 Knowledge Check 1

1.10 Combining Datasets01:17

1.11 Concatenating Datasets08:07

1.12 Interleaving Method03:13

1.13 Knowledge Check 2

1.14 One-to-One Reading03:16

1.15 One-to-One Merging03:14

1.16 Knowledge Check 3

1.17 Data Manipulation00:53

1.18 Delete and Group Observations04:52

1.19 Modifying Variable Attributes03:54

1.20 Access Excel Workbook02:54

1.21 Assignment 1

1.22 Assignment 1 Solution02:33

1.23 Assignment 2

1.24 Assignment 2 Solution01:31

1.25 Quiz

1.26 Key Takeaways01:14

2.1 Introduction00:47

2.2 SAS Dataset03:04

2.3 Knowledge Check

2.4 Create and Manipulate SAS Date Values02:52

2.5 YearCutOff Option02:48

2.6 Export SAS Dataset03:02

2.7 Controlling Observation and Variables02:24

2.8 Activity

2.9 Assignment

2.10 Assignment Solution01:18

2.11 Quiz

2.12 Key Takeaways00:59

3.1 Introduction00:51

3.2 Proc Contents01:45

3.3 Proc Datasets03:32

3.4 Proc Sort01:28

3.5 Knowledge Check 1

3.6 Loop Statements08:46

3.7 Data Type Conversion05:17

3.8 Chararacter Functions

3.9 SCAN function01:26

3.10 Date Time Functions – Example03:05

3.11 Knowledge Check 2

3.12 SAS Arrays03:36

3.13 Assignment

3.14 Assignment Solution02:27

3.15 Quiz

3.16 Key Takeaways01:08

4.1 Introduction00:40

4.2 Need for Reports03:21

4.3 Proc Print04:30

4.4 Knowledge Check 1

4.5 PROC Means04:09

4.6 Knowledge Check 2

4.7 Proc Freq03:06

4.8 Proc Univariate04:01

4.9 Knowledge Check 3

4.10 Proc Report01:48

4.11 Output Delivery System (ODS)03:51

4.12 Spot the Error

4.13 Assignment

4.14 Assignment Solution02:19

4.15 Quiz

4.16 Key Takeaways01:08

5.1 Introduction00:42

5.2 Errors in SAS Program01:34

5.3 Logical Errors04:44

5.4 Syntax Errors03:25

5.5 Data Errors01:47

5.6 Spot the Error

5.7 Quiz

5.8 Key Takeaways00:49

Project 01 Generate Descriptive Analytics Report

Project Solution 0103:10

Course Feedback


That was just a sneak-peak into the lesson.Enroll for this course and get full access.

Exam & Certification


To become a Certified Data Scientist with SAS, you must fulfill the following criteria:

Complete any one project out of the two provided in the course. Submit the deliverables in the LMS to be evaluated by our lead trainer

Score a minimum of 60% in any one of the three simulation tests

Please Note:

When you have completed the course, you will receive a three-month experience certificate for implementing the projects using SAS

It is mandatory that you fulfill both the criteria: completion of any one project and passing the online exam with minimum score of 60% to become a certified data scientist

What do I need to do to unlock my Simplilearn certificate?

Live Virtual Classroom:

  • Attend one complete batch.
  • Complete one project and one simulation test with a minimum score of 60%.

Online Self-Learning:

  • Complete 85% of the course.
  • Complete one project and one simulation test with a minimum score of 60%.


You can enroll for the training online. Upon successful payment you will receive an email from Yan Academy with an activation link to access the SimpliLearn online learning platform where all learnings are conducted. Payments can be made using any of the following options and receipt of the same will be issued to the candidate automatically via email.

  • Visa debit/credit card
  • American express and Diners club card
  • Master Card, or
  • PayPal


To run SAS, your need to download and install the SAS university edition from http://www.sas.com/en_us/software/university-edition.html

We offer this SAS training in the following modes:

Live Virtual Classroom or Online Classroom: In online classroom training, you can attend the SAS course remotely from your desktop via video conferencing. This format saves time and reduces the time spent away from work or home.

Online Self-Learning: In this mode, you can go through the lecture videos at your convenience.

We provide recordings of each class after the session is conducted. If you miss a class, you can go through the recordings before the next session.

Yes, you can cancel your enrolment. We provide a complete refund after deducting the administration fee. To know more, please go through our Refund Policy.

At the end of the SAS training, after satisfactory evaluation of the project and after passing the online exam (minimum 75%), you will receive a certificate from Simplilearn stating that you are a Certified Data Scientist with SAS.

Yes, we have group discount packages for online classroom training programs. Contact Help and Support to learn more about group discounts.


All of our highly qualified trainers are industry experts with at least 10-12 years of relevant teaching experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating continue to train for us.

Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.

We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us.


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