Key features

MONEY BACK GUARANTEE

How this works :

At Simplilearn, we greatly value the trust of our patrons. Our courses were designed to deliver an effective learning experience, and have helped over half a million find their professional calling. But if you feel your course is not to your liking, we offer a 7-day money-back guarantee. Just send us a refund request within 7 days of purchase, and we will refund 100% of your payment, no questions asked!

For Self Placed Learning :

Raise refund request within 7 days of purchase of course. Money back guarantee is void if the participant has accessed more than 25% content.

For Instructor Led Training :

Raise refund request within 7 days of commencement of the first batch you are eligible to attend. Money back guarantee is void if the participant has accessed more than 25% content of an e-learning course or has attended Online Classrooms for more than 1 day.

  • 32 hours of instructor-led training
  • 24 hours of self-paced video
  • 4 real-life industry projects on customer segmentation, retail analysis etc.
  • Learn SAS Macros and PROC SQL
  • Includes advanced statistical concepts on regression, clustering and forecasting
  • Includes a free SAS Base Programmer course

Course description

  • What’s the focus of this course?

    The data science with SAS certification training is designed to impart an in-depth knowledge of SAS programming language, SAS tools, and various advanced analytics techniques. The training provides a solid base for implementing these techniques. The course is packed with real-life projects and case studies to give a hands-on and practical experience to the participants.

    Mastering SAS and related tools: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization.

    Mastering advanced analytics concepts: The course also covers advanced analytics techniques like clustering, decision tree, and regression.  The course covers time series, it's modeling, and implementation using SAS.

    As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis.

  • What are the course objectives?

    This course will enable you to:
    • Understand analytics, the various analytics techniques, and the 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, etc.
    • Understand the power of SAS Macros and how it 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 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 the 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 list of all data sets in SAS which has sales related information and pass it 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 preview

    • Lesson 00 - Course Introduction 04:21
      • 0.1 Introduction 04:21
    • Lesson 01 - Analytics Overview 07:26
      • 1.1 Introduction 00:55
      • 1.2 Introduction to Business Analytics 02:04
      • 1.3 Types of Analytics
      • 1.4 Areas of Analytics 02:46
      • 1.5 Analytical Tools 00:50
      • 1.6 Analytical Techniques
      • 1.7 Quiz
      • 1.8 Key Takeaways 00:51
    • Lesson 02 - Introduction to SAS 18:47
      • 2.1 Introduction 00:40
      • 2.2 What is SAS 02:34
      • 2.3 Navigating in the SAS Console 01:47
      • 2.4 SAS Language Input Files 01:55
      • 2.5 DATA Step
      • 2.6 PROC Step and DATA Step - Example 01:44
      • 2.7 DATA Step Processing 03:51
      • 2.8 SAS Libraries 03:00
      • 2.9 Demo - Importing Data 01:15
      • 2.10 Demo - Exporting Data 00:59
      • 2.11 Knowledge Check
      • 2.12 Assignment
      • 2.13 Quiz
      • 2.14 Key Takeaways 01:02
    • Lesson 03 - Combining and Modifying Datasets 35:10
      • 3.1 Introduction 00:29
      • 3.2 Why Combine or Modify Data 00:55
      • 3.3 Concatenating Datasets 08:14
      • 3.4 Interleaving Method 03:05
      • 3.5 Knowledge Check 1
      • 3.6 One - to - one Reading 03:09
      • 3.7 One - to - one Merging 02:57
      • 3.8 Knowledge Check 2
      • 3.9 Data Manipulation 06:51
      • 3.10 Modifying Variable Attributes 03:57
      • 3.11 Assignment 1
      • 3.12 Assignment 1 Solution 01:04
      • 3.13 Assignment 2
      • 3.14 Assignment 2 Solution 03:50
      • 3.15 Activity
      • 3.16 Quiz
      • 3.17 Key Takeaways 00:39
    • Lesson 04 - PROC SQL 20:42
      • 4.1 Introduction 00:35
      • 4.2 What is PROC SQL 01:56
      • 4.3 Retrieving Data from a Table
      • 4.4 Demo - Retrieve Data from a Table 01:44
      • 4.5 Knowledge Check 1
      • 4.6 Selecting Columns in a Table 04:28
      • 4.7 Knowledge Check 2
      • 4.8 Retrieving Data from Multiple Tables 00:50
      • 4.9 Selecting Data from Multiple Tables 03:36
      • 4.10 Concatenating Query Results 02:28
      • 4.11 Activity
      • 4.12 Assignment 1
      • 4.13 Assignment 1 Solution 01:47
      • 4.14 Assignment 2
      • 4.15 Assignment 2 Solution 02:13
      • 4.16 Quiz
      • 4.17 Key Takeaways 01:05
    • Lesson 05 - SAS Macros 18:07
      • 5.1 Introduction 00:41
      • 5.2 Need for SAS Macros 04:39
      • 5.3 Macro Functions 01:41
      • 5.4 Macro Functions Examples 03:03
      • 5.5 SQL Clauses for Macros 00:59
      • 5.6 Knowledge Check
      • 5.7 The % Macro Statement 01:27
      • 5.8 The Conditional Statement 01:24
      • 5.9 Activity
      • 5.10 Assignment
      • 5.11 Assignment Solution 03:29
      • 5.12 Quiz
      • 5.13 Key Takeaways 00:44
    • Lesson 06 - Basics of Statistics 21:22
      • 6.1 Introduction 00:42
      • 6.2 Introduction to Statistics 02:31
      • 6.3 Statistical Terms 02:29
      • 6.4 Procedures in SAS for Descriptive Statistics 02:04
      • 6.5 Demo - Descriptive Statistics 01:10
      • 6.6 Knowledge Check 1
      • 6.7 Hypothesis Testing 01:56
      • 6.8 Variable Types 01:56
      • 6.9 Hypothesis Testing - Process
      • 6.10 Knowledge Check 2
      • 6.11 Demo - Hypothesis Testing 01:45
      • 6.12 Parametric and Non - parametric Tests 00:51
      • 6.13 Parametric Tests 03:05
      • 6.14 Non - parametric Tests 00:46
      • 6.15 Parametric Tests - Advantages and Disadvantages 01:10
      • 6.16 Quiz
      • 6.17 Key Takeaways 00:57
    • Lesson 07 - Statistical Procedures 29:13
      • 7.1 Introduction 00:44
      • 7.2 Statistical Procedures 00:27
      • 7.3 PROC Means 01:12
      • 7.4 PROC Means - Examples 04:05
      • 7.5 Knowledge Check 1
      • 7.6 PROC FREQ 01:56
      • 7.7 Demo - PROC FREQ 01:23
      • 7.8 PROC UNIVARIATE 02:16
      • 7.9 Demo - PROC UNIVARIATE 01:27
      • 7.10 Knowledge Check 2
      • 7.11 PROC CORR 01:21
      • 7.12 PROC CORR Options
      • 7.13 Demo - PROC CORR 02:21
      • 7.14 PROC REG 01:14
      • 7.15 PROC REG Options
      • 7.16 Demo - PROC REG 01:43
      • 7.17 Knowledge Check 3
      • 7.18 PROC ANOVA 01:30
      • 7.19 Demo - PROC ANOVA 02:55
      • 7.20 Activity
      • 7.21 Assignment 1
      • 7.22 Assignment 1 Solution 02:36
      • 7.23 Assignment 2
      • 7.24 Assignment 2 Solution 01:08
      • 7.25 Quiz
      • 7.26 Key Takeaways 00:55
    • Lesson 08 - Data Exploration 17:50
      • 8.1 Introduction 00:41
      • 8.2 Data Preparation 02:15
      • 8.3 General Comments and Observations on Data Cleaning 00:43
      • 8.4 Knowledge Check
      • 8.5 Data Type Conversion 04:39
      • 8.6 Character Functions
      • 8.7 SCAN Function 01:17
      • 8.8 Date/Time Functions 01:52
      • 8.9 Missing Value Treatment 01:50
      • 8.10 Various Functions to Handle Missing Value
      • 8.11 Data Summarization 01:22
      • 8.12 Assignment
      • 8.13 Assignment Solution 02:23
      • 8.14 Quiz
      • 8.15 Key Takeaways 00:48
    • Lesson 09 - Advanced Statistics 26:52
      • 9.1 Introduction 00:41
      • 9.2 Introduction to Cluster 03:30
      • 9.3 Clustering Methodologies
      • 9.4 Demo - Clustering Method 03:07
      • 9.5 K Means Clustering 02:06
      • 9.6 Knowledge Check
      • 9.7 Decision Tree 04:01
      • 9.8 Regression 04:47
      • 9.9 Logistic Regression 04:06
      • 9.10 Assignment 1
      • 9.11 Assignment 1 Solution 01:44
      • 9.12 Assignment 2
      • 9.13 Assignment 2 Solution 01:59
      • 9.14 Quiz
      • 9.15 Key Takeaways 00:51
    • Lesson 10 - Working with Time Series Data 23:23
      • 10.1 Introduction 00:45
      • 10.2 Need for Time Series Analysis 03:43
      • 10.3 Time Series Analysis — Options
      • 10.4 Reading Date and Datetime Values 02:47
      • 10.5 Knowledge Check 1
      • 10.6 White Noise Process 03:57
      • 10.7 Stationarity of a Time Series 03:21
      • 10.8 Knowledge Check 2
      • 10.9 Demo — Stages of ARIMA Modelling 05:47
      • 10.10 Plot Transform Transpose and Interpolating Time Series Data
      • 10.11 Assignment
      • 10.12 Assignment Solution 02:09
      • 10.13 Quiz
      • 10.14 Key Takeaways 00:54
    • Lesson 11 - Designing Optimization Models 11:47
      • 11.1 Introduction 00:36
      • 11.2 Need for Optimization 02:32
      • 11.3 Optimization Problems 02:52
      • 11.4 PROC OPTMODEL 04:18
      • 11.5 Optimization - Example 1
      • 11.6 Optimization - Example 2
      • 11.7 Assignment
      • 11.8 Assignment Solution 00:32
      • 11.9 Quiz
      • 11.10 Key Takeaways 00:57
    • Project 1
      • Project 01 Data-Driven Macro Calls
    • Project 2
      • Project 02 Customer Segmentation with RFM Methodology
    • Project 3
      • Project 03 Attrition Analysis
    • Project 4
      • Project 04 Retail Analysis
    • Course Feedback
      • Course Feedback
    • Lesson 00 - Course Introduction 04:35
      • 0.1 Introduction 04:35
    • Lesson 01 - Introduction to SAS Base Program 59:49
      • 1.1 Introduction 00:57
      • 1.2 SAS Installation and Access 01:51
      • 1.3 Opening SAS University Edition 03:05
      • 1.4 SAS Input Statements 02:15
      • 1.5 DATA Step Statement 01:18
      • 1.6 Reading Data 05:04
      • 1.7 Options Available in the Input Statement 05:43
      • 1.8 SAS Libraries 02:38
      • 1.9 Knowledge Check 1
      • 1.10 Combining Datasets 01:17
      • 1.11 Concatenating Datasets 08:07
      • 1.12 Interleaving Method 03:13
      • 1.13 Knowledge Check 2
      • 1.14 One-to-One Reading 03:16
      • 1.15 One-to-One Merging 03:14
      • 1.16 Knowledge Check 3
      • 1.17 Data Manipulation 00:53
      • 1.18 Delete and Group Observations 04:52
      • 1.19 Modifying Variable Attributes 03:54
      • 1.20 Access Excel Workbook 02:54
      • 1.21 Assignment 1
      • 1.22 Assignment 1 Solution 02:33
      • 1.23 Assignment 2
      • 1.24 Assignment 2 Solution 01:31
      • 1.25 Quiz
      • 1.26 Key Takeaways 01:14
    • Lesson 02 - Creating Data Structures 17:14
      • 2.1 Introduction 00:47
      • 2.2 SAS Dataset 03:04
      • 2.3 Knowledge Check
      • 2.4 Create and Manipulate SAS Date Values 02:52
      • 2.5 YearCutOff Option 02:48
      • 2.6 Export SAS Dataset 03:02
      • 2.7 Controlling Observation and Variables 02:24
      • 2.8 Activity
      • 2.9 Assignment
      • 2.10 Assignment Solution 01:18
      • 2.11 Quiz
      • 2.12 Key Takeaways 00:59
    • Lesson 03 - Managing Data 33:21
      • 3.1 Introduction 00:51
      • 3.2 Proc Contents 01:45
      • 3.3 Proc Datasets 03:32
      • 3.4 Proc Sort 01:28
      • 3.5 Knowledge Check 1
      • 3.6 Loop Statements 08:46
      • 3.7 Data Type Conversion 05:17
      • 3.8 Chararacter Functions
      • 3.9 SCAN function 01:26
      • 3.10 Date Time Functions - Example 03:05
      • 3.11 Knowledge Check 2
      • 3.12 SAS Arrays 03:36
      • 3.13 Assignment
      • 3.14 Assignment Solution 02:27
      • 3.15 Quiz
      • 3.16 Key Takeaways 01:08
    • Lesson 04 - Generating Reports 28:53
      • 4.1 Introduction 00:40
      • 4.2 Need for Reports 03:21
      • 4.3 Proc Print 04:30
      • 4.4 Knowledge Check 1
      • 4.5 PROC Means 04:09
      • 4.6 Knowledge Check 2
      • 4.7 Proc Freq 03:06
      • 4.8 Proc Univariate 04:01
      • 4.9 Knowledge Check 3
      • 4.10 Proc Report 01:48
      • 4.11 Output Delivery System (ODS) 03:51
      • 4.12 Spot the Error
      • 4.13 Assignment
      • 4.14 Assignment Solution 02:19
      • 4.15 Quiz
      • 4.16 Key Takeaways 01:08
    • Lesson 05 - Handling Errors 13:01
      • 5.1 Introduction 00:42
      • 5.2 Errors in SAS Program 01:34
      • 5.3 Logical Errors 04:44
      • 5.4 Syntax Errors 03:25
      • 5.5 Data Errors 01:47
      • 5.6 Spot the Error
      • 5.7 Quiz
      • 5.8 Key Takeaways 00:49
    • Project 03:10
      • Project 01 Generate Descriptive Analytics Report
      • Project Solution 01 03:10
    • Course Feedback
      • Course Feedback
    • {{childObj.title}}
      • {{childObj.childSection.chapter_name}}
        • {{lesson.title}}
      • {{lesson.title}}

    View More

    View Less

Exam & certification FREE PRACTICE TEST

  • How to get certified?

    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 of the project in the LMS which will be evaluated by our lead trainer
    • Score a minimum of 60% in any one of the three simulation tests
    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 i.e., completion of any one project and clearing 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?

    Online Classroom:
    • You need to attend one complete batch.
    • Complete 1 project and 1 simulation test with a minimum score of 60%.
    Online Self-Learning:
    • Complete 85% of the course.
    • Complete 1 project and 1 simulation test with a minimum score of 60%.

Reviews

I had enrolled with Simplilearn for Data Science with SAS course (self-learning). The content provided was very good and the explanation provided were simple to understand. I also got frequent meeting invites from Simplilearn to clear any doubts on project submission. Great way to add stars to your resume by taking up the certifications.

Read more Read less

The session was nice. The course orientation and topic insight was very informative. I would definitely suggest this R programming to my colleagues. Thanks to the trainer for making this course so interesting.

Read more Read less

"It is a wonderful experience and the best educational course that I enrolled in Simplilearn. Very easy to go through, and all the guides and ebooks are on the site. It’s easy to plan and schedule the modules your learning and manage your workload at the same time your studies. Thank you support team for helping and assisting me in the course and providing assistance and updates on other courses. Wish you all the best.

Read more Read less

Good course and material. It has installation steps, demo, and real-life study case.

I already had some technology and project management experience and took this training to get an understanding of the analytics domain. This course is structured and designed well, it makes the concepts easy to grasp. The statistical input was the best part as it really changes the way you look at data. The projects were really interesting and I actually went ahead and completed 2 of them. Simplilearn support is good and all my queries were handled promptly. I have already recommended this training to my team.

Read more Read less

Course was very good and I learned everything about data analysis from nothing. You can learn everything about SAS and Excel from this course.

Read more Read less

This exposure on SAS and Excel is a must before taking advanced course in analytics.

I was recognized instantly as an expert in Data Science within my organization. The course has provided me with an opportunity to establish myself as a strong candidate for the ongoing and future data projects. I have been able to suggest and recommend confidently based on the knowledge that I got from the course. It has been a great stepping stone as well in my career path.

Read more Read less

The data scientist training is a must for someone who wants to build a career in this field. It is filled with real world examples and exercises which helped me gain a new perspective to the subject. I am from a non-coding background and I was able to follow the course content with ease. My firm is starting a data science division and this training has now made me eligible for the role of a data science consultant in the division. I am thankful to Simplilearn for all the help.

Read more Read less

Course advisor

Ronald van Loon
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, and he regularly speaks at renowned events.

FAQs

  • What are the System Requirements?

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

  • Who are the trainers?

    The trainings are delivered by highly qualified and certified instructors with relevant industry experience.

  • What are the modes of training offered for this course?

    We offer this training in the following modes:
    Live Virtual Classroom or Online Classroom: In online classroom training, you have the option to attend the course remotely from your desktop via video conferencing. This format saves productivity challenges and decreases your time spent away from work or home.
    Online Self-Learning: In this mode, you will receive the lecture videos and you can go through the course as per your convenience.

  • What if I miss a class?

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

  • Can I cancel my enrolment? Do I get a refund?

    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.

  • Who provides the certification?

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

  • Are there any group discounts for classroom training programs?

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

  • What are the payment options?

    Payments can be made using any of the following options and a receipt of the same will be issued to you automatically via email.
    • Visa Debit/credit Card
    • American Express and Diners Club Card
    • Master Card, Or
    • PayPal

  • Who are our Faculties and how are they selected?

    All our trainers are working professionals and industry experts with at least 10-12 years of relevant teaching experience.

    Each of them have gone through a rigorous selection process which includes profile screening, technical evaluation, and 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.

  • What is Global Teaching Assistance?

    Our teaching assistants are here to help you get certified in your first attempt.

    They are a dedicated team of subject matter experts to help you at every step and enrich your learning experience from class onboarding to project mentoring and job assistance.

    They engage with the students proactively to ensure the course path is followed.

    Teaching Assistance is available during business hours.

  • What is covered under the 24/7 Support promise?

    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.

Contact Us

+1-844-532-7688

(Toll Free)

People also bought this Masters Program:

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.
/index/hidden/ - Never remove this line