Complete & Practical SAS, Statistics & Data Analysis Course
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Complete & Practical SAS, Statistics & Data Analysis Course

A complete guide and use cases study for job seekers and beginners -- start career in SAS, Statistics and Data science
4.0 (404 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
3,395 students enrolled
Last updated 3/2017
English
Current price: $10 Original price: $90 Discount: 89% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 16.5 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Be equipped with a powerful tool for the most sexy data analytics career path!
  • Read and write various types of raw data with different formats and options
  • Create and modify various professional and statistical reports
  • Be aware of statistical analysis and concepts such as non parametric test, interaction, correlation..
  • Master the most complete SAS graphics tool such GTL and statistical plots
  • Learn comprehensive SAS Macro programming knowledge -- variables and user defined functions
  • Perform many real world case studies -- retail banks, credit bureau, marketing firms and clinical trials
  • Apply powerful data manipulation -- SQL, subsetting, slicing, filtering, transformation, ranking, sorting..
  • Understand data management and data piping
  • Use SAS ODS -- help deliver many useful objects such as charts, tables between different systems
  • Hundreds of SAS sample codes to explain arrays, functions and business cases
View Curriculum
Requirements
  • Basic computer operational skills.
  • Basic math skills.
  • Data intuition
Description

You should take this course! 

• If you need a complete and comprehensive package that covers SAS programming, intuitive statistics interpretation, data analysis, and predictive modeling, and

• If you would like to learn by doing various practical use cases fitting in the positions in different business portfolios, and

• Whether you are a job seeker or beginner intending to start a data science career

Then this around 18 hours course is right for you!

This complete SAS course includes more than 150 lectures and contains 11 real world case studies/projects in different applied areas such as banking and marketing. After this intensive training, you will be equipped with a powerful tool for the most sexy data analytics career path!

Who is the target audience?
  • Beginners or job seekers interested in learning SAS Programming, statistical and data analysis in industry fields.
  • People who wish to enter data science/analytics field.
Compare to Other Statistics Courses
Curriculum For This Course
169 Lectures
16:19:01
+
Introduction
1 Lecture 14:47

This tutorial describes what are you going to take away from this complete training for job seekers and beginners

Preview 14:47
+
SAS environment and basic concepts
4 Lectures 15:11

We will learn key windows under SAS environment

Introduce SAS environment
00:47

Learn concepts about SAS library 

SAS library
02:11

Learn SAS environment, library and data creating by running SAS program 

Try SAS codes
02:51

This is a guide to let you know how to set up homework. A zipped file (resource) is provided in this session

Home work and data installation
09:22
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Get started SAS programming
9 Lectures 22:22

Learn how to create SAS data sets from external files such as .TXT and .CSV. 

Create data sets from external files
02:11

In this lecture, we will learn how a SAS program is running and generate physical data sets.

SAS program - create data sets
03:03

In this lecture we learn, what are correct naming rules in SAS and how to set comments in SAS programming

Valid names and comments
01:38

SAS program -- Valid names and comments
02:06

In this lecture we learn, what are data types and formats which can be used in SAS data and programming

Data type and format
02:51

SAS program -- data type and format
04:07

SAS program - date and format
02:39

In this lecture, we will learn how a SAS program is running and generate physical data sets.

Mechanism of SAS data set
01:23

In this lecture we learn, what are major SAS operations which can be realized using the SAS programming knowledge and skills that we will learn in the later sections. 

Summarize SAS operations
02:24
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Input and output raw data
9 Lectures 36:20

In this lecture we learn, what is list input in SAS, How should we create a SAS data set by reading data using list input method.

List input (1)
02:13

List input (2)
01:42

SAS program -- list input
04:58

In this lecture we learn, how to read raw data if the data format and potions are fixed.

Read data with fixed layout
03:07

In this lecture we learn,about inputting data using input modifiers under some special cases such as date type in SAS . .

Read data with modified list input
02:59

Input data with other features
13:17

In this lecture we learn, how to write SAS data into external files such as TXT and CSV

Write data using data step
01:28

SAS program --write data
02:28

In this lecture we learn, how to import and export data using Wizard tools and SAS coding methods.

Import and export data
04:08
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Manipulate data by data step programming
11 Lectures 22:01

In this lecture we learn, how to duplicate data sets in SAS.

Duplicate data sets
00:46

SAS program -- duplicate data sets
01:20

We will learn how to add and modify columns or variables of SAS data sets using data step

Modify variables
00:32

SAS program -- modify variables
01:21

We'll look at using various data step statements on column selection.

Variables selection.
04:25

We'll see how how to change column names in SAS data sets

Rename variables
01:00

SAS program -- rename variables
01:30

We will learn what is label and how to assign labels to variables in SAS data sets

Assign labels to variables
01:36

SAS program -- assign labels to variables
02:08

Introduce some methods for subsetting data sets

Subsetting data sets
06:05

SAS program -- Subsetting data sets
01:18
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Control flow in SAS
4 Lectures 20:14
Structured programming (I)
07:30

SAS program -- Structured programming (I)
04:47

Structured programming (II)
03:50

SAS program -- Structured programming (II)
04:07
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SAS data step functions
8 Lectures 44:24

In this lecture, we will learn how to use data step character functions  

Data step character functions
05:48

SAS program --data step character functions
03:49

Data step numeric functions
02:12

SAS program -- numeric functions
05:47

Data step special functions
02:30

In this lecture we learn, How to apply date and special functions and how to improve performance in data steps

Data step special functions
09:53

In this lecture we learn, what is user defined format and PROC format in SAS, How to create your own data formats to tailor your different needs .

User defined format
04:40

SAS program -- User defined format
09:45
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Use cases study (1)
8 Lectures 17:06

In this lecture we walk though the data reading using employee data set in SAS

Case study 001(read employee data)
02:07

SAS program -- read employee data
03:00

In this lecture we walk though the data reading using pharmaceutical data set in SAS. Codes can be downloaded

Case study 002(read chronic disease data)
01:16

SAS program -- Case study 002(read chronic disease data)
03:04

In this lecture we walk though the data reading using business account data set in SAS. Codes can be downloaded

Case study 003 ( read business account data)
00:26

SAS program -- Case study 003 ( read business account data)
01:49

In this lecture we walk though the data reading using stock market data set in SAS. Codes can be downloaded

Case study 004 (process stock data)
01:35

SAS program -- Case study 004 (process stock data)
03:49
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Other SAS features in data step programming
9 Lectures 01:00:36

In this lecture we learn, what is automatic SAS variable. Specifically, we introduce the usages of _N_ and _ERROR_ in data step programming  

Automatic Variables(_N_ and _ERROR_)
11:03

In this lecture we show, how to use output statement in data step.

Output statement
08:24

In this lecture we learn, how to apply a return statement and break loop in SAS.

Return statement
10:59

pinpoint the first and last record
02:35

In this lecture we learn, how to use first and last statements to pinpoint the first and last record in SAS data sets

SAS program -- Pinpoint the first and last record
01:34

In this lecture we learn, how to handle the previous record using retain statement

Retain statement
06:41

SAS program -- Retain statement
02:49

In this lecture we learn, what is SAS array and how to apply array in data step

Data step array (1)
08:53

In this lecture we learn, what is SAS array and how to apply array in data step

Data step array (2)
07:38
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Use cases study (2)
2 Lectures 22:06

In this lecture we learn, how to create new variables in SAS data set

Case study 005(create new KPI features)
12:13

In this lecture we learn, how to apply array Technics in SAS data step to grade students' multiple choice exam. 

Case study 006(students grades)
09:53
11 More Sections
About the Instructor
Doctor Shenggang Li
4.0 Average rating
403 Reviews
3,395 Students
1 Course
Senior Data Scientist

Having successfully led the development of cutting-edge risk models using Big data at multiple major financial institutions and excelled in the advanced analytics field for the past 15 years, I am very enthusiastic at transferring  knowledge and skills to the job seekers and new comers in the field of data analytics and application to business.

I hold a PhD in Statistics and operational research. I am also a passionate educator, teaching as a principal instructor of a Toronto-based college, including advanced SAS data mining, Python & R for data science and machine learning and Big data analytics foundation and projects and  for over 10 years. As a result, I have helped many of my students land their dream jobs in advanced analytics.

I am also a Big data experts in machine learning, predictive modelling and retail/marketing analytics in Canada. My work includes but not limited to: implementation of Big data analysis for credit bureau, model vetting and validation for banking capital market, and customers attrition and life stage/life style segmentation for retail banks as well as big market firms. I also worked closely with senior executives and Big data architects in the field of health science to provide strategic advice.