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Data Science with SAS Certification Training

Course Summary

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.


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    Course Syllabus


    Course preview

    Data Science with SAS

    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

    Free Course Certified SAS Base Programmer

    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

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Course Fee:
USD 599

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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