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Data Science with SAS Certification Training Course Agenda
Lesson 1: Analytics Overview
- Definition of Analytics
- Types of Analytics
- Analytics Problem Types
- Widely used tools and analytical techniques
Lesson 2: SAS Introduction
- Introduction of GUI
- Library statement, understanding of PDV
- Import / Export of Data
- Variable Attributes
- Basic Procedures
Lesson 3: Combining/Modifying Datasets
- Combining Data Sets Methods
- Concatenation
- Interleaving
- One to One Reading
- One to One Merging
- Data Manipulation steps and tools
- SAS Functions and Procedures for Data Manipulations
Lesson 4: PROC SQL
- Introduction and Advantages
- Options and Syntax – Understanding of Select Statement
- Joins in SQL
- Merge v/s Join
Lesson 5: SAS Macros
- Need for SAS Macros
- Macro Variables
- Automatic Macro Variables
- User-defined Macro Variables
- Macro Functions
- SYMBOLGEN System Option
- SQL Clauses for Macros
- The %Macro Statement
Lesson 6: Basic Statistics
- Descriptive Statistics
- Inferential Statistics
- Hypothesis testing
- Non parametric tests
Lesson 7: Basic Statistical Procedures
- PROC UNIVARIATE
- PROC MEANS
- PROC FREQ
- PROC CORR
- PROC REG
- PROC ANOVA
Lesson 8: Data Exploration
- Data Preparation
- Data Type Conversion
- Missing Value Treatment
- Summarizing Data
Lesson 9: Advanced Statistical Techniques
- Clustering
✓ Introduction
✓ Clustering Methodology
✓ Data Preparation
✓ K Means Clustering
✓ Cluster Profiling
- Decision Trees
✓ Introduction
✓ Creating Decision Trees
- Linear Regression
✓ Introduction
✓ Linear Regression in SAS
✓ Diagnostics
- Logistic Regression
✓ Introduction
✓ Logistic Regression in SAS
✓ Diagnostics
Lesson 10: Working with Time series Data
- Reading Simple Time Series
- Dating time series and working with SAS date and date time values
- Sub setting data and selecting observations
- Storing time series data in SAS data sets
- Plotting, transforming, transposing, interpolating
Lesson 11: Data Optimization using SAS
- Data Optimization
- Creating optimization models commonly used in industry
- Formulating and solving a data envelopment analysis
- Solving optimization problems using the OPTMODEL procedure in SAS
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