Markovdata

Introduce SPSS

Data coding, and data entry

Importing data to SPSS from excel

Data manipulation in SPSS

Data checking and editing in SPSS Introduction to descriptive statistics using SPSS

6

Measures of central tendency for different types of data

7

Measures of Variability for different types of data

8

One-way Tabulation distinct types of variables

9

Two-way and 3-way tabulations for distinct types of variables

10

Correlation and Covariance

11

Probability

12

Probability Distributions and Central Limit Theorem

13

Inferential Statistics

Section 4

Module 3: Data Visualization (using Python)

Introduction to Data Visualization Tools

Basic and Specialized Visualization

Matplotlib and Seaborn

Different Data Charts

Advanced Visualization Tools

Geospatial Maps in Python

11

Choropleth Maps

Section 5

Module 4: Data Prediction Models

Section 6

Use Case-1

Explore US Bikeshare Data Use python to understand US bikeshare data. Calculate statistics and build an interactive environment where a user can choose the data and filter for a dataset to show.

Section 7

Use Case-2

House Sales in King County, USA Analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors and so on

Section 8

Use Case-3

Audience Interest in Data Science Topics Use python to generate visualization plots to summarize the results of a survey that was conducted to gauge an audience interest in different data science topics

Section 9

Use Case-4

San Francisco Incidents Distribution Use python Folium maps to generate a Choropleth map of the crime rate in San Francisco, based on data for one year, and show distribution of different crimes’ type and cities

Section 10

2- Data Analysis & Visualization Using Power BI (35hrs)

Section 11

Module 1: Introducing Power BI

Introduction to Power BI

The Power BI Desktop User Interface

Building Our First Visualization in Power BI

Filtering and Interactions

Using Data from Multiple Tables

6

Saving and Uploading Your Work

7

Creating and Sharing a Dashboard

Section 12

Module 2: Introduction to the Query Editor

Connecting to Multiple Files

Pivoting and Un-pivoting the Dataset

Assigning Data Types

Merging and Appending Datasets

Grouping and Aggregating Data

6

Filtering in the Query Editor

7

Formatting Columns

8

Custom and Conditional Columns

9

The M Formula Language

10

Editing Queries and Loading to Power BI

11

Connecting to Folders

Section 13

Module 3: Modeling Data

What are the Relationships?

Fact Tables vs. Dimension Tables

Star/Snowflake Schema

Viewing Relationships

Active vs. Inactive Relationships

Creating Relationships

Cross Filter Direction

9

Section 14

Module 4: Introduction to DAX

Aggregation Functions

COUNT and DISTINCTCOUNT

Section 15

Module 5: Advanced DAX

Date Functions

Time Intelligence Analysis

Working with Variables

Multiple Row Contexts

Section 16

Module 6: Interactive Data Visualizations

Power BI Reports: Page Layout and Formatting

Chart Types

Creating and Formatting Charts

Drill-through Filters

Managing & Viewing Roles

Section 17

3- Data Analysis & Visualization Using Tableau (40hrs)

Section 18

Module 1: Introduction to Tableau Desktop

Section 19

Module 2: Connecting to Data

Section 20

Module 3: Customizing a Data Source

Section 21

Module 4: Filtering Your Data

Section 22

Module 5: Sorting Your Data

Section 23

Module 6: Creating Groups in Your Data

Section 24

Module 7: Creating Hierarchies in Your Data

Section 25

Module 8: Working with Data Fields: Discrete and Continuous Time

Section 26

Module 9: Working with Data Fields: Custom Dates

Section 27

Module 10: Working with Multiple Measures: Dual Axis and Combo Charts

Section 28

Module 11: Working with Multiple Measures: Combined Axis Charts

Section 29

Module 12: Showing Relationships between Numerical Values

Section 30

Module 13: Mapping Data Geographically

Section 31

Module 14: Using Crosstabs: Totals and Aggregation

Section 32

Module 15: Using Crosstabs: Highlight Tables

Section 33

Module 16: Using Crosstabs: Heat Maps

Section 34

Module 17: Using Calculations: Customize Your Data

Section 35

Module 18: Using Calculations: Working with Strings

Section 36

Dates

Section 37

and Type Conversion Functions

Section 38

Module 19: Using Calculations: Working with Aggregations

Section 39

Module 20: Using Quick Table Calculations to Analyze Data

Section 40

Module 21: Showing Breakdowns of the Whole

Section 41

Module 22: Using Calculations: Customize Your Data

Section 42

Module 23: Highlighting Data with Reference Lines

Section 43

Module 24: Create a Dashboard: Combining Your Views

Section 44

Module 25: Create a Dashboard: Add Actions for Interactivity

Section 45

Module 26: Sharing Your Work

Section 46

Module 27: Working with a Data Extract

Section 47

Module 28: Joining Tables

Section 48

Module 29: Joining Tables Using Calculations

Section 49

Module 30: Blending Multiple Data Sources

Section 50

Module 31: Blending Data without a Common Field

Section 51

Module 32: Using Unions to Combine Data

Section 52

Module 33: Filtering Across Data Sources

Section 53

Module 34: Using Sets to Highlight Data

Section 54

Module 35: Using Context Filters to Limit Scope

Section 55

Module 36: Using Split and Custom Split

Section 56

Module 37: Controlling Table Calculations

Section 57

Module 38: Using Level of Detail Expressions

Section 58

Module 39: Filtering and LOD Expressions

Section 59

Module 40: Using Parameters to Control Data in the View

Section 60

Module 41: Parameters: Swap Measures

Section 61

Module 42: Advanced Mapping: Modifying Locations

Section 62

Module 43: Advanced Mapping: Customizing Tableau’s Geocoding

Section 63

Module 44: Advanced Mapping: Using a Background Image

Section 64

Module 45: Viewing Distributions

Section 65

Module 46: Comparing Measures Against a Goal

Section 66

Module 47: Showing Statistics and Forecasting: Use the Analytics Pane and Trend Lines

Section 67

Module 48: Advanced Dashboards: Using Design Techniques and Filter Actions

Section 68

Module 49: Telling Stories with Data