Become a Certified Data Analytics Associate with Python

1. Understanding the Data

• Introduction to Data Types

• Numerical parameters to represent data

• Mean

• Mode

• Information Gain

• Entropy

• Median

• Sensitivity

• Statistical parameters to represent data

2. Probability and its uses

• Uses of probability

• Need of probability Bayesian Inference Density Concepts

• Normal Distribution Curve

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3. Statistical Inference

• Point Estimation

• Hypothesis Testing Confidence Margin

• Levels of Hypothesis Testing

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4. Data Clustering

• Association and Dependence Simpson’s Paradox Clustering Technique Covariance

• Causation and Correlation

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5. Testing the Data

• Parametric Test Parametric Test Types Non- Parametric Test Experimental Designing A/B testing

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6. Regression Modelling

• Logistic and Regression Techniques Problem of Collinearity

• WOE and IV

• Residual Analysis Heteroscedasticity Homoscedasticity

Module 1: Introduction to Business Intelligence and Tableau

• Overview of BI

• Overview of Tableau Environment

• Putting it all together

Module 2: Data Connections

• Getting to data from Tableau Desktop

• Learning the basics of visualizing data

• Visualizing business needs

Module 3. Transforming Data

• Why transform data?

• Data Blends

• Data Joins

• Simplifying and sorting your data

• Organizing your data

• Slicing your data by date

Module 4. Calculations in Tableau

• Data Aggregates

• Calculation Wizards

• Table Calculations

• Customized Calculations

• Using calculations in Tableau

Module 5. Advanced Calculations

• Strings

• Floor and Ceiling

• Dates

Module 6. Creating and using Parameters and Filters

• Basics of filtering

• Basics of Parameters

• Putting it all together

Module 7. Sorting

• Ascending and Descending Order manually

• Computes and Sorting

• Nested Sorting

Module 8. Grouping Techniques and formatting

• Sets

• Combining Fields

• Colors

• Custom Colors

• Highlighters

Module 9. Map Basics

• Layers

• Editing

• Customizing

Module 10. Visualizations:

• Understanding Charts

• Text Charts

• Visual Charts

• Time Charts

• Trend Charts

Module 11. Introduction to Dashboards

• Designing

• Actions

• Stories

Module 12. Server Deployment:

• What is the Tableau Server?

• Working with Users

• Working with Projects

• Working with Groups

• Publishing Data Sources

• Publishing Visualizations

• Securing Projects

Module 1:

Beginning with Microsoft Data Analytics

• Data Analytics and Microsoft

• Getting Started with Power BI

Module 2:

Data Preparation in Power BI

• Obtaining Data from Various Data Sources

• Optimizing Performance

• Resolving Data Errors

Module 3:

Clean, Transform, and Load Data in Power BI

• Data Shaping

• Data Structure Enhancement

• Data Profiling

Module 4:

Creating a Power BI Data Model

• Data Modeling Fundamentals

• Working with Tables

• Dimensions and Hierarchies

Module 5:

Create Measures in Power BI Using DAX

• Introduction to DAX

• DAX Content

• Advanced DAX

Module 6:

Optimize Model Performance

• Optimize data model for performance

• Optimize DirectQuery Models

• Create and maintain aggregations

Module 7:

Report Creation

• Report Design

• Report Enhancement

Module 8:

Dashboard Creation

• Create a Dashboard

• Real-time Dashboards

• Enhance a Dashboard

Module 9:

Create Paginated Reports in Power BI

• Overview of Paginated Reports

• Creating Paginated Reports

Module 10:

Advanced Analytics

• Advanced Analytics

• Data Insights Using AI Visuals

Module 11:

Create and Manage Workspaces

• Creating Workspaces

• Sharing and Managing Assets

Module 12:

Power BI Dataset Management

• Parameters

• Datasets

Module 13:

Row-level Security

• Power BI security

Introduction to Databases & SQL

• Introduction to relational databases

• SQL flavors

• Tables

• SQL data types

• Queries

• Aggregate functions

Joins and Subqueries

• Review Day 1

• Combining data with joins

• Working with subqueries