COURSE MODULES:
Data Analytics 360
Module 1: Understanding and Visualizing Data
Gather and Qualify Data
Visualization and Analysis
Bring the Data into the Decision
Module 2: Implementing Scientific Decision Making
Define a Hypothesis
Test the Hypothesis
Testing and Conclusions
Module 3: Using Predictive Data Analysis
Discovering Relationships
Quantifying Impact
Assessing and Validating our Model
Applying the Predictive Analytics Framework
Module 4: Modeling Uncertainty and Risk
Making One-off and Repeating Decisions
Adjusting and Accounting for Risk
Using Monte Carlo Simulation for Nuanced Decision Making
Module 5: Optimization and Modeling Simultaneous Decisions
Using Optimization
Developing Nonlinear Models
Creating Non-continuous Models That Work
Data Analytics
Module 1: Introduction to Data Analytics
§ What is Data Analytics
§ Difference between Data Analysis and Data Analytics
§ Why do We Analyze a Data
§ Type of Analytics
§ Tools
Module 2: Business Analytics with Excel
§ Microsoft Excel fundamentals
§ Entering and editing texts and formulae.
§ Working with basic Excel functions.
§ Inserting images and shapes into an Excel worksheet.
§ Creating Basic charts in Excel.
§ Importing and exporting data.
§ Excel pivot tables.
§ Conditional function.
§ Lookup functions.
§ Data Analysis Tools
Module 3: Tableau
§ What is Data Visualization
§ Working with Dimensions
§ Data Management Filters
§ Filters in Detail
§ Advance Visuals and Features in Tableau
Module 4: Power BI
§ Introduction to Power BI
§ Getting and Transforming Data in Power Bi Desktop
§ Modeling with Power BI
§ DAX Function
§ Visualization of Data
§ Publishing Reports
5. Data Analytics with Python
§ Intro to NUMPY.
§ Arrays
§ Series.
§ Data frames.
§ Reading and writing text files.
§ Matplotlib
§ Sci-Kit Learn
§ Introduction to SQL with Python.
§ SQL SELECT, DISTINCT, WHERE, AND & OR.
§ SQL WILDCARDS, ORDER BY, GROUP BY, and Aggregate Functions.
6. SQL for Data Analytics
§ Introduction
§ ER Diagram.
§ Schema Design.
§ Normalization.
§ SQL SELECT and its Functions
§ SQL JOIN and its Function
§ AGGREGATION Function.
§ Sorting.
§ Analytic function.
§ Set operations.
§ SQL views.
§ SQL constraints
§ SQL DDL and DML operation
7. Data Analyst Project.
