- IIE JOB ASSURED PROGRAM
DATA ANALYTICS
Course Description
Data analytics is the process of examining raw data to draw conclusions about the information it contains. It involves applying statistical analysis, machine learning algorithms, and other techniques to identify patterns, trends, correlations, and insights within large datasets. The goal of data analytics is to extract valuable insights that can inform decision-making & drive business improvements. Data analytics is widely used across various industries and domains, including business, finance, healthcare, marketing, and government. It plays a crucial role in improving decision-making, optimizing processes, identifying opportunities, mitigating risks, and gaining a competitive advantage.
Curriculum
Installation and Setting up path
Features
Python variables
Input & Output and Import
Why Learn Python
Who used Python
Using Pycharm & Scripting
Keywords & Identifiers
Operators, Indentations
Basic Data types: int, float, string, Boolean and Complex
Numbers and String
Tuple and List
Dictionary and Set
Arrays
String, String slices
Date
Math
Random and Statistics
PDF Data Extraction
CVS module
Introduction to Tuples
Working with Tuples
Tuple Operations
Function and Methods
Introduction to Lists
Working with lists
Lists Operations
Function and Methods
Introduction to Sets
Working with Sets
Sets Operations
Function and Methods
If…else
Elif
For, for else, while
Break and Continue, Pass
Looping Techniques
Types of Functions
Function Arguments
Recursion
Anonymous Function
Global, local and Nonlocal
Lambda Functions
Modules
Packages
Reading & Writing Files
Manipulating File Pointer
Type of Files
File Operations
Directories
File I/O Attributes, File Methods
Try, Except and Finally
Try else
Custom Exception
Error Vs. Exception
Real-time in OOPS
Access Specifiers
Class and Objects
Methods, Overloading and Overriding
Inheritance
Abstraction and Data Hiding
Properties &Self-keyword
OS module
Environment variables,
Paths, directories, and filenames.
Working with file systems, Dates and times
Starting a New Thread
Creating Thread Using Threading Module
Synchronizing Threads
Multithreaded Priority Queue
My SQL & Mongo Database Connection with Python
CRUD
Queries in MySQL
Working with XML
DOM and SAX introducing
Parsing JSON into Python
Pattern matching and searching
Real time parsing of networking or system data using regex
Validation Concepts
Working with tkinter module
Grid Positions
Create Button
Radio Button & Combo Box
Check Box & Menu bar
Sending email
Sending html email using python
Sending attachments as an email
Introduction to Django
Django and python
MVC: Model View and Template
Numpy Introduction
Numpy Arrays
Data Types in Numpy
Array Indexing
Array Slicing
Array Shape
Array Reshape
Array Iteration
Array Join
Array Split
Array Search & Sorting
Array Filter
Introduction
Pandas Series
Pandas Data Frames
Pandas Read CSV & JSON
Pandas Analyzing Data
Data Cleaning
Introduction
Pyplot
Plotting
Markers
Line
Labels
Grid
Subplot
Scatter Plot
Bar Chart
Histogram
Pie Chart
Dataset Information
Description
Dataset Unique & Missing Values
Indexing, Plotting
Separators, Converters
Merge, Concat, Groupby, Pivot
BI Concepts
What is TABLEAU? Why Data Visualization?
Unique Features compared to Traditional BI Tools
TABLEAU Overview & Architecture
File Types & Extensions
Data Connections in the Tableau Interface
Connecting to Tableau Data Server
Types of Join
When to Use Joining
What is Data Blending
When to Use Data Blending
Joining vs. Blending
Creating Data Extracts in Tableau
Shadow Extracts
Prepare your Data for Analysis
Filters. Applying Filters
Quick Filters
Sorting of Data
Creating Combined Fields
Creating Groups and Defining Aliases
Working with Sets and Combined Sets
Drill to Other Levels in a Hierarchy
Grand totals and Subtotals
Tableau Bins
Fixed Sized Bins
Variable Sized Bins
Creating and using Parameters
Exploring Parameter Controls
Using parameters for titles, field selections, logic statements, Top X
Cross Tabs [Pivot Tables]
Page Trials
Total and Sub-Total
Working with Combined Axis
Working with Combination Charts
Working with Geocoding and Geographic Mapping
Using Scatter Plots
Using Text tables and Highlight tables
Using Heat Maps
Using Histograms
Using Pie Charts
Using Bullet Charts
Using Pareto Charts
Using Waterfall Charts
Using Gantt Charts
Using Box Plots
Using Sparkline Charts
Using Density Charts
Using KPI Charts
Small Multiples Working with aggregate versus disaggregate data
What is Market Basket Analysis
Performing Market Basket Analysis
Formatting
Options in Formatting Visualizations
Working with Labels and Annotations
Effective Use of Titles and Captions
Introduction to Visual Best Practices
Importing and Modifying Custom Geocoding
Working with Symbol Map and Filled Map
Using Background Image
Exploring Geographic Search
Perform Pan Zoom Lasso and Radial Selection
Working with WMS Server Maps [Web Map Service]
Add Reference Lines Bands and Distribution
Adding Reference Lines
Adding Reference Bands
Adding Reference Distribution
Working Reference Lines Bands and Forecasting
Trend lines and Trend Models
Build Interactive Dashboards
Best practices for creating effective dashboards
Creating a Dashboard and Importing Sheets
Interaction Exploring Dashboard Actions
Use of Running Actions & Dashboard Actions
How to Share your Reports & Exporting your Work
What is Power BI
Why we have to use?
Components
Data Sources
Power BI vs Tableau
Using Data Modeling and Navigation
Creating Calculated Columns
Creating Calculated Tables
Managing Time-Based Data
Exploring Different Datasets
Creating and Sharing Dashboards
Tiles in Dashboard
Data Gateway
Creating Simple Visualizations
Creating Map Visualizations
Using Combination Charts
Using Tables
Modify Colors in Charts
Adding Shapes, Images and Text box
Styling Reports
Duplicating Reports
Using Excel Data
Importing xlsx Files
Using Power BI Desktop for Report Sharing
Printing Power BI Dashboards
Export Options
Publishing Report to Web
Using & Editing
Content Pack
DAX Architecture, Entity Sets
DAX Data Types, Syntax Rules
DAX Measures and Calculation
Data Modeling Options in DAX
Purchasing
REST API
Security
FORMULAS & FUNCTIONS
Aggregate Function
Logical Function
Lookup & References
Financial Functions
Formatting and Proofing
Conditional Formatting using New Rule
Conditional Formatting using Formula
Creating Simple Pivot Tables
Classic Pivot table
Basic and Advanced Value Field Setting
Calculated Field & Calculated Items
Grouping based on numbers and Dates
Activating Power pivot
Usage of Data model
DAX Calculation
Relational Data
Using SLICERS, Filter data with Slicers
Various Charts i.e. Bar Charts/Pie Charts/Line Charts
Manage Primary and Secondary Axis
Number, Date & Time Validation
Text and List Validation
Custom Validation
Dropdown List Validation
Creating Scenarios
Working with Data Tables
Using Goal Seek
Using Solver
Using Consolidating Data by Position or
Category
Consolidating Data Using Formulas Excel
Macro Builder
Create a standalone macro
Create an embedded macro
Add actions to a macro
Control program flow with If, Else If, and Else
Create sub macros
Group related actions together
Expand and collapse macro actions or blocks
Copy and paste macro actions
Share a macro with others
Get started with database, SQL and MySQL
What is database?
Why use SQL?
Importance of MySQL
First Steps in SQL
Creating a database
Introduction to data types
Creating a table
Get acquainted with the interface
DDL
DCL
DML
TCL
Relational Database essentials
Primary key
Foreign key
Unique key and null values
Load the database
Loading employees’ database
Starting with SELECT statement
Select-From Where
And-Or
(In-not in)
Like-not like
Wildcard characters0
Between-and
Is not null-is null
Select distinct
Aggregate statement
Order by-Group by
Using Aliases
Having and Limit
Insert statement
Inserting data INTO table
Update statement Commit and rollback
Delete statement
Drop vs Truncate
AGGREGATE FUNCTIONS
Functions
Count
Sum
Min() and Max
Avg
Round()
Maped Certification
PCEP-30-xx
PCAP-31-xx
PCPP-32-1xx
PCPP-32-2xx
Exit Profile
Data Analyst
Data Scientist
Data Architect
Business Intelligence Developer
Machine Learning Scientist
Back-end Developer
Quality Assurance Engineer
