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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

PYTHON INTRODUCTION

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

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