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Data Analytics Bootcamp

In today’s tech-driven society, data touches almost every aspect of our lives. The field of data analytics combines information technology and business management to help companies manage data, gain business insights from it, and develop opportunities for expansion.

What you'll learn -

  • MySQL
  • MS Excel
  • Python
  • PowerBI
  • Tableau
  • Data Visualization
  • Exploratory Data Analysis (EDA)
  • Statistics
  • Machine Learning
  • Capstone Project

 

Requirements -

  • System with Good Internet Connectivity
  • Curious to Learn
  • Full Dedication

 

Course Curriculum -

 

 

MySQL 

  • Introduction & Installation
  • Overview of Databases
  • SQL Statement & Fundamentals
    • CREATE DATABASE
    • SHOW DATABASE
    • USE DATABASE
    • CREATE TABLE
    • INSERT INTO
    • SELECT
    • DROP TABLE
    • DROP DATABASE
    • NULL VALUES
    • AUTO INCREMENT
    • UPDATE
    • RENAME TABLE
    • DELETE
    • ALTER DATABASE
    • ALTER TABLE
    • CREATE INDEX
    • DROP INDEX
    • DESCRIBE TABLE
    • WHERE
    • AND, OR, NOT
    • ORDER BY
    • LIMIT
    • Aggregate Function
    • Wildcard
    • IN
    • BETWEEN
    • Aliases
  • Overview of Databases
  • Data Type
  • Constraints
    • Not Null
    • Unique
    • Primary Key
    • Foreign Key
    • Check
    • Default
    • Create Index
  • Views
  • Joins
    • Inner Join
    • Left Join
    • Right Join
    • Cross Join
    • Self-Join
  • UNION
  • UNION ALL
  • GROUP BY
  • HAVING
  • EXISTS
  • ANY, ALL
  • INSERT SELECT
  • CASE
  • NULL Functions
  • Comments
  • Operators
  • Function
    • String Functions
    • Numeric Functions
    • Date Functions
    • Window Functions
  • PostgreSQL
  • SQL Assignments
  • SQL Project

  

 

Microsoft Excel

  • Introduction & Installation
  • Overview of MS Excel
  • Understanding the Structure of the Workbook & Worksheet
  • Introduction to the Excel Interface
  • Syntax
  • Ranges
  • Fill
    • Copying
    • Sequences
    • Dates
    • Functions(*)
  • Move Cells
  • Add Cells
  • Delete Cells
  • Undo Redo
  • Relative Reference
  • Absolute Reference
  • Arithmetic Operators
  • Parentheses
  • Format
    • Format Painter
    • Format Colors
    • Format Fonts
    • Format Borders
    • Format Numbers
    • Format Grids
    • Format Settings
  • Data Analysis
    • Sort
    • Filter
    • Tables
    • Conditional Format
    • Highlight Cell Rules
    • Top Bottom Rules
    • Data Bars
    • Color Scales
    • Icon Sets
    • Manage Rules
    • Charts
  • Functions & Formulas
    • AND, OR, NOT
    • AVERAGE, AVERAGEIF, AVERAGEIFS
    • CONCAT, COUNT, COUNTA, COUNTBLANK, COUNTIF, COUNTIFS
    • IF, IFS, IFERROR, IFNA
    • LEFT, RIGHT
    • LOWER
    • MAX, MEDIAN, MIN, MODE
    • Net Presend Value (NPV)
    • RAND, RANDBETWEEN, RADIANS, RATE, etc
    • STDEV.P, STDEV.S
    • SUM, SUMIF, SUMIFS, SUBTOTAL, SUMPRODUCT, etc
    • TRIM, TRANSPOSE, TREND, TRUNC, etc
    • XOR
    • Remove Duplicate
  • Pivot Table
  • VLOOKUP, HLOOKUP
  • Basic Macros
  • Assignments
  • Project

  

 

Python

  • Introduction and Software Installation
    • Anaconda Installation
    • Jupiter Notebook Installation
    • Introduction
  • Basic of Python
    • History of Python & Its Importance
    • Introduction of Jupiter Notebook
    • Data Types in Python
    • Literals
    • Arithmetic Operations
    • String Operations
    • Slicing
  • Data Structures in Python
    • Tuples
    • Lists
    • Sets
    • Dictionaries
    • Numpy
    • Matplotlib
    • Pandas
  • Control Structures and Functions in Python
    • Decision Making
    • Loops and Iterations
    • Iterator
    • Comprehensions
    • Functions in Python
    • Lambda Function
    • Map
    • Filter and Reduce Functions
  • Industry Immersion
    • Industry Immersion in the Program
    • Roles in the Data Industry
  • OOP in Python
    • Introduction
    • Class and Objects
    • Methods
    • Class Inheritance and Overriding
    • Polymorphism
    • Encapsulation
    • Inheritance
    • Data Abstraction
  • File Handling
  • Exception Handling
  • Assignments
  • Project

  

 

PowerBI

  • Introduction and Software Installation
  • Basic of Power BI
    • Data Sources & Visual Types
    • Canvas, Visualizations, and Fields
    • Get Data and Memory Tables
    • Table and TreeMap Visuals
    • Format Button and Data Labels
    • Legend, Category, and Grid
    • Visual Interaction, Data Points
    • Disabling Visual Interactions
    • Edit Interactions - Format Options
    • SPOTLIGHT & FOCUS MODE
    • CSV and PDF Exports. Tooltips
    • Power BI Ecosystem, Architecture
  • Visual Sync, Grouping
    • Slicer Visual: Real-time Usage
    • Orientation, Selection Properties
    • Single & Multi Select, CTRL Options
    • Slicer: Number, Text and Date Data
    • Slicer List and Slicer Dropdowns
    • Visual Sync Limitations with Slicer
    • Disabling Slicers, Clear Selections
    • Grouping: Real-time Use, Examples
    • List Grouping and Binning Options
  • Hierarchies, Filters
    • Creating Hierarchies in Power BI
    • Independent Drill-Down Options
    • Dependant Drill-Down Options
    • Conditional Drilldowns, Data Points
    • Drill Up Buttons and Operations
    • Show Data and See Records
    • Filters: Types and Usage in Real-time
    • Visual Filter, Page Filter, Report Filter
    • Basic, Advanced, and TOP N Filters
    • Category and Summary Level Filters
    • Cross Report Filters, Include, Exclude
  • Bookmarks, Azure, Modelling
  • Visualization Properties
    • Stacked Charts and Clustered Charts
    • Line Charts, Area Charts, Bar Charts
    • 100% Stacked Bar & Column Charts
    • Map Visuals: Tree, Filled, Bubble
    • Cards, Funnel, Table, Matrix
    • Scatter Chart: Play Axis, Labels
    • Series Clusters & Selections
    • Waterfall Chart and ArcGIS Maps
    • Join Types: Round, Bevel, Miter
    • Shapes, Markers, Axis, Plot Area
    • Series, Custom Series, and Legends
  • Publishing Reports & Power BI Services
  • Scheduling, Data Gateway & Mobile App
  • Row Level & Page Level Security
  • Assignments
  • Project

 

 

 Tableau

  • Introduction and Software Installation
  • Data Exploration in Tableau
    • Introduction
    • Data Formats and Tableau Interface
    • Connecting to Excel Files
    • Connecting to Text Files
    • Connect to Microsoft SQL Server
    • Connecting to Microsoft Analysis Services
    • Creating and Removing Hierarchies
    • Bins
    • Joining Tables
    • Data Blending
  • Basic Reports
    • Parameters
    • Edit Groups
    • Set
    • Combined Sets
    • Creating a First Report
    • Data Labels
    • Create Folders
    • Sorting Data
    • Add Totals, Sub Totals and Grand Totals to Report
  • Visualising and Analysing Data
    • Bar Charts
    • Scatter Plots and Pie Charts
    • Tree Maps
    • Dual Axes Charts
    • Histograms
    • Box Plots
    • Area Maps
    • Calculations
    • Dashboard and Stories
  • Advanced Reports
  • Calculations & Filters
  • Data Server
  • Tableau Server UI
  • Assignments
  • Project

 

Data Visualization

  • Module Introduction
    • The Necessity of Data Visualization
    • Module Overview
    • Visualizations - Some Examples
    • Data Handling and Cleaning
    • Sanity Check
    • Outliers Analysis with Boxplots
    • Histograms
    • Distribution Plots
    • Styling Options
  • Data Visualization with Seaborn
    • Distribution Plots
    • Styling Options
    • Pee - Charts and Bar Chart
    • Scatter Plots
    • Pair Plots
    • Revisiting Bar Graphs and Box Plots
    • Heatmaps
    • Line Charts
    • Stacked Bar Charts
    • Plotly
  • Assignments
  • Project

 

 

 Exploratory Data Analysis (EDA)

  • Data Sourcing
  • Data Cleaning
  • Univariate Analysis
  • Bivariate and Multivariate Analysis
  • Assignments
  • Projects

 

 

Statistics

  • Introduction to Probability
  • Basics of Probability
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Central Limit Theorem
  • Assignments
  • Projects

 

 

Machine Learning

  • Linear Regression
  • Logistic Regression
  • Unsupervised Learning: Clustering
  • Business Problem Solving
  • Tree Models
  • Model Selection
  • Unsupervised Learning: Principal Component Analysis
  • Advanced Regression
  • Boosting
  • Time Series Forecasting
  • Assignments
  • Projects

Capstone Project

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