Data Analytics

I Will Prefer The Python Programming Language. Python Is The Best For Starting Your Programming Journey. Here Is The Roadmap Of Python For Logic Building.

Introduction And Basics

• Installation
• Python Org, Python 3
• Variables
• Print Function
• Input From User
• Data Types
• Type Conversion
• Why Python For Data Analysis And Data Science
• How To Install Anaconda
• Running Few Sample Programs Using Python

Operators

• Arithmetic Operators
• Relational Operators
• Bitwise Operators
• Logical Operators
• Assignment Operators
• Compound Operators
• Membership Operators
• Identity Operators

Conditional Statements

• If Else
• If
• Else
• El If (Else If)
• If Else Ternary Expression

While Loop

• While Loop Logic Building
• Series Based Questions
• Break
• Continue
  
• Nested While Loops
• Pattern-Based Questions
• Pass
• Loop Else

Lists

• List Basics
• List Operations
• List Comprehensions / Slicing
• List Methods

Strings

• String Basics
• String Literals
• String Operations
• String Comprehensions / Slicing
• String Methods

For Loops

• Range Function
• For Loop
• Nested For Loops
• Pattern-Based Questions
• Break
• Continue
• Pass
• Loop Else

Functions

• Definition
• Call
• Function Arguments
• Default Arguments
• Docstrings
• Scope
• Special Functions Lambda, Map, And Filter
  
• Recursion
• Functional Programming And Reference Functions

Dictionary

• Dictionaries Basics
• Operations
• Comprehensions
• Dictionaries Methods

Tuple

• Tuples Basics
• Tuples Comprehensions / Slicing
• Tuple Functions
• Tuple Methods

Set

• Sets Basics
• Sets Operations
• Union
• Intersection
• Difference And Symmetric Difference

50+ Coding Ǫuestions Practice And Assignments 

• Numpy
• Pandas
• Matplotlib
• Seaborn
• Sklearn

Data Visualization Using Matplotlib And Seaborn

• Introduction To Matplotlib
• Basic Plotting
• Properties Of Plotting
• Sub Plots
• Line Plots
• Pie Chart
• Bar Graph
• Scatter Plot
• Histograms
• Box Plots
• Violin Plots
• Dist Plots
• Dis Plots
• Kde Plots

• Uni-Variate Analysis
• Bi-Variate Analysis
• Multi-Variate Analysis

• Managing Data Frames With The Dplyr
• Package
  
• Control Structures
• Functions
• Lexical/Dynamic Scoping
• Loop Functions
• Debugging
• Data Visualization In R
• Storytelling With Data
• Principle Tenets
• Elements Of Data Visualization
• Infographics Vs Data Visualization
• Data Visualization & Graphical Functions In R
• Plotting Graphs
• Customizing Graphical Parameters To Improvise The Plots
• Various Guis
• Spatial Analysis
• Other Visualization Concepts

Introduction

• What Is Data
• Types Of Data
• What Is Database
• Types Of Databases
• What Is A Table

Operations On Table

• Creation Of Table
• Select Statement

Data Modifications

• Insert Data Into Tables
• Insert Statements & Insert Into Select Statements
• Updating Existing Data
• Deleting Data From Table
• Drop
• Truncating Tables
• Alter Statements

Constraints

• Primary Key
  
• Foreign Key
• Unique Key
• Not Null
• Check
• Default

Indexes

• Understanding Indexes And Their Importance
• Creating And Dropping Indexes
• Index (B Tree, Hash)

Views

• Creating Views
• Modifying Views
• Dropping Views
• Updating Data Through View

Data Retrieval

• Retrieving Data From A Single Table
• Where Clause
• Group By Clause
• Having Clause
• Order By Clause
• Limit Clause
• Case Statement
• Case Statement For Validating The Data Based On Condition

Joins

• Inner Join
• Left Join
• Right Join
• Full Join
• Cross Join
• Self-Join

Functions

• Numerical Functions
• Date Functions
• String Functions
• Aggregate Functions

Set Operator

• Union
  
• Intersect
• Minus
• Except
• Union All

Sub Ǫueries

• Single Row
• Multiple Row
• Scalar Row
• Correlated
• Exist
• Not Exist
• From And Select
• Where And From

Stored Procedure

• Create
• Dml
• Tcl (Commit,Roll Back, Savepoints,Acid)
• Cursor
• Execution
• Passing Parameters To Stored Procedures And Functions
• Invoking Stored Procedures And Functions

Advance Sǫl Topics

• Windows Functions
• Common Table Expression
• Recursion
• Pivot And Unpivot Operation
• Dynamic Sǫl

• Introduction Of Power Bi Pbi Desktop Installation Power Bi Desktop & Power Bi Service Overview
• Power Ǫuery Software Overview
• Power Pivot Software Overview
• Power View Software Overview
• Power Bi Service Overview
• Power Bi Desktop User Interface
• Building Blocks Of Power Bi
  
• Power Ǫuery
• Data Processing, Data Types And Filters In Power Ǫuery
• Inbuilt Column Transformation
• In Built Row Transformations
• Combine Ǫueries (Merge Ǫueries & Append Ǫueries)
• Merge Ǫueries / Join Tables
• Append Ǫueries / Union All Tables
• Ǫuery Options
• How Tab Options
• Transform Tab Options
• Add Column Tab Options
• Power Pivot
• Power Bi Data Modeling – Model View (Previously Relationship View)
• Enhancing The Data Model- Dax
• Dax Function – Categories
• Dax Text Functions
• Dax Logical Functions
• Dax Date & Time Functions
• Dax Filter Function
• Dax Math And Statistical Functions
• Dax Time Intelligence Functions
• Ǫuick Measures
• Power View
• Report View
• Visuals Interactions
• Filters In Power View
• Hierarchies And Drill-Down Reports
• Power Bi Visualizations
• Visuals For Filtering
• Visualizing Categorical Data
• Visualizing Trend Data
• Visualizing Kpi Data
• Visualizing Tabular Data
• Visualizing Geographical Data
• Grouping, Binning & Sorting
• Bookmarks, Selection Pane & Buttons
  
• Power Bi Services
• Adding Dataset To Power Bi Service And Creating Multiple New Reports
• Dashboards Development

• Types Of Variables
  1. Nominal/Categorical
  2. Ordinal
  3. Interval/Ratio
  4. Continuous, Time Series
• Central Tendency
  1. Mean
  2. Median
  3. Mode
  4. Interquartile Mean

Measures And Statistical Difference

• Variance
• Correlation
• Standard Error
• Iqr
• Range
• Mean Absolute Difference
• Median Absolute Deviation
• Skewness
• Kurtosis
• Correlation And Auto Correlation And Correlation Matrix
• Correlation Ratio

Hypothesis Testing

• Chiquare
• Z Test
• T Test
• Anova
• P Value
  
• Beta Test
• F Score

Methods Of Imputation

• Mean
• Median
• Mode
• B-Fill
• F-Fill
• Knn Imputation
• Random Forest Imputation
• Regressor Based Imputation

Encoding

• Label Encoding
• Dummy Encoding
• Effect Encoding
• Binary Encoding
• Hash Encoding
• Base N Encoding

Feature Scaling

• Standardization
• Normalization

Handling With Outliers

• Z-Score
• Iǫr
• Percentile

Python Supports N-Dimensional Arrays With Numpy. For Data In 2 Dimensions, Pandas Is The Best Library For Analysis. You Can Use Other Tools But Tools Have Drag- And-Drop Features And Limitations. Pandas Can Be Customized As Per The Need As We Can Code Depending Upon The Real-Life Problem

Supervised Learning Regression

• Linear Regression
• Polynomial Regression
• Classification
• Naïve Bayes
• Logistic Regression
• Knn
• Decision Tree Svm

Unsupervised Learning

• K-Means
• C-Means
• Pca
• K-Means
• C-Means
• Pca

Metrics

• Classification Report
• Confusion Matrix
• Accuracy Score
• Crosstab
  
• Fi-Score
• Precision
• Recall
• Roc Curve
• R Squared And Adjusted R Squared
• Rmse, Mse
• Evaluation Metrix

• Live Kaggle Competition
• Hands On Experience On Datasets
• End To End Unique Projects