Part-1 Business Analysis And Analytics

Lecture -1 Introducing business analyst 
·     Introduction to business analyst domain

·     The need for business analysts

·     The various roles and responsibilities

·     How the business analyst fits in the project team

·     Significance of communication and collaboration

·     Core competencies of business analyst

·     Techniques and approaches in business analysis

·     How business analysts fit in the corporate structure

·     The different departments in the organization that business analysts connect with

·     Practical Exercise

Lecture -2 Understanding business needs 
·     Understanding the needs of the business

·     Gathering the requirements

·     Studying feasibility

·     Prioritizing

·     Assessing the risks

·     Evaluating and choosing the right initiative

·     Assessing change of requirements

·     Getting the requirements approved

·     Practical Exercise

Lecture -3 Project management 
·     Introduction to the various types of projects

·     What are the phases in an IT project

·     Important activities

·     deliverables and key people involved

·     Comparing the software development lifecycle and product lifecycle

·     How the projects depend on other projects

·     What are the tasks and responsibilities of project manager

·     Planning and monitoring a project

·     Critical path analysis

·     Creation of tasks

·     Relationship between tasks

·     Allocating the resources

·     Working under various constraints

·     Practical Exercise

Lecture -4 Techniques used by business analysts 
·     Introduction to the various techniques that business analysts use like SWOT

·     CATWOE

·     Important tools used by business analysts

·     Analysis of strategy

·     Various components of strategy analysis

·     Identification of stakeholders and the needs of business

·     What is business modeling

·     Gathering of requirements

·     Analyzing

·     Designing

·     Implementing

·     Testing

·     deploying in the business environment

·     Practical Exercise

Lecture -5 Software project methodologies 
·     The various software engineering processes

·     Understanding the software project steps

·     The software development lifecycle

·     The difference between waterfall and agile software project methodologies

·     RUP and RAD methodologies

·     Project deliverables

·     Practical Exercise

Lecture -6 UML with Microsoft Visio 
·     UML Architecture

·     Modeling Types

·     Basic Notations

·     Standard Diagrams

·     Class Diagram

·     Object Diagram

·     Use Case Diagram

·     Interaction Diagram

·     Activity Diagram

·     Practical Exercise

  Part-2 Advance Excel

Lectutre-1 Entering Data 
·    Introduction to Excel spreadsheet

·    Learning to enter data

·    Flling of series and custom fill list

·    Editing and deleting fields

·    Practical Exercise

Lecture-2 Referencing in Formulas 
·    Learning about relative and absolute referencing

·    The concept of relative formulae

·    The issues in relative formulae

·    Creating of absolute and mixed references

·    Practical Exercise

Lecture-3 Name Range 
·    Creating names range

·    Using names in new formulae

·    Working with the name box

·    Selecting range

·    Names from a selection

·    Pasting names in formulae

·    Selecting names

·    Working with Name Manager

·    Practical Exercise

Lecture-4 Understanding Logical Functions 
·    The various logical functions in Excel

·    The If function for calculating values and displaying text

·    Nested If functions

·    VLookUp and IFError functions

·    Practical Exercise

Lecture-5 Getting started with Conditional Formatting 
·    Learning about conditional formatting

·    The options for formatting cells

·    Various operations with icon sets

·    Data bars and color scales

·    Creating and modifying sparklines

·    Practical Exercise

Lecture-6 Advanced-level Validation 
·    Multi-level drop down validation

·    Restricting value from list only

·    Learning about error messages and cell drop down

·    Practical Exercise

Lecture-7 Important Formulas in Excel 
·    Introduction to the various formulae in Excel

·    Sum, SumIF & SumIFs

·    Count, CountA, CountIF and CountBlank

·    Networkdays, Networkdays International

·    Today & Now function

·    Trim (Eliminating undesirable spaces)

·    Concatenate (Consolidating columns)

·    Practical Exercise

Lecture-8 Working with Dynamic table 
·    Introduction to dynamic table in Excel

·    Data conversion

·    Table conversion

·    Tables for charts

·    VLOOKUP

·    Practical Exercise

Lecture-9 Data Sorting 
·    Sorting in Excel

·    Various types of sorting

·    Alphabetical

·    Numerical

·    Row

·    Multiple column

·    Working with paste special

·    Hyperlinking

·    Using subtotal

·    Practical Exercise

Lecture-10 Data Filtering 
·    The concept of data filtering

·    Understanding compound filter and its creation

·    Removing of filter

·    Using custom filter and multiple value filters

·    Working with wildcards

·    Practical Exercise

Lecture-11 Chart Creation 
·    Creation of Charts in Excel

·    Performing operations in embedded chart

·    Modifying

·    Resizing

·    Dragging of chart

·    Practical Exercise

Lecture-12 Various Techniques of Charting 
·    Introduction to the various types of charting techniques

·    Creating titles for charts

·    Axes

·    Learning about data labels

·    Displaying data tables

·    Modifying axes

·    Displaying gridlines and inserting trendlines

·    Textbox insertion in a chart

·    Creating a 2-axis chart

·    Creating combination chart

·    Practical Exercise

Lecture-13 Pivot Tables in Excel 
·    The concept of Pivot tables in Excel

·    Report filtering

·    Shell creation

·    Working with Pivot for calculations

·    Formatting of reports

·    Dynamic range assigning

·    The slicers

·    Creating of slicers

·    Practical Exercise

Lecture-14 Ensuring Data and File Security 
·    Data and file security in Excel

·    Protecting row, column, and cell

·    Different safeguarding techniques

·    Practical Exercise

Lecture-15 Getting started with VBA Macros 
·    Learning about VBA macros in Excel

·    Executing macros in Excel

·    The macro shortcuts

·    Applications

·    The concept of relative reference in macros

·    Practical Exercise

Lecture-16 Core concepts of VBA 
·    In-depth understanding of Visual Basic for Applications

·    The VBA Editor

·    Module insertion and deletion

·    Performing action with Sub

·    Ending Sub if condition not met

·    Practical Exercise

Lecture-17 Ranges and Worksheet in VBA 
·    Learning about the concepts of workbooks & worksheets in Excel Protection of macro codes

·    Range coding

·    Declaring a variable

·    The concept of Pivot Table in VBA

·    Introduction to arrays

·    User forms

·    Getting to know how to work with databases within Excel

·    Practical Exercise

Lecture-18 IF condition 
·    Learning how the If condition works

·    How to apply it in various scenarios

·    Working with multiple Ifs in Macro

·    Practical Exercise

Lecture-19 Loops in VBA 
·    Understanding the concept of looping

·    Deploying looping in VBA Macros

·    Practical Exercise

Lecture-20 Debugging in VBA 
·    Studying about debugging in VBA

·    The various steps of debugging

·    Understanding breakpoints and way to mark it

·    The code for debugging and code commenting

·    Practical Exercise

Lecture-21 Messaging in VBA 
·    The concept of message box in VBA

·    Learning to create the message box

·    Various types of message boxes

·    The IF condition as related to message boxes

·    Practical Exercise

Lecture-22 Practical Projects in VBA 
·    Mastering the various tasks and functions using VBA

·    Understanding data separation

·    Auto filtering

·    Formatting of report

·    Combining multiple sheets into one

·    Merging multiple files together

·    Practical Exercise

Lecture-23 Best Practices of Dashboards Visualization 
·    Introduction to powerful data visualization with Excel Dashboard

·    Loading the data

·    Managing data and linking the data to tables and charts

·    Creating Reports using dashboard features

·    Practical Exercise

Lecture-24 Principles of Charting 
·    Learning to create charts in Excel

·    The various charts available

·    The steps to successfully build a chart

·    Personalization of charts

·    Formatting and updating features

·    Various special charts for Excel dashboards

·    Understanding how to choose the right chart for the right data

·    Practical Exercise

Lecture-25 Getting started with Pivot Tables 
·    Creation of Pivot Tables in Excel

·    Learning to change the Pivot Table layout

·    Generating Reports

·    The methodology of grouping and ungrouping of data

·    Practical Exercise

Lecture-26 Creating Dashboards 
·    Learning to create Dashboards

·    The various rules to follow while creating Dashboards

·    Creation of dynamic dashboards

·    Knowing what is data layout

·    Introduction to thermometer chart and its creation

·    How to use alerts in the Dashboard setup

·    Practical Exercise

Lecture-27 Creation of Interactive Components 
·    How to insert a Scroll bar to a data window

·    Concept of Option buttons in a chart

·    Use of combo box drop-down

·    List box control Usage

·    How to use Checkbox Control

·    Practical Exercise

Lecture-28 Data Analysis 
·    Understanding data quality issues in Excel

·    Linking of data

·    Consolidating and merging data

·    Working with dashboards for Excel Pivot Tables

·    Practical Exercise

  Part-3 Business Analytics Using SQL

Lecture-1 SQL Fundamentals 
·    Various types of databases           

·    Introduction to Structured Query Language         

·    Distinction between client server and file server databases        

·    Understanding SQL Server Management Studio

·    SQL Table basics              

·    Data types and functions              

·    Transaction-SQL               

·    Authentication for Windows                    

·    Data control language                   

·    The identification of the keywords in T-SQL, such as Drop Table

·    Practical Exercise

Lecture-2 Database Normalization 
·    Data Anomalies                

·    Update Anomalies            

·    Insertion Anomalies                      

·    Deletion Anomalies                      

·    Types of Dependencies                 

·    Functional Dependency                

·    Fully functional dependency                    

·    Partial functional dependency                  

·    Transitive functional dependency            

·    Multi-valued functional dependency                   

·    Decomposition of tables               

·    Lossy decomposition                    

·    Lossless decomposition                

·    What is Normalization?                

·    First Normal Form            

·    Second Normal Form                    

·    Third Normal Form                       

·    Boyce-Codd Normal Form(BCNF)                      

·    Fourth Normal Form

·    Practical Exercise

Lecture-3 Entity Relationship Model 
·    Entity-Relationship Model                       

·    Entity and Entity Set                    

·    Attributes and types of Attributes            

·    Entity Sets             

·    Relationship Sets              

·    Degree of Relationship                 

·    Mapping Cardinalities, One-to-One, One-to-Many, Many-to-one, Many-to-many                 

·    Symbols used in E-R Notation

·    Practical Exercise

Lecture -4 SQL Operators 
·    Introduction to relational databases                     

·    Fundamental concepts of relational rows, tables, and columns   

·    Several operators (such as logical and relational), constraints, domains, indexes, stored procedures, primary and foreign keys     

·    Understanding group functions                

·    The unique key

·    Practical Exercise

Lecture -5 Working with SQL 
·    Join,                       

·    Tables                    

·    Variables

·    Practical Exercise

Lecture-6 Advanced concepts of SQL tables 
·    SQL functions                   

·    Operators & queries                      

·    Table creation                   

·    Data retrieval from tables             

·    Combining rows from tables using inner, outer, cross, and self joins             

·    Deploying operators such as ‘intersect,’ ‘except,’ ‘union,’         

·    Temporary table creation             

·    Set operator rules              

·    Table variables

·    Practical Exercise

Lecture – 7 Deep Dive into SQL Functions 
·    Understanding SQL functions                  

·    Scalar functions                

·    Aggregate functions                      

·    Functions that can be used on different datasets, such as numbers, characters, strings, and dates

·    Inline SQL functions                     

·    General functions              

·    Duplicate functions

·    Practical Exercise

Lecture - 8 Working with Subqueries 
·    Understanding SQL subqueries, their rules          

·    Statements and operators with which subqueries can be used     

·    Using the set clause to modify subqueries

·    Understanding different types of subqueries, such as where, select, insert, update, delete, etc 

·    Methods to create and view subqueries

·    Practical Exercise

Lecture - 9 SQL Views, Functions, and Stored Procedures 
·    Learning SQL views                     

·    Methods of creating, using, altering, renaming, dropping, and modifying views                     

·    Understanding stored procedures and their key benefits 

·    Working with stored procedures              

·    Studying user-defined functions               

·    Error handling

·    Practical Exercise

Lecture -10 Deep Dive into User-defined Functions 
·    User-defined functions                 

·    Types of UDFs, such as scalar                  

·    Inline table value              

·    Multi-statement table                    

·    Stored procedures and when to deploy them        

·    What is rank function?                 

·    Triggers, and when to execute triggers?

·    Practical Exercise       

Lecture - 11 SQL Optimization and Performance 
·    SQL Server Management Studio              

·    Using pivot in MS Excel and MS SQL Server     

·    Differentiating between Char, Varchar, and NVarchar   

·    XL path, indexes and their creation                     

·    Records grouping, advantages, searching, sorting, modifying data

·    Clustered indexes creation           

·    Use of indexes to cover queries                

·    Common table expressions                       

·    Index guidelines

·    Practical Exercise

Lecture -12 Managing Data with Transact-SQL 
·    Creating Transact-SQL queries                

·    Querying multiple tables using joins                    

·    Implementing functions and aggregating data     

·    Modifying data                 

·    Determining the results of DDL statements on supplied tables and data       

·    Constructing DML statements using the output statement

·    Practical Exercise

Lecture - 13 Querying Data with Advanced Transact-SQL Components 
·    Querying data using subqueries and APPLY       

·    Querying data using table expressions                 

·    Grouping and pivoting data using queries

·    Querying temporal data and non-relational data

·    Constructing recursive table expressions to meet business requirements       

·    Using windowing functions to group                   

·    Rank the results of a query

·    Practical Exercise       

Lecture - 14 Programming Databases Using Transact-SQL 
·    Creating database programmability objects by using T-SQL      

·    Implementing error handling and transactions

·    Implementing transaction control in conjunction with error handling in stored procedures  

·    Implementing data types and NULL

·    Practical Exercise

Lecture - 15 Designing and Implementing Database Objects 
·    Designing and implementing relational database schema           

·    Designing and implementing indexes                  

·    Learning to compare between indexed and included columns    

·    Implementing clustered index                  

·    Designing and deploying views                

·    Column store views

·    Practical Exercise

Lecture - 16 Implementing Programmability Objects 
·    Explaining foreign key constraints                       

·    Using T-SQL statements               

·    Usage of Data Manipulation Language (DML)

·    Designing the components of stored procedures

·    Implementing input and output parameters          

·    Applying error handling               

·    Executing control logic in stored procedures       

·    Designing trigger logic, DDL triggers, etc

·    Practical Exercise

Lecture - 17 Managing Database Concurrency 
·    Applying transactions                   

·    Using the transaction behavior to identify DML statements       

·    Learning about implicit and explicit transactions

·    Isolation levels management                    

·    Understanding concurrency and locking behaviour

·    Using memory-optimized tables   

·    Practical Exercise

Lecture - 18 Optimizing Database Objects 
·    Accuracy of statistics                    

·    Formulating statistics maintenance tasks 

·    Dynamic management objects management        

·    Identifying missing indexes                      

·    Examining and troubleshooting query plans        

·    Consolidating the overlapping indexes                

·    The performance management of database instances

·    SQL server performance monitoring

·    Practical Exercise

Lecture - 19 Advanced SQL 
·    Correlated Subquery, Grouping Sets, Rollup, Cube

·    Implementing Correlated Subqueries                   

·    Using EXISTS with a Correlated subquery          

·    Using Union Query                       

·    Using Grouping Set Query           

·    Using Rollup                     

·    Using CUBE to generate four grouping sets        

·    Perform a partial CUBE

·    Practical Exercise

  Part-4 Business Analytics using Python

Lecture-1 Introduction to Business Analytics 
·    Business Analytics

·    Describe the evolution of analytics

·    Describe the differences between aalnytics and analysis

·    Explain the concept of insights

·    Describe the broad types of business analytics

·    Describe how organisations benefit from using analytics

·    Practical Exercise

Lecture-2 Understanding Data 
·    Importance of data in business analytics

·    Differences between data, information and knowledge

·    The various stages that an organization goes through in terms of data maturity

·    Practical Exercise

Lecture-3 Business Analytics, Business Intelligence and Data Mining 
·    Differences between Business Analytics and Business Intelligence

·    Describe the two major components within Business Analytics and Business Intelligence

·    Data Mining technique helps both Business Intelligence and Business Analytics

·    Analytical Decision-Making Process

·    Analysing Business Problems

·    Practical Exercise

Lecture-4 Social Media Analytics 
·    Capabilities social media analytics

·    Common goals of social media analytics

·    Practical Exercise

Lecture-5 Python for Analytics 
·    Introduction to Python Installation

·    Jupyter Notebook Introduction

·    Practical Exercise

Lecture-6 Python Basics 
·    What is Python?

·    Progress of Python

·    Success of Python

·    Programming Model of Python

·    Python Programming Features

·    Commands for common tasks and control

·    Essential Python programming concepts & language mechanics

·    Python Installation

·    Introduction to Python using Jupyter Notebook

·    Simple Input/Output

·    Basic Data Types

·    Control Structures

·    Arithmetic Operators

·    Logical Operators

·    Practical Exercise

Lecture-7 Python Programming 
·    Strings,

·    Lists

·    Tuples

·    Dictionaries

·    Functions

·    Parameters

·    Arguments

·    Recursion

·    Data Processing using Pandas and Nampy

·    Introduction to Modules & Packages

·    Generators

·    Errors & Exception Handling

·    Practical Exercise

Lecture-8 FILE Input/Output 
·    Path and Directory

·    File Operations

·    Reading and Writing to Files

·    Advance File I/O

·    Practical Exercise

Lecture-9 Pandas 
·    Pandas Introduction

·    Series, Data Frames and csvs

·    Data from urls

·    Describing Data with Pandas

·    Selecting and Viewing Data with Pandas

·    Selecting and Viewing Data with Pandas Part 2

·    Manipulating Data

·    Manipulating Data 2

·    Manipulating Data 3

·    Practical Exercise

Lecture-10 numpy 
·    Mathematical Computing with Python (numpy)

·    Numpy Introduction

·    Numpy datatypes and Attributes

·    Creating numpy Arrays

·    Numpy Random Seed

·    Viewing Arrays and Matrices

·    Manipulating Arrays

·    Standard Deviation and Variance

·    Reshape and Transpose

·    Dot Product vs Element Wise

·    Comparison Operators

·    Sorting Arrays

·    Turn Images Into numpy Arrays

·    Practical Exercise

Lecture-11 Basic Statistical Concepts and Types of Data 
·    Statistics and its use in business

·    Types of data

·    Basic statistical concepts

·    Various techniques for sampling

·    Frequency distributions

·    Various measures of central tendency

·    Different measures of dispersion

·    Different measures of shape

·    Practical Exercise

Lecture-12 One-way Analysis of Variance 
·    Explain the concept of ANOVA

·    Calculate ANOVA using Python

·    Test a hypothesis using ANOVA

·    Practical Exercise

Lecture-13 Correlation 
·    Statistical relationships

·    Understand the measure of correlation

·    Correlation between two datasets using Python

·    Concepts of correlation versus causation

·    Practical Exercise

Lecture-14 Linear Regression 
·    Two data series using linear regression

·    To forecast values using linear regression in Python

·    K-Means Clustering

·    What is clustering?

·    K-Means Clustering using python

·    NbClust

·    Practical Exercise

Lecture-15 Time series 
·    Introduction to time series data

·    Time series forecasting using Moving Average

·    Time series forecasting using Naïve forecasting

·    Practical Exercise

Lecture-16 Linear Programming 
·    Explain the concept of linearity

·    Describe linear programming

·    Formulate a linear programming problem

·    Linear Programming – Allocation Models

·    Describe allocation models in linear programming

·    Solve allocation model problems in linear programming using Python

·    Practical Exercise

Lecture-17 Linear Programming – Covering Models 
·    Describe covering models in linear programming

·    Solve covering model problems in linear programming using Python

·    Practical Exercise

Lecture-18 Text Mining 
·    The concepts of text-mining

·    Use cases

·    Text Mining Algorithms

·    Quantifying text

·    TF-IDF

·    Beyond TF-IDF

·    Data Mining vs. Text Mining

·    Text Mining and Text Characteristics

·    Predictive Text Analytics

·    Text Mining Problems

·    Prediction & Evaluation

·    Python as a Data Science Platform

·    Practical Exercise

Lecture-19 Text mining modeling using NLTK 
·    Text Corpus

·    Sentence Tokenization

·    Word Tokenization

·    Removing special Characters

·    Expanding contractions

·    Removing Stopwords

·    Correcting words: repeated characters

·    Stemming & lemmatization

·    Part of Speech Tagging

·    Feature Extraction

·    Bag of words model

·    TF-IDF model

·    Text classification problem

·    Building a classifier using support vector machine

·    Practical Exercise

  Part- 5 Business Analytics using R

Lecture-1 Introduction to Business Analytics 
·    Introduction to Business Intelligence

·    Introduction to Business Analytics

·    Introduction to Data

·    Introduction to Information

·    How information hierarchy can be improved/introduced

·    Understanding Business Analytics and R

·    Knowledge about the R language

·    Its community and ecosystem

·    Understand the use of 'R' in the industry

·    Compare R with other software in analytics

·    Install R and the packages useful for the course

·    Perform basic operations in R using command line

·    Learn the use of IDE R Studio and Various GUI

·    Use the ‘R help’ feature in R

·    Worldwide R community collaboration

·    Practical Exercise

Lecture-2 Understanding Data 
·    Importance of data in business analytics

·    Differences between data, information and knowledge

·    The various stages that an organization goes through in terms of data maturity

·    Business Analytics, Business Intelligence and Data Mining

·    Differences between Business Analytics and Business Intelligence

·    Describe the two major components within Business Analytics and Business Intelligence

·    Data Mining technique helps both Business Intelligence and Business Analytics

·    Analytical Decision-Making Process

·    Analysing Business Problems

·    Practical Exercise

Lecture-3 Introduction to R programming and R Studio 
·    Installation of rstudio

·    Implementing simple mathematical operations

·    Logic using R operators

·    Loops

·    If statements

·    Switch cases

·    Practical Exercise

Lecture-4 Data Exploration 
·    Introduction to data exploration

·    Importing and exporting data to/from external sources

·    What are data exploratory analysis and data importing?

·    Dataframes

·    Accessing individual elements

·    Vectors

·    Factors

·    Operators

·    In-built functions

·    Conditional Looping statements

·    User-defined functions

·    Data types

·    Practical Exercise

Lecture-5 Data Manipulation 
·    Need for data manipulation

·    Introduction to the dplyr package

·    Selecting one or more columns with select()

·    Filtering records on the basis of a condition with filter()

·    Adding new columns with mutate()

·    Sampling, and counting

·    Combining different functions with the pipe operator

·    Implementing SQL-like operations with sqldf

·    The various steps involved in Data Cleaning

·    Functions used in Data Inspection

·    Tackling the problems faced during Data Cleaning

·    Uses of the functions

·    Coerce the data

·    Uses of the apply() functions

·    Practical Exercise

Lecture-6 Data Import Techniques in R 
·    Import data from spreadsheets and text files into R

·    Import data from other statistical formats

·    Packages installation used for database import

·    Connect to RDBMS from R using ODBC

·    Basic SQL queries in R

·    Basics of Web Scraping

·    Practical Exercise

Lecture-7 Exploratory Data Analysis 
·    Understanding the Exploratory Data Analysis(EDA)

·    Implementation of EDA on various datasets

·    Boxplots

·    Whiskers of Boxplots

·    Understanding the cor() in R

·    EDA functions

·    Multiple packages in R for data analysis

·    The Fancy plots like the Segment plot

·    HC plot in R

·    Practical Exercise

Lecture-8 Data Visualization 
·    Introduction to visualization

·    Different types of graphs

·    The grammar of graphics

·    The ggplot2 package

·    Categorical distribution with geom_bar()

·    Numerical distribution with geom_hist()

·    Building frequency polygons with geom_freqpoly()

·    Making a scatterplot with geom_pont()

·    Multivariate analysis with geom_boxplot

·    Univariate analysis with barplot, histogram & density plot

·    Multivariate distribution

·    Creating barplots for categorical variables using geom_bar()

·    Adding themes with the theme() layer

·    Visualization with plotly

·    Frequency plots with geom_freqpoly()

·    Multivariate distribution with scatter plots and smooth lines

·    Continuous distribution vs categorical distribution with box-plots

·    Sub grouping plots

·    Co-ordinates and themes

·    Understanding plotly

·    Various plots

·    Visualization with ggvis

·    Geographic visualization with ggmap()

·    Building web applications with shinyr

·    Practical Exercise

Lecture-9 Introduction to Statistics 
·    Why do we need statistics?

·    Categories of statistics

·    Statistical terminology

·    Types of data

·    Measures of central tendency

·    Measures of spread

·    Correlation and covariance

·    Standardization and normalization

·    Probability and the types

·    Hypothesis testing

·    Chi-square testing

·    ANOVA

·    Normal distribution

·    Binary distribution

·    Practical Exercise

Lecture-10 Machine Learning 
·    Introduction to Machine Learning

·    Practical Exercise

Lecture-11 Linear Regression 
·    Introduction to linear regression

·    Predictive modeling

·    Simple linear regression vs multiple linear regression

·    Concepts

·    Formulas

·    Assumptions

·    Residuals in Linear Regression

·    Building a simple linear model

·    Predicting results

·    Finding the p-value

·    Practical Exercise

Lecture-12 Logistic Regression 
·    Introduction to logistic regression

·    Logistic regression concepts

·    Linear vs logistic regression

·    Math behind logistic regression

·    Detailed formulas

·    logit function and odds

·    Bivariate logistic regression

·    Poisson regression

·    Building a simple binomial model

·    Predicting the result

·    Making a confusion matrix for evaluating the accuracy

·    True positive rate

·    False positive rate

·    Threshold evaluation with ROCR

·    Finding out the right threshold by building the ROC plot

·    Cross validation

·    Multivariate logistic regression

·    Building logistic models with multiple independent variables

·    Real-life applications of logistic regression

·    An introduction to logistic regression

·    Comparing linear regression with logistics regression

·    Bivariate logistic regression with multivariate logistic regression

·    Understanding the fit of the model

·    Using qqnorm() and qqline()

·    Understanding the summary results with null hypothesis & F-statistic

·    Practical Exercise

Lecture-13 Decision Trees and Random Forest 
·    What is classification?

·    Different classification techniques

·    Introduction to decision trees

·    Algorithm for decision tree induction

·    Building a decision tree in R

·    Confusion matrix & regression trees vs classification trees

·    Introduction to bagging

·    Random forest and implementing it in R

·    Computing probabilities

·    Impurity function

·    Entropy

·    Gini index

·    Information gain for the right split of node

·    Overfitting

·    Pruning

·    Re-pruning

·    Post-pruning

·    Cost-complexity pruning

·    Pruning a decision tree and predicting values

·    Finding out the right number of trees

·    Evaluating performance metrics

·    Practical Exercise

Lecture-14 Unsupervised Learning 
·    What is Clustering?

·    Its use cases

·    What is k-means clustering?

·    What is canopy clustering?

·    What is hierarchical clustering?

·    Introduction to unsupervised learning

·    Feature extraction

·    Clustering algorithms

·    The k-means clustering algorithm

·    Theoretical aspects of k-means

·    K-means process flow

·    K-means in R

·    Implementing k-means

·    Finding out the right number of clusters using a screen plot

·    Dendograms

·    Understanding hierarchical clustering

·    Implementing it in R

·    Explanation of Principal Component Analysis (PCA)

·    Implementing PCA in R

·    Practical Exercise

Lecture-15 Association Rule Mining & Recommendation Engines 
·    Introduction to association rule mining and MBA

·    Measures of association rule mining

·    Introduction to recommendation engines

·    User-based collaborative filtering

·    Item-based collaborative filtering

·    Implementing a recommendation engine in R

·    Recommendation engine use cases

·    Practical Exercise

Lecture-16 Time Series Analysis 
·    What is a time series?

·    The techniques

·    Applications

·    Components of time series

·    Moving average

·    Smoothing techniques

·    Exponential smoothing

·    Univariate time series models

·    Multivariate time series analysis

·    ARIMA model

·    Time series in R

·    Sentiment analysis in R

·    Text analysis

·    Practical Exercise

Lecture-17 Support Vector Machine (SVM) 
·    Introduction to Support Vector Machine (SVM)

·    Data classification using SVM

·    SVM algorithms using separable and inseparable cases

·    Linear SVM for identifying margin hyperplane

·    Practical Exercise

Lecture-18 Naïve Bayes 
·    What is Naive Bayes?

·    What is the Bayes theorem?

·    What is Naïve Bayes Classifier?

·    Classification Workflow

·    How Naive Bayes classifier works

·    Classifier building in Scikit-Learn

·    Building a probabilistic classification model using Naïve Bayes

·    The zero probability problem

·    Practical Exercise

Lecture-19 Text Mining 
·    Introduction to the concepts of text mining

·    Text mining use cases

·    Understanding and manipulating the text with ‘tm’ and ‘stringr’

·    Text mining algorithms and the quantification of the text

·    TF-IDF and after TF-IDF

·    Practical Exercise

  Part-6 Tableau

Lecture-1 Data Visualization and Power of Tableau 
·    What is data visualization?

·    Comparison and benefits against reading raw numbers

·    Real use cases from various business domains

·    Some quick and powerful examples using Tableau without going into the technical details of Tableau

·    Installing Tableau

·    Tableau interface

·    Connecting to DataSource

·    Tableau data types

·    Data preparation

·    Practical Exercise

Lecture-2 Tableau Architecture 
·    Installation of Tableau Desktop

·    Architecture of Tableau

·    Tableau Layout

·    Tableau Toolbars

·    Tableau Data Pane

·    Tableau Analytics Pane

·    How to start with Tableau

·    The ways to share and export the work done in Tableau

·    Practical Exercise

Lecture-3 Tableau Metadata and Data Blending 
·    Connection to Excel

·    Cubes and PDFs

·    Management of metadata and extracts

·    Data preparation

·    Joins and Union

·    Dealing with NULL values

·    Cross-database joining

·    Data extraction

·    Data blending

·    Refresh extraction

·    Incremental extraction

·    How to build extract

·    Practical Exercise

Lecture-4 Creation of Sets and Using Filters 
·    Mark

·    Highlight

·    Sort

·    Group, and use sets

·    Creating and editing sets

·    IN/OUT

·    Sets in hierarchies

·    Constant sets

·    Computed sets

·    Bins

·    Filters

·    Filtering continuous dates

·    Dimensions, and measures

·    Interactive filters

·    Marks card

·    Hierarchies

·    How to create folders in Tableau

·    Sorting in Tableau

·    Types of sorting

·    Filtering in Tableau

·    Types of filters

·    Filtering the order of operations

·    Practical Exercise

Lecture-5 Organizing Data and Visual Analytics 
·    Using Formatting Pane to work with menu, fonts, alignments, settings, and copy-paste

·    Formatting data using labels and tooltips

·    Edit axes and annotations

·    K-means cluster analysis

·    Trend and reference lines

·    Visual analytics in Tableau

·    Forecasting

·    Confidence interval

·    Reference lines

·    Bands

·    Practical Exercise

Lecture-6 Working with Mapping, Calculations, Expressions and Parameters 
·    Working on coordinate points

·    Plotting longitude and latitude

·    Editing unrecognized locations

·    Customizing geocoding, polygon maps

·    WMS: web mapping services

·    Working on the background image, including add image

·    Plotting points on images and generating coordinates from them

·    Map visualization

·    Custom territories

·    Map box

·    WMS map

·    How to create map projects in Tableau

·    Creating dual axes maps and editing locations

·    Calculation syntax and functions in Tableau

·    Various types of calculations, including Table, String, Date, Aggregate, Logic, and Number

·    LOD expressions, including concept and syntax

·    Aggregation and replication with LOD expressions

·    Nested LOD expressions

·    Fixed level

·    Lower level

·    Higher level

·    Quick table calculations

·    The creation of calculated fields

·    Predefined calculations

·    How to validate

·    Creating parameters

·    Parameters in calculations

·    Using parameters with filters

·    Column selection parameters

·    Chart selection parameters

·    How to use parameters in the filter session

·    How to use parameters in calculated fields

·    How to use parameters in the reference line

·    Practical Exercise

Lecture-7 Introduction of Charts, Graphs, Dashboards and Stories 
·    Dual axes graphs

·    Histograms

·    Single and dual axes

·    Box plot

·    Motion Charts

·    Pareto Charts

·    Funnel Charts

·    Pie Charts

·    Bar Charts

·    Line Charts

·    Bubble Charts

·    Bullet Charts

·    Scatter Charts

·    Waterfall charts

·    Tree Maps

·    Heat Maps

·    Market basket analysis (MBA)

·    Using Show me

·    Text table and highlighted table

·    Building and formatting a dashboard using size, objects, views, filters, and legends

·    Best practices for making creative as well as interactive dashboards using the actions

·    Creating stories, including the intro of story points

·    Creating as well as updating the story points

·    Adding catchy visuals in stories

·    Adding annotations with descriptions; dashboards and stories

·    What is dashboard?

·    Highlight actions, URL actions, and filter actions

·    Selecting and clearing values

·    Best practices to create dashboards

·    Dashboard examples; using Tableau workspace and Tableau interface

·    Learning about Tableau joins

·    Types of joins

·    Tableau field types

·    Saving as well as publishing data source

·    Live vs extract connection

·    Various file types

·    Practical Exercise

Lecture-8 Tableau Prep 
·    Introduction to Tableau Prep

·    How Tableau Prep helps quickly combine join, shape, and clean data for analysis

·    Creation of smart examples with Tableau Prep

·    Getting deeper insights into the data with great visual experience

·    Making data preparation simpler and accessible

·    Integrating Tableau Prep with Tableau analytical workflow

·    Understanding the seamless process from data preparation to analysis with Tableau Prep

·    Practical Exercise

  Part-7 Power BI

Lecture-1 Power BI Architecture 
·    Components of Power BI Architecture

·    Data Sources

·    Power BI Desktop

·    Power BI Service

·    Power BI Report Server

·    Power BI Gateway

·    Power BI Mobile

·    Power BI Embedded

·    Working of Power BI Architecture

·    On-Premise

·    On-Cloud

·    Power BI Service

·    Front End cluster

·    Back End cluster

·    Working of Power BI Service

·    Azure block /storage

·    Azure SQL database

·    Practical Exercise

Lecture-2 Power BI Building Blocks 
·    Introduction

·    Visualizations

·    Datasets

·    Reports

·    Dashboards

·    Tiles

·    Practical Exercise

Lecture-3 Power BI Components 
·    What is Power BI

·    Power Query

·    Power Pivot

·    Power View

·    Power Map

·    Power BI Desktop

·    Power BI Website

·    Power Q&A

·    Power BI Mobile Apps

·    Practical Exercise

Lecture-4 Power BI-Installation 
·    List of Operating System which supports Power BI

·    Supported Operating Systems

·    How to Install Power BI in PC (Windows)

·    Practical Exercise

Lecture-5 Power BI Data Modeling 
·    What is Power BI Data Modeling?

·    Using information Modeling and Navigation

·    How to Create Power BI Dashboard?

·    Report Tab

·    Data Tab

·    Relationships Tab

·    Create Workspace in Power BI

·    Create Calculated Columns in Data Modeling

·    Creating Calculated Table in Data Modeling

·    Managing Time-Based Information

·    Practical Exercise

Lecture-6 Power BI-Create Workspace and Dashboard 
·    Create Groups in Power BI

·    Introduction to Reports and dashboards

·    Alter dashboards in Power BI

·    Customer DataSet

·    Order DataSet

·    Sales DataSet

·    Region DataSet

·    Product DataSet

·    Deployment Channels in Power BI Custom Visuals

·    Dashboard Vs. Report

·    Practical Exercise

Lecture-7 Share and view Dashboard 
·    Imparting Power BI Dashboard

·    Power BI recognizes “an association”

·    Ways to Share Power BI Dashboard

·    Share Power BI with Internal Clients and External Clients

·    View of Dashboards on Different Devices like IPhone, iPad, Android Phone, Android Tablet, Windows 10, etc.

·    Practical Exercise

Lecture-8 Introduction to Power BI Desktop and connecting to data 
·    Benefits of Power BI Desktop

·    Installing Power BI Desktop

·    Power BI Work Area

·    Connect to Data in Power BI Desktop

·    Practical Exercise

Lecture-9 Q & A in Power BI Desktop 
·    Introduction

·    Include Missing Connections

·    Rename Tables and Segments

·    Fix Mistaken Data Composes

·    Check year and Identifier Segments as Don’t Summarize

·    Pick a Sort By Column for Important Sections

·    Standardize your Model

·    New Tables for Multi-Segment Elements

·    Practical Exercise

Lecture-10 Power BI Archived Workspace 
·    What is Power BI Archived Workspace?

·    Confinements in your Archived Workspace in Power BI

·    OneDrive for Business

·    Sharing Dashboards

·    Creating Gatherings

·    Access on Power BI Versatile Applications

·    Moving Content in your Power BI Archived Workspace

·    Excel or Power BI Desktop Datasets

·    Other Datasets

·    Reports

·    Dashboards

·    Power BI Archived Workspace in Office 365

·    Practical Exercise

Lecture-11 Data Sources for Power BI 
·    Introduction and Types of Data Sources for Power BI Services

·    Files

·    Content Packs

·    Databases

·    How Data Originates from an Alternate Source?

·    Some More Subtle Elements

·    Data Invigorate

·    Contemplations and Limitations

·    Data Sources in Power Metal Desktop

·    All Class

·    File Class

·    Database Class

·    Power Metal Class

·    Azure Class

·    Online Service Class

·    Other Class

·    Connect a Data Source in Power BI

·    Practical Exercise

Lecture-12 Power BI Admin Roles 
·    Purchasing

·    REST API

·    Security

·    Practical Exercise

Lecture-13 DAX in Power BI 
·    Introduction and Importance of DAX in Power BI

·    DAX Formula & Syntax

·    DAX Calculation Types

·    DAX Functions

·    Date and Time Functions

·    Time Intelligence Functions

·    Information Functions

·    Logical Functions

·    Mathematical and Trigonometric Functions

·    Statistical Functions

·    Text Functions

·    Parent-Child functions

·    Table functions

·    Row context

·    Filter Context

·    Creating a Measure Formula using DAX

·    Practical Exercise

Lecture-14 Power BI and Excel Integration 
·    Microsoft Power BI and Excel

·    Integration of Power BI and Excel

·    Existing Dashboard in Power BI

·    Practical Exercise

Lecture-15 Integration of Microsoft Flow and Power BI 
·    Make a Microsoft Flow that Utilizes Power BI from a Layout

·    Fabricate the Microsoft Flow

·    Construct your Microsoft Flow

·    Practical Exercise

Lecture-16 Table in Power BI 
·    Utilize a Power BI Table

·    Create a Table in Power BI

·    Arrange a Table in Power BI

·    Contingent Arranging in Power BI Table

·    Change the Segment Width of a Table

·    Practical Exercise

Lecture-17 Power BI Conditional Formatting 
·    Background Shading Scale

·    Shade Color by Rules in Table

·    Shade Color Least to Most Extreme in Table

·    Shade Color Text Style in Table

·    Shade Color Information Bars

·    Practical Exercise

Lecture-18 Power BI Gateway 
·    Standard Mode

·    Personal Mode

·    Power BI Gateway Architecture

·    Cloud Services

·    Gateway Services

·    On-premises Data Sources

·    Use Gateway in Power BI

·    Install Power BI Gateway

·    Adding a Data Source for Gateway

·    Gateway Connection Set up to a Dataset

·    Troubleshooting of Power BI Gateway

·    Practical Exercise

Lecture-19 Power BI Filters 
·    Order Dataset

·    Sales Dataset

·    Customer Dataset

·    Region Dataset

·    Product Dataset

·    Visual-level Filters

·    Page-level Filters

·    Report-level Filters

·    Drillthrough Filters

·    Apply a Filter in Power BI Desktop

·    Applying Filter to a Visual

·    Applying Filter to a Page

·    New Filter Pane Experience in Power BI Desktop

·    Add Filter Pane for all New Reports

·    Add Filter Pane for an Existing Report

·    Format the Filter Pane

·    Apply Filters in Power BI Workspace

·    Adding Filter in Edit Report Mode

·    Filters in Reading view mode

·    Practical Exercise

Lecture-20 Power BI Query 
·    Report See

·    Information See

·    Connections See

·    Power BI Query Editor

·    Inquiry Strip

·    Left Sheet (Pane)

·    Inside (information) Sheet

·    Question Settings Sheet

·    The Advanced Editor

·    Sparing your Work

·    Practical Exercise

Lecture-21 Power BI Slicers 
·    Date Slicer

·    Numeric Range Slicer

·    Sync Slicers

·    Formatting the Slicer

·    Practical Exercise

Lecture-22 Power BI API 
·    Admin Operations

·    Available Features Operations

·    Capacities Operations

·    Dashboards Operations

·    Datasets Operations

·    Embed Token Operations

·    Gateways Operations

·    Groups Operations

·    Imports Operations

·    Reports Operations

·    Operation group Description

·    Dashboards GetDashboardsAsAdmin

·    Dashboards GetDashboardsInGroupAsAdmin

·    Dashboards GetTilesAsAdmin

·    Datasets GetDatasetsAsAdmin

·    Datasets GetDatasetsInGroupAsAdmin

·    Datasets GetDatasourcesAsAdmin

·    Gatherings AddUserAsAdmin

·    Gatherings DeleteUserAsAdmin

·    Gatherings RestoreDeletedGroupAsAdmin

·    Gatherings UpdateGroupAsAdmin

·    Imports GetImportsAsAdmin

·    Reports GetReportsAsAdmin

·    Reports GetReportsInGroupAsAdmin

·    Power BI Accessible Features

·    Power BI Capacities API

·    Practical Exercise

Lecture-23 Power BI Rest API 
·    Include Dashboard

·    Include Dashboard In Group

·    Clone Tile

·    Clone Tile In Group

·    Get Dashboard

·    Get Dashboard In Group

·    Get Tile

·    Get Tile In Group

·    Power BI Embed Token API

·    Power BI Gateways API

·    Power BI Group API

·    Limitations

·    Power BI Import API

·    Power BI Push Datasets API

·    Power BI Reports API

·    Practical Exercise

Lecture-24 KPI and Mobile Apps 
·    What are KPIs?

·    KPI Elements in Power BI

·    Uses of KPIs in Power BI

·    Requirements for Creating KPI in Power BI

·    KPI Custom Visualizations

·    Considerations and Troubleshooting

·    Power BI Apps on Mobile Gadgets

·    Power BI Apps for Various Gadget

·    Configure Power BI Apps with Microsoft Intune

·    General Mobile Gadget Administration Setup

·    Practical Exercise

Lecture-25 Custom Visuals and Custom Visualization 
·    Developing Custom Visuals in Power BI

·    Custom visual files

·    Organizational visuals

·    Marketplace visuals

·    Downloading and Importing Custom Visuals from Microsoft AppSource

·    Essentials for Power BI Customization

·    Power BI Customize Visualization Backgrounds

·    Power BI Customize Visualization Legends

·    Visualization Types that can Customize in Power BI

·    Practical Exercise

Lecture-26 Card Visualizations and Matrix Visualization 
·    Create a Power BI Card with Report Editor

·    Create Power BI Card from the Q&A Question Box

·    Considerations and Troubleshooting

·    Power BI Matrix Visualization

·    Seeing How Power BI Ascertains Aggregates

·    Utilizing Drill-Down with Power BI Matrix Visual

·    Power BI Matrix Visuals – Ventured Design

·    Subtotals with Matrix Visuals in Power BI

·    Cross-Featuring with Power BI Matrix Visuals

·    Shading & Textual Style Hues with Matrix Visuals

·    Practical Exercise

Lecture-27 Hyperlinks and Bookmarks 
·    Create Hyperlink in Power BI Desktop

·    Make a Table or Network Hyperlink in Power BI Desktop

·    Make a Table or Grid Hyperlink in Excel Power Pivot

·    What is the Power BI Bookmark?

·    Empower – Power BI Bookmarks

·    Utilize Power BI Bookmark

·    Organize Bookmarks in Power BI

·    Power BI Bookmark as a Slide Appear

·    Perceivability – Utilizing the Selection Sheet

·    Power BI Bookmarks for Shapes & Pictures

·    Utilizing Spotlight

·    Power BI Bookmarks in Power BI Benefit

·    Practical Exercise

Lecture-28 Importing Excel Workbooks into Power BI Desktop 
·    How would We Import an Excel Sheet into Power BI (manually)?

·    Power Inquiry Queries

·    Power Turn Outside Information Connections

·    Connected Tables or Current Exercise Manual Tables

·    Information Show Ascertained Segments and Others

·    Power View Worksheets

·    Constraints to Bringing in Excel Workbook Manual

·    Practical Exercise

Lecture-29 Power BI Data Category 
·    Data Categorization in Power BI Desktop

·    How to Determine Power BI Data Category?

·    Recognize Geographic Information in Report

·    Make Visuals with Your Geographic Information

·    View the Report in Power BI Portable Application

·    Practical Exercise

Lecture-30 Power BI Aggregate 
·    What is Power BI Aggregate?

·    Kinds of Data (Information)

·    Working of Aggregation in Power BI

·    Change How a Numeric Field is Amassed

·    Aggregate your Data in Power BI

·    Make a Total Utilizing a Classification (Content) Field

·    Practical Exercise

Lecture-31 Admin Portal 
·    Power BI Administrator Portal

·    Instructions to get Administrator Entry

·    Usage Measurements

·    Manage Clients (User)

·    Audit Logs

·    Tenant Settings

·    Workspace Settings

·    Fare and Sharing Settings

·    Content Pack Settings

·    Joining Settings in Power BI Portal

·    Utilize Analyze in Excel with On-Premises Datasets

·    Power BI Custom Visuals Settings

·    R Visuals Settings

·    Review and Use Settings

·    Power BI Dashboard Settings

·    Power BI Designer Settings

·    Limit Settings

·    Implant Codes

·    Power BI Association Visuals

·    Practical Exercise

Lecture-32 ArcGIS, Shape and Tree Map 
·    What is ArcGIS, Shape, and Tree Map?

·    Client Assent

·    Empower ArcGIS Outline

·    Make an ArcGIS Delineate

·    Settings and Organizing for ArcGIS Maps

·    When to Utilize Power BI Treemap

·    Featuring and Cross-Sifting

·    Create Shape Map in Power BI

·    How to Utilize Custom Maps?

·    Test Custom Map

·    Getting Map Information

·    Review Conduct and Prerequisites

·    Practical Exercise

Lecture-33 Types of Chart 
·    BI Scatter Charts & Bubble Charts

·    Combo Chart

·    Basic Area Chart

·    Funnel Charts

·    Donut Chart

·    Waterfall Chart

·    Radial Gauge Chart

·    Ribbon Chart

·    Time Series Chart

·    Featuring and Cross-Sifting

·    Practical Exercise

Lecture-34 Power BI Premium Capacity 
·    Memory Administration

·    CPU Asset Administration in Premium Capacity of Power BI

·    Investigating and Testing

·    Practical Exercise

Lecture-35 Relationship View 
·    Autodetect Amid Stack

·    How to Make a Power BI Relationship?

·    Arrange Extra Alternatives

·    Power BI Cardinality

·    Make the New Relationship in Power BI

·    Extra Choices for Relationship in Power BI

·    Information Require an Alternate Cardinality

·    Practical Exercise

  Part-8 Casestudies

  Select Two Specialization 
1. Business Analytics using R

2. Tableau

3. Power BI