Data Analytics with Artificial Intelligence Course in Mumbai

Module 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of the Analytics domain

Module 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

Module 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
• Modeling, Evaluation, Deploying, Monitoring

Module 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation.
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

Module 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

Module 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

Module 1: PYTHON BASICS

• Introduction to Python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, Strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

Module 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

Module 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

Module 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

Module 1: PYTHON PACKAGES

• Defining packages
• How to create a package
• Importing package
• Installing third-party packages

Module 2: DATA FRAME CREATION USING PANDAS

• Creating dataframes from dictionaries, lists, NumPy arrays, CSV/Excel files, etc.
• Data cleaning
• Filtering
• Grouping
• Aggregation
• Missing values handling
• Descriptive statistics
• Merging & joining datasets

Module 3: VISUALIZATION USING MATPLOTLIB & SEABORN

• Line Plots
• Bar Charts
• Histograms
• Scatter plots
• Heatmaps
• Box plots & customization

Module 4: NUMPY INTRODUCTION

• Arrays
• Indexing
• Slicing
• Reshaping
• Broadcasting
• Mathematical operations
• Performance comparison with lists

Module 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• Relational Database Management System
• CRUD operations

Module 2: SQL BASICS

• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MySQL Workbench installation

Module 3: DATA TYPES AND CONSTRAINTS

• Numeric, Character, date, time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment

Module 4: DATABASES AND TABLES (MySQL)

• Create a database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create a new table from existing data types
• Insert into, Update records
• Alter table

Module 5: SQL JOINS

• Create a database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create a new table from existing data types
• Insert into, Update records
• Alter table

Module 6: SQL COMMANDS AND CLAUSES

• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries

Module 7: DOCUMENT DB/NO-SQL DB

• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods

Module 1: OVERVIEW OF STATISTICS

• Introduction to Statistics
• Descriptive And Inferential Statistics
• Basic Terms Of Statistics
• Types Of Data

Module 2: HARNESSING DATA

• Random Sampling
• Sampling With Replacement And Without Replacement
• Cochran's Minimum Sample Size
• Types of Sampling
• Simple Random Sampling
• Stratified Random Sampling
• Cluster Random Sampling
• Systematic Random Sampling
• Multi stage Sampling
• Sampling Error
• Methods Of Collecting Data

Module 3: EXPLORATORY DATA ANALYSIS

• Exploratory Data Analysis Introduction
• Measures Of Central Tendencies: Mean, Median, And Mode
• Measures Of Central Tendencies: Range, Variance And Standard Deviation
• Data Distribution Plot: Histogram
• Normal Distribution & Properties
• Z Value / Standard Value
• Empherical Rule and Outliers
• Central Limit Theorem
• Normality Testing
• Skewness & Kurtosis
• Measures Of Distance: Euclidean, Manhattan, And Minkowski Distance
• Covariance & Correlation

Module 4: HYPOTHESIS TESTING

• Hypothesis Testing Introduction
• P-Value, Critical Region
• Types of Hypothesis Testing
• Hypothesis Testing Errors : Type I And Type II
• Two Sample Independent T-test
• Two Sample Relation T-test
• One Way Anova Test
• Application of Hypothesis testing

Module 1: INTRODUCTION

• MS office Versions (similarities and differences)
• Interface
• Row and columns
• Keyboard shortcuts for easy navigation
• Data Entry (Fill series)
• Find and select
• Clear options
• Formatting options (Font, Alignment, Clipboard)

Module 2: REFERENCING, NAME RANGES, USES, ARITHMETIC FUNCTIONS

• Mathematical calculations with Cell referencing(Absolute, Relative, Mixed)
• Functions with Name Range

Module 3: ARITHMETIC FUNCTIONS

• Arithmetic functions (SUM, SUMIF, SUMIFS, COUNT, COUNTA, COUNTIFS, AVERAGE, AVERAGEIFS, MAX, MAXIFS, MIN, MINIFS)

Module 4: LOGICAL FUNCTIONS

• Logical functions (IF, AND, OR, NESTED IFS, NOT, IFERROR)

Module 5: REFERRING DATA FROM DIFFERENT TABLES

• LOOKUP
• VOOKUP
• NESTED VLOOKUP
• HLOOKUP
• INDEX
• INDEX WITH MATCH FUNCTION
• INDIRECT
• OFFSET

Module 6: DATE AND TEXT FUNCTIONS

• Date Functions (DATE, DAY, MONTH, YEAR, YEARFRAC, DATEDIFF, EOMONTH)
• Text Functions (TEXT, UPPER, LOWER, PROPER, LEFT, RIGHT, SEARCH, FIND, MID, TTC, Flash Fill)

Module 7: DATA HANDLING

• Number Formatting
• Converting Range into a table
• Formatting table
• Remove duplicates
• SORT
• Advanced Sort
• FILTER
• Advanced Filter

Module 8: DATA VISUALIZATION

• Conditional Formatting (icon sets, highlighted colour sets, data bars, custom formatting)
• Charts (Bar, Column, Lines, Scatter, Pie)

Module 9: DATA SUMMARIZATION

• Pivot Reports (Insert, Interface, Crosstable Reports, Filter, Pivot Charts)
• Slicers (Add, connect to multiple reports and charts)
• Calculated field, Calculated item

Module 10: CONNECTING TO DATA: POWER QUERY, PIVOT, POWER PIVOT WITHIN EXCEL

• Power Query: Interface, Tabs
• Connecting to dаta from other Excel files, text files, other sources
• Dаta Cleaning
• Transforming
• Loading Dаta into Excel Query

Module 11: CONNECTING TO DATA: POWER QUERY, PIVOT, POWER PIVOT WITHIN EXCEL

• Using Loaded queries
• Merge and Append
• Insert Power Pivot
• Similarities and Differences in Pivot and Power Pivot reporting
• Getting dаta from databases, workbooks, webpages

Module 12: DATA SUMMARIZATION: DASHBOARD CREATION, TIPS AND TRICKS

• Dashboard: Types, Getting reports and charts together, Use of Slicers.
• Design and placement: Formatting of Tables, Charts, Sheets, Proper use of Colors and Shapes

Module 1: INTRODUCTION TO POWER BI

• What is Power BI? Overview & Importance
• Power BI vs. Excel vs. Other BI Tools
• Power BI Desktop vs. Power BI Service vs. Power BI Mobile
• Installing and Setting Up Power BI
• Understanding the Power BI Interface
• Data Sources Supported in Power BI

Module 2: CONNECTING TO DATA & DATA TRANSFORMATION (POWER QUERY)

• Importing Data from Excel, SQL, Web, APIs, JSON, etc.
• Data Cleaning & Transformation using Power Query
• Handling Missing Data, Duplicates, and Errors
• Splitting & Merging Columns
• Data Type Conversion and Formatting
• Append & Merge Queries
• Unpivoting and Pivoting Data

Module 3: DATA MODELING IN POWER BI

• Introduction to Data Modeling
• Star Schema vs. Snowflake Schema
• Understanding Relationships (One-to-One, One-to-Many, Many-to-Many)
• Creating & Managing Relationships Between Tables
• Data Normalization & Denormalization
• Role of Primary and Foreign Keys

Module 4: DAX (DATA ANALYSIS EXPRESSIONS) - BASICS & ADVANCED

• Introduction to DAX and Why It’s Important
• Basic DAX Functions
• SUM, AVERAGE, COUNT, DISTINCTCOUNT
• Logical DAX Functions
• IF, SWITCH, AND, OR
• Aggregation & Statistical DAX Functions
• SUMX, COUNTX, AVERAGEX, MAXX, MINX
• Time Intelligence DAX Functions
• TOTALYTD, TOTALQTD, TOTALMTD, DATESYTD, PREVIOUSMONTH, SAMEPERIODLASTYEAR
• Working with Calculated Columns & Measures

Module 5: DATA VISUALIZATION IN POWER BI

• Introduction to Power BI Visuals
• Creating Bar, Line, Pie, Donut, and Area Charts
• Scatter Plots and Bubble Charts
• Maps: Basic Map, Filled Map, ArcGIS Map
• KPI Visuals & Cards
• Waterfall & Funnel Charts
• Tree Maps & Matrix Tables
• Customizing Visuals (Colors, Labels, Interactions)

Module 6: ADVANCED VISUALIZATIONS & CUSTOM REPORTS

• Hierarchies & Drill-Through Reports
• Bookmarks & Buttons for Navigation
• Slicers & Filters (Page Level, Report Level, Visual Level)
• Creating Custom Tooltips
• Using Conditional Formatting in Visuals
• Advanced Table & Matrix Visuals
• Custom Visuals from Power BI Marketplace

Module 7: ADVANCED FILTERING & SLICING DATA

• Using Basic & Advanced Filters
• Dynamic Slicers (Sync Slicers Across Pages)
• Cross-Filtering & Highlighting
• Creating Parameterized Reports
• Using Relative Date Filters

Module 8: POWER BI SERVICE & ONLINE PUBLISHING

• Publishing Reports to Power BI Service
• Power BI Workspaces and Sharing Reports
• Scheduling Data Refresh in Power BI Service
• Managing Permissions & Access Control
• Creating Dashboards in Power BI Service
• Power BI Mobile App

Module 9: POWER BI WITH POWER AUTOMATE & POWER APPS

• Introduction to Power Automate
• Automating Data Refresh in Power BI
• Creating Workflows with Power Automate
• Integrating Power BI with Power Apps

Module 1: INTRODUCTION TO TABLEAU

• What is Tableau? Overview & Importance
• Tableau vs. Power BI vs. Excel
• Installing and Setting Up Tableau
• Tableau Products (Tableau Desktop, Tableau Public, Tableau Server, Tableau Online)
• Understanding the Tableau Interface
• Connecting to Different Data Sources

Module 2: CONNECTING TO DATA & DATA PREPARATION

• Importing Data from Excel, SQL, Web, APIs, JSON, etc.
• Data Cleaning in Tableau
• Handling Missing Data, Duplicates, and Errors
• Splitting & Merging Columns
• Pivoting and Unpivoting Data
• Joining & Blending Data
• Creating Data Extracts vs. Live Connections

Module 3: DATA MODELING & RELATIONSHIPS IN TABLEAU

• Understanding Measures & Dimensions
• Working with Relationships, Joins, and Unions
• Data Normalization & Denormalization
• Primary and Foreign Keys in Tableau
• Understanding Data Granularity

Module 4: BASIC & ADVANCED CALCULATIONS IN TABLEAU

• Creating Calculated Fields
• Working with Table Calculations
• String, Date, and Arithmetic Calculations
• Logical Calculations (IF, CASE, AND, OR, NOT)
• Aggregation Calculations (SUM, COUNT, AVG, MIN, MAX)
• Running Total, Moving Average, and Percentile Calculations

Module 5: DATA VISUALIZATION & CHARTS IN TABLEAU

• Basic Charts (Bar, Line, Pie, Scatter, Bubble)
• Dual-Axis Charts & Combined Axis Charts
• Histograms & Box Plots
• Heatmaps & Highlight Tables
• Tree Maps & Packed Bubbles
• Bullet Charts & Lollipop Charts
• Waterfall & Funnel Charts
• Customizing Colors, Labels, and Formatting

Module 6: ADVANCED VISUALIZATION TECHNIQUES

• Creating Hierarchies & Drill-Downs
• Using Filters & Context Filters
• Creating Dynamic Filters
• Parameter Controls for Interactive Dashboards
• Using Sets & Groups for Data Analysis
• Reference Lines, Bands & Distributions

Module 7: MAPS & GEOSPATIAL ANALYTICS IN TABLEAU

• Creating Geographic Maps
• Customizing Map Views
• Using Latitude & Longitude in Maps
• Heat Maps & Density Maps
• Connecting Tableau with Google Maps
• Custom Shapes & Background Images in Maps

Module 8: TABLEAU DASHBOARDS & STORYTELLING

• Building Interactive Dashboards
• Designing Dashboard Layouts
• Dashboard Actions (Filter, Highlight, URL)
• Best Practices for Dashboard Design
• Storytelling with Tableau (Creating Story Points)
• Mobile-Friendly Dashboards

Module 9: ADVANCED DATA ANALYSIS & FORECASTING

• Trend Lines & Forecasting in Tableau
• Clustering & Data Segmentation
• Statistical Analysis (Mean, Median, Standard Deviation)
• Box Plots for Distribution Analysis
• Scenario Analysis & What-If Analysis
• Market Basket Analysis using Tableau

Module 10: TABLEAU SERVER & ONLINE COLLABORATION

• Publishing Workbooks to Tableau Server
• Managing User Roles & Permissions
• Creating and Managing Data Extracts
• Scheduling Data Refresh
• Using Tableau Public & Tableau Online
• Embedding Tableau Visualizations in Websites

Module 1: GIT INTRODUCTION

• Purpose of Version Control
• Popular Version Control Tools
• Git Distribution Version Control
• Terminologies
• Git Workflow
• Git Architecture

Module 2: GIT REPOSITORY and GitHub

• Git Repo Introduction
• Create a New Repo with the Init command
• Git Essentials: Copy & User Setup
• Mastering Git and GitHub

Module 3: COMMITS, PULL, FETCH, AND PUSH

• Git Repo Introduction
• Create a New Repo with the Init command
• Git Essentials: Copy & User Setup
• Mastering Git and GitHub

Module 4: TAGGING, BRANCHING, AND MERGING

• Organize code with branches
• Check out the branch
• Merge branches

Module 5: UNDOING CHANGES

• Editing Commits
• Commit command, Amend flag
• Git reset and revert

Module 6: GIT WITH GITHUB AND BITBUCKET

• Creating a GitHub Account
• Local and Remote Repo
• Collaborating with other developers
• Bitbucket Git account