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AI Powered Data Analytics  Curriculum

Course Module

    Introduction

    • What is Data Analytic
    • Common Terms in Data Analytics
    • What is data
    • Classication of data
    • Relevance in industry and need of the hour
    • Types of problems and business objectives in various industries
    • How leading companies are harnessing the power of analytics
    • Critical success drivers.
    • Overview of Data Analytics tools & their popularity.
    • Data Analytics Methodology & problem-solving framework.

    Introduction To Python

    • Installation and Working with Python
    • Understanding Python variables
    • Python basic Operators
    • Understanding the Python blocks.

    Python Keyword and Identiers

    • Python Comments, Multiline Comments.
    • Python Indentation
    • Understating the concepts of Operators
      • Arithmetic
      • Relational
      • Logical
      • Assignment
      • Membership
      • Identity

    Introduction To Variables

    • Variables, expression condition and function
    • Global and Local Variables in Python
    • Packing and Unpacking Arguments
    • Type Casting in Python
    • Byte objects vs. string in Python
    • Variable Scope

    Python Data Type

    • Declaring and using Numeric data types
    • Using string data type and string operations
    • Understanding Non-numeric data types
    • Understanding the concept of Casting and Boolean.
    • Strings
    • List
    • Tuples
    • Dictionary
    • Sets

    Control Structure & Flow

    • Statements ? if, else, elif
    • How to use nested IF and Else in Python
    • Loops
    • Loops and Control Statements.
    • Jumping Statements ? Break, Continue, pass
    • Looping techniques in Python
    • How to use Range function in Loop
    • Programs for printing Patterns in Python
    • How to use if and else with Loop
    • Use of Switch Function in Loop
    • Elegant way of Python Iteration
    • Generator in Python
    • How to use nested Loop in Python
    • Use If and Else in for and While Loop
    • Examples of Looping with Break and Continue Statement
    • How to use IN or NOT IN keyword in Python Loop.

    Python Function, Modules and Packages

    • Python Syntax
    • Function Call
    • Return Statement
    • Arguments in a function ? Required, Default, Positional, Variable-length
    • Write an Empty Function in Python ?pass statement.
    • Lamda/ Anonymous Function
    • *args and **kwargs
    • Help function in Python
    • Scope and Life Time of Variable in Python Function
    • Nested Loop in Python Function
    • Recursive Function and Its Advantage and Disadvantage
    • Organizing python codes using functions
    • Organizing python projects into modules
    • Importing own module as well as external modules
    • Understanding Packages
    • Random functions in python
    • Programming using functions, modules & external packages
    • Map, Filter and Reduce function with Lambda Function
    • More example of Python Function

    List

    • What is List.
    • List Creation
    • List Length
    • List Append
    • List Insert
    • List Remove
    • List Append & Extend using ?+? and Keyword
    • List Delete
    • List related Keyword in Python
    • List Revers
    • List Sorting
    • List having Multiple Reference
    • String Split to create a List
    • List Indexing
    • List Slicing
    • List count and Looping
    • List Comprehension and Nested Comprehension

    Tuple

    • What is Tuple
    • Tuple Creation
    • Accessing Elements in Tuple
    • Changing a Tuple
    • Tuple Deletion
    • Tuple Count
    • Tuple Index
    • Tuple Membership
    • TupleBuilt in Function (Length, Sort)

    Dictionary

    • Dict Creation
    • Dict Access (Accessing Dict Values)
    • Dict Get Method
    • Dict Add or Modify Elements
    • Dict Copy
    • Dict From Keys.
    • Dict Items
    • Dict Keys (Updating, Removing and Iterating)
    • Dict Values
    • Dict Comprehension
    • Default Dictionaries
    • Ordered Dictionaries
    • Looping Dictionaries
    • Dict useful methods (Pop, Pop Item, Str , Update etc.)

    Sets

    • What is Set
    • Set Creation
    • Add element to a Set
    • Remove elements from a Set
    • PythonSet Operations
    • Frozen Sets

    Strings

    • What is Set
    • Set Creation
    • Add element to a Set
    • Remove elements from a Set
    • PythonSet Operations

    Python Exception Handling

    • Python Errors and Built-in-Exceptions
    • Exception handing Try, Except and Finally
    • Catching Exceptions in Python
    • Catching Specic Exception in Python
    • Raising Exception
    • Try and Finally

    Python File Handling

    • Opening a File
    • Python File Modes
    • Closing File
    • Writing to a File
    • Reading from a File
    • Renaming and Deleting Files in Python
    • Python Directory and File Management
    • List Directories and Files
    • Making New Directory
    • Changing Directory

    Python Database Interaction

    • SQL Database connection using
    • Creating and searching tables
    • Reading and Storing cong information on database
    • Programming using database connections

    Reading an excel

    • Working With Excel
    • Reading an excel le using Python
    • Writing to an excel sheet using Python
    • Python| Reading an excel le
    • Python | Writing an excel le
    • Adjusting Rows and Column using Python
    • ArithmeticOperation in Excel le.
    • Play with Workbook, Sheets and Cells in Excel using Python
    • Creating and Removing Sheets
    • Formatting the Excel File Data
    • More example of Python Function

    Complete Understanding of OS Module of Python

    • Check Dirs. (exist or not)
    • How to split path and extension
    • How to get user prole detail
    • Get the path of Desktop, Documents, Downloads etc.
    • Handle the File System Organization using OS
    • How to get any les and folder?s details using OS

    AI and LLM Integration in Python:

    • PandasAI: Natural language queries on DataFrames
    • OpenAI API (GPT) to generate code, EDA, and reports
    • LangChain for building chat-based data apps
    • Autogen/Code Interpreter tools for automating insights

    Introduction to Statistics

    • Categorical Data
    • Numerical Data
    • Mean
    • Median
    • Mode
    • Outliers
    • Range
    • Interquartile range
    • Correlation
    • Standard Deviation
    • Variance
    • Box plot

    Understanding Statistics

    • Descriptive Statistics
    • Sample vs Population Statistics
    • Random variables
    • Probability distribution functions
    • Expected value
    • Normal distribution
    • Gaussian distribution
    • Z-score
    • Spread and Dispersion
    • Correlation and Co-variance

    Data Pre-Processing & Data Mining

    • Data Preparation
    • Feature Engineering
    • Feature Scaling
    • Datasets
    • Dimensionality Reduction
    • Anomaly Detection
    • Parameter Estimation
    • Data and Knowledge
    • Selected Applications in Data Mining

    EDA (Exploratory Data Analysis)

    • Need for structured exploratory data
    • EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
    • Identify missing data
    • Identify outliers? data
    • Imbalanced Data Techniques

    Data Analysis and Visualization using Pandas.

    • Statistics
      • Categorical Data
      • Numerical Data
      • Mean
      • Median
      • Mode
      • Outliers
      • Range
      • Interquartile range
      • Correlation
      • Standard Deviation
      • Variance
      • Box plot
    • Pandas
      • Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
      • How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
      • Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue?s
      • Exploring the Data Plotting, Correlations, and Histograms
      • Getting statistical information about the data Analysis Concepts, Handle the None Values
      • Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
      • Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
      • Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function
      • Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
      • Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data
      • Exporting the results to Excel Joins
      • Python | Pandas Data Frame Inner Join
      • Under sting the properties of Data Frame Left Join (Left Outer Join)
      • Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
      • Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
      • Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data
      • Pandas | How to Group Data How to apply Lambda / Function on Data Frame
      • Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

    Data Analysis and Visualization using NumPy and MatPlotLib

    • NumPy
      • Introduction to NumPy Numerical Python
      • Importing NumPy and Its Properties
      • NumPy Arrays
      • Creating an Array from a CSV
      • Operations an Array from a CSV
      • Operations with NumPy Arrays
      • Two-Dimensional Array
      • Selecting Elements from 1-D Array
      • Selecting Elements from 2-D Array
      • Logical Operation with Arrays
      • Indexing NumPy elements using conditionals
      • NumPy?s Mean and Axis
      • NumPy?s Mode, Median and Sum Function
      • NumPy?s Sort Function and More
    • MatPlotLib
      • Bar Chart using Python MatPlotLib
      • Column Chart using Python MatPlotLib
      • Pie Chart using Python MatPlotLib
      • Area Chart using Python MatPlotLib
      • Scatter Plot Chart using Python MatPlotLib
      • Play with Charts Properties Using MatPlotLib
      • Export the Chart as Image
      • Understanding plt. subplots () notation
      • Legend Alignment of Chart using MatPlotLib
      • Create Charts as Image
      • Other Useful Properties of Charts.
      • Complete Understanding of Histograms
      • Plotting Different Charts, Labels, and Labels Alignment etc.

    Introduction to Data Visualization with Seaborn

    • Introduction to Seaborn
      • Introduction to Seaborn
      • Making a scatter plot with lists
      • Making a count plot with a list
      • Using Pandas with seaborn
      • Tidy vs Untidy data
      • Making a count plot with a Dataframe
      • Adding a third variable with hue
      • Hue and scattera plots
      • Hue and count plots
    • Visualizing Two Quantitative Variables
      • Introduction to relational plots and subplots
      • Creating subplots with col and row
      • Customizing scatters plots
      • Changing the size of scatter plot points
      • Changing the style of scatter plot points
      • Introduction to line plots
      • Interpreting line plots
      • Visualizing standard deviation with line plots
      • Plotting subgroups in line plots
    • Visualizing a Categorical and a Quantitative Variable
      • Current plots and bar plots
      • Count plots
      • Bar plot with percentages
      • Customizing bar plots
      • Box plots
      • Create and interpret a box plot
      • Omitting outliers
      • Adjusting the whisk
      • Point plots
      • Customizing points plots
      • Point plot with subgroups
    • Customizing Seaborn Plots
      • Changing plot style and colour
      • Changing style and palette
      • Changing the scale
      • Using a custom palette
      • Adding titles and labels Part 1
      • Face Grids vs. Axes Subplots
      • Adding a title to a face Grid object
      • Adding title and labels Part 2
      • Adding a title and axis labels
      • Rotating x-tics labels
      • Putting it all together
      • Box plot with subgroups
      • Bar plot with subgroups and subplots
      • Well done! What?s next

    SQL Server Fundamentals

    • SQL Server 2019 Installation
    • Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
    • SQL Server Features & Purpose
    • Using Management Studio (SSMS)
    • Conguration Tools & SQLCMD
    • Conventions & Collation

    SQL Server 2019 Database Design

    • SQL Database Architecture
    • Database Creation using GUI
    • Database Creation using T-SQL scripts
    • DB Design using Files and File Groups
    • File locations and Size parameters
    • Database Structure modications

    SQL Tables in MS SQL Server

    • SQL Server Database Tables
    • Table creation using T-SQL Scripts
    • Naming Conventions for Columns
    • Single Row and Multi-Row Inserts
    • Table Aliases
    • Column Aliases & Usage
    • Table creation using Schemas
    • Basic INSERT
    • UPDATE
    • DELETE
    • SELECT queries and Schemas
    • Use of WHERE, IN and BETWEEN
    • Variants of SELECT statement
    • ORDER BY
    • GROUPING
    • HAVING
    • ROWCOUNT and CUBE Functions

    Data Validation and Constraints

    • Table creation using Constraints
    • NULL and IDENTITY properties
    • UNIQUE KEY Constraint and NOT NULL
    • PRIMARY KEY Constraint & Usage
    • CHECK and DEFAULT Constraints
    • Naming Composite Primary Keys
    • Disabling Constraints & Other Options

    Views and Row Data Security

    • Benets of Views in SQL Database
    • Views on Tables and Views
    • SCHEMA BINDING and ENCRYPTION
    • Issues with Views and ALTER TABLE
    • Common System Views and Metadata
    • Common Dynamic Management views
    • Working with JOINS inside views

    Indexes and Query tuning

    • Need for Indexes & Usage
    • Indexing Table & View Columns
    • Index SCAN and SEEK
    • INCLUDED Indexes & Usage
    • Materializing Views (storage level)
    • Composite Indexed Columns & Keys
    • Indexes and Table Constraints
    • Primary Keys & Non-Clustered Indexes

    Stored Procedures and Benets

    • Why to use Stored Procedures
    • Types of Stored Procedures
    • Use of Variables and parameters
    • SCHEMABINDING and ENCRYPTION
    • INPUT and OUTPUT parameters
    • System level Stored Procedures
    • Dynamic SQL and parameterization

    System functions and Usage

    • Scalar Valued Functions
    • Types of Table Valued Functions
    • SCHEMABINDING and ENCRYPTION
    • System Functions and usage
    • Date Functions
    • Time Functions
    • String and Operational Functions
    • ROW_COUNT
    • GROUPING Functions

    Triggers, cursors, memory limitations

    • Why to use Triggers
    • DML Triggers and Performance impact
    • INSERTED and DELETED memory tables
    • Data Audit operations & Sampling
    • Database Triggers and Server Triggers
    • Bulk Operations with Triggers

    Cursors and Memory Limitations

    • Cursor declaration and Life cycle
    • STATIC
    • DYNAMIC
    • SCROLL Cursors
    • FORWARD_ONLY and LOCAL Cursors
    • KEYSET Cursors with Complex SPs

    Transactions Management

    • ACID Properties and Scope
    • EXPLICIT Transaction types
    • IMPLICIT Transactions and options
    • AUTOCOMMIT Transaction and usage

    AI Integration in SQL:

    • AI Tools:
      • ChatGPT/Vanna.ai/DataGPT for Natural Language to SQL
      • Explain SQL queries using AI
      • Suggest query improvements with AI
    • Copilot in Azure Data Studio or GitHub for SQL suggestions

    Understanding Concepts of Excel

    • Creation of Excel Sheet Data
    • Range Name, Format Painter
    • Conditional Formatting, Wrap Text, Merge & Centre
    • Sort, Filter, Advance Filter
    • Different type of Chart Creations
    • Auditing, (Trace Precedents, Trace Dependents)Print Area
    • Data Validations, Consolidate, Subtotal
    • What if Analysis (Data Table, Goal Seek, Scenario)
    • Solver, Freeze Panes
    • Various Simple Functions in Excel(Sum, Average, Max, Min)
    • Real Life Assignment work

    Ms Excel Advance

    • Advance Data Sorting
    • Multi-level sorting
    • Restoring data to original order after performing sorting
    • Sort by icons
    • Sort by colours
    • Lookup Functions
      • Lookup
      • VLookup
      • HLookup
    • Subtotal, Multi-Level Subtotal
    • Grouping Features
      • Column Wise
      • Row Wise
    • Consolidation With Several Worksheets
    • Filter
      • Auto Filter
      • Advance Filter
    • Printing of Raw & Column Heading on Each Page
    • Workbook Protection and Worksheet Protection
    • Specified Range Protection in Worksheet
    • Excel Data Analysis
      • Goal Seek
      • Scenario Manager
    • Data Table
      • Advance use of Data Tables in Excel
      • Reporting and Information Representation
    • Pivot Table
      • Pivot Chat
      • Slicer with Pivot Table & Chart
    • Generating MIS Report In Excel
      • Advance Functions of Excel
      • Math & Trig Functions
    • Text Functions
    • Lookup & Reference Function
    • Logical Functions & Date and Time Functions
    • Database Functions
    • Statistical Functions
    • Financial Functions
    • Functions for Calculation Depreciation

    AI Integration in Excel:

    • Excel Copilot (Microsoft 365):
      • AI-assisted formula creation
      • Data summary using natural language prompts
      • Generate charts and pivot tables via prompts
    • Ideas in Excel: Automated pattern recognition
    • Integration with Power Automate for Workflow Automation

    Introduction to Power BI

    • Overview of BI concepts
    • Why we need BI
    • Introduction to SSBI
    • SSBI Tools
    • Why Power BI
    • What is Power BI
    • Building Blocks of Power BI
    • Getting started with Power BI Desktop
    • Get Power BI Tools
    • Introduction to Tools and Terminology
    • Dashboard in Minutes
    • Interacting with your Dashboards
    • Sharing Dashboards and Reports

    Power BI Desktop

    • Power BI Desktop
    • Extracting data from various sources
    • Workspaces in Power BI

    Power BI Data Transformation

    • Data Transformation
    • Query Editor
    • Connecting Power BI Desktop to our Data Sources
    • Editing Rows
    • Understanding Append Queries
    • Editing Columns
    • Replacing Values
    • Formatting Data
    • Pivoting and Unpivoting Columns
    • Splitting Columns
    • Creating a New Group for our Queries
    • Introducing the Star Schema
    • Duplicating and Referencing Queries
    • Creating the Dimension Tables
    • Entering Data Manually
    • Merging Queries
    • Finishing the Dimension Table
    • Introducing the another DimensionTable
    • Creating an Index Column
    • Duplicating Columns and Extracting Information
    • Creating Conditional Columns
    • Creating the FACT Table
    • Performing Basic Mathematical Operations
    • Improving Performance and Loading Data into the Data Model

    Modelling with Power BI

    • Introduction to Modelling
    • Modelling Data
    • Manage Data Relationship
    • Optimize Data Models
    • Cardinality and Cross Filtering
    • Default Summarization & Sort by
    • Creating Calculated Columns
    • Creating Measures & Quick Measures

    Data Analysis Expressions (DAX)

    • What is DAX
    • Data Types in DAX
    • Calculation Types
    • Syntax, Functions, Context Options
    • DAX Functions
      • Date and Time
      • Time Intelligence
      • Information
      • Logical
      • Mathematical
      • Statistical
      • Text and Aggregate
    • Measures in DAX
    • Measures and Calculated Columns
    • ROW Context and Filter Context in DAX
    • Operators in DAX - Real-time Usage
    • Quick Measures in DAX - Auto validations
    • In-Memory Processing DAX Performance

    Power BI Desktop Visualisations

    • How to use Visual in Power BI
    • What Are Custom Visuals
    • Creating Visualisations and Colour Formatting
    • Setting Sort Order
    • Scatter & Bubble Charts & Play Axis
    • Tooltips and Slicers, Timeline Slicers & Sync Slicers
    • Cross Filtering and Highlighting
    • Visual, Page and Report Level Filters
    • Drill Down/Up
    • Hierarchies and Reference/Constant Lines
    • Tables, Matrices & Conditional Formatting
    • KPI's, Cards & Gauges
    • Map Visualizations
    • Custom Visuals
    • Managing and Arranging
    • Drill through and Custom Report Themes
    • Grouping and Binning and Selection Pane, Bookmarks & Buttons
    • Data Binding and Power BI Report Server

    Introduction to Power BI Dashboard and Data Insights

    • Why Dashboard and Dashboard vs Reports
    • Creating Dashboards
    • Conguring a Dashboard Dashboard Tiles, Pinning Tiles
    • Power BI Q&A
    • Quick Insights in Power BI

    Direct Connectivity

    • Custom Data Gateways
    • Exploring live connections to data with Power BI
    • Connecting directly to SQL Server
    • Connectivity with CSV & Text Files
    • Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
    • Content packs
    • Update content packs

    Publishing and Sharing

    • Introduction and Sharing Options Overview
    • Publish from Power BI Desktop and Publish to Web
    • Share Dashboard with Power BI Service
    • Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
    • Print or Save as PDF and Row Level Security (Power BI Pro)
    • Export Data from a Visualization
    • Export to PowerPoint and Sharing Options Summary

    Refreshing Datasets

    • Understanding Data Refresh
    • Personal Gateway (Power BI Pro and 64-bit Windows)
    • Replacing a Dataset and Troubleshooting Refreshing

    AI Integration in Power BI:

    • Smart Narrative visual (AI-generated insights)
    • Decomposition Tree (Root Cause Analysis)
    • Q&A Visual (Natural Language Querying)
    • Azure Cognitive Services integration
    • Power BI Copilot (Preview): Report creation via prompts
    • Integration with Power Automate for alerts and workflows

    Introduction to Data Preparation using Tableau Prep

    • Data Visualization
    • Business Intelligence tools
    • Introduction to Tableau
    • Tableau Architecture
    • Tableau Server Architecture
    • VizQL Fundamentals
    • Introduction to Tableau Prep
    • Tableau Prep Builder User Interface
    • Data Preparation techniques using Tableau Prep Builder tool

    Data Connection with Tableau Desktop

    • Features of Tableau Desktop
    • Connect to data from File and Database
    • Types of Connections
    • Joins and Unions
    • Data Blending
    • Tableau Desktop User Interface

    Basic Visual Analytics

    • Visual Analytics
    • Basic Charts Bar Chart, Line Chart, and Pie Chart
    • Hierarchies
    • Data Granularity
    • Highlighting
    • Sorting
    • Filtering
    • Grouping
    • Sets

    Calculations in Tableau

    • Types of Calculations
    • Built-in Functions (Number, String, Date, Logical and Aggregate)
    • Operators and Syntax Conventions
    • Table Calculations
    • Level of Detail (LOD) Calculations
    • Using R within Tableau for Calculations

    Advanced Visual Analytics

    • Parameters
    • Tool tips
    • Trend lines
    • Reference lines
    • Forecasting
    • Clustering

    Level of Detail (LOD) Expressions in Tableau

    • Count Customer by Order
    • Profit per Business Day
    • Comparative Sales
    • Profit Vs Target
    • Finding the second order date
    • Cohort Analysis

    Geographic Visualizations in Tableau

    • Introduction to Geographic Visualizations
    • Manually assigning Geographical Locations
    • Types of Maps
    • Spatial Files
    • Custom Geocoding
    • Polygon Maps
    • Web Map Services
    • Background Images

    Advanced charts in Tableau

    • Box and Whisker?s Plot
    • Bullet Chart
    • Bar in Bar Chart
    • Gantt Chart
    • Waterfall Chart
    • Pareto Chart
    • Control Chart
    • Funnel Chart
    • Bump Chart
    • Step and Jump Lines
    • Word Cloud
    • Donut Chart

    Dashboards and Stories

    • Introduction to Dashboards
    • The Dashboard Interface
    • Dashboard Objects
    • Building a Dashboard
    • Dashboard Layouts and Formatting
    • Interactive Dashboards with actions
    • Designing Dashboards for devices
    • Story Points

    Get Industry Ready

    • Tableau Tips and Tricks
    • Choosing the right type of Chart
    • Format Style
    • Data Visualization best practices

    Exploring Tableau Online

    • Publishing Workbooks to Tableau Online
    • Interacting with Content on Tableau Online
    • Data Management through Tableau Catalog
    • AI-Powered features in Tableau Online (Ask Data and Explain Data)
    • Understand Scheduling
    • Managing Permissions on Tableau Online
    • Data Security with Filters in Tableau Online

    AI Integration in Tableau:

    • Ask Data: Natural Language Data Exploration
    • Explain Data: Automatic statistical insights
    • Tableau GPT (Einstein Copilot - Salesforce)
    • AI forecasting in visualizations
    • Integration with Python (TabPy) and R

    Capstone Project

Free Quiz

Python

Python for Data Analyst

Take Exam
My SQL & SQL

My SQL & SQL Exam

Take Exam
Excel

Analytics with Excel

Take Exam
Microsoft Power BI

Microsoft Power BI

Take Exam
Tableau

Tableau

Take Exam

Course Design By

naswipro

Nasscom & Wipro

Course Offered By

croma-orange

Croma Campus

Master's Program Certificate

You will get certificate after completion of program

Tools Covered of AI Powered Data Analytics

Python

Python

Tableau

Tableau

Power BI

Power BI

Excel

Excel

SQL

SQL

Data analytics

Data analytics

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AI Powered Data Analytics Projects

Domain: Healthcare

Project Name:

Healthcare Readmission Prediction

An AI-powered model designed to predict hospital readmissions using patient health records and treatment history. The solution helps healthcare providers reduce costs, optimize resources, and enhance the quality of patient care. Dashboards visualize readmission risks, supporting data-driven clinical decisions.

Tools & Technology Used

Domain: Education

Project Name:

Student Performance Prediction in Education

A machine learning-based solution that predicts student performance by analyzing attendance, grades, and engagement data. The model enables early identification of at-risk students, supporting timely interventions to improve academic outcomes. Dashboards provide insights into progress trends for educators and administrators.

Tools & Technology Used

Domain: Manufacturing

Project Name:

Predictive Maintenance for Manufacturing

An AI-driven solution that leverages sensor and operational data from machines to predict potential equipment failures. The system minimizes unplanned downtime, optimizes maintenance schedules, and reduces overall costs. Interactive dashboards display real-time maintenance alerts for proactive decision-making.

Tools & Technology Used

Domain: E-commerce

Project Name:

Sentiment Analysis for E-commerce Reviews

An NLP-driven project that classifies customer reviews into positive, negative, or neutral categories. The analysis provides deep insights into customer opinions, enabling businesses to enhance product quality, improve customer satisfaction, and refine marketing strategies. Visual dashboards highlight sentiment trends to support data-driven decision-making.

Tools & Technology Used

Domain: Travel & Hospitality

Project Name:

Dynamic Pricing for Travel & Hospitality

An AI-powered dynamic pricing system designed for hotels and airlines to maximize revenue. The model analyzes booking patterns, seasonal demand, and competitor pricing to recommend optimal prices in real-time. Interactive dashboards provide insights into pricing trends and help improve revenue management strategies.

Tools & Technology Used

Domain: Banking

Project Name:

Credit Risk Assessment in Banking

An AI-powered credit risk scoring model developed using historical loan repayment data and demographic features. The solution evaluates borrower profiles, predicts default probability, and assists in smarter lending decisions. Interactive dashboards enable portfolio risk analysis, ensuring proactive risk management and regulatory compliance.

Tools & Technology Used

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Job Target Roles

Data Analyst ₹4L - ₹10L

Data Scientist ₹8L - ₹15L

ML Engineer ₹7L - ₹10L

AI Engineer ₹8L - ₹12L

Data Engineer ₹6L - ₹10L

BI Analyst ₹5L - ₹10L

GenAI Engineer ₹10L - ₹15L

AI Architect ₹10L - ₹12L

Data Manager ₹9L - ₹12L

AI Analyst ₹6L - ₹12L

Tech Analyst ₹7L - ₹12L

Data Leader ₹12L - ₹18L

AI Leader ₹12L - ₹15L

AI Officer ₹15L - ₹20L

AI Director ₹12L - ₹20L

AI Director ₹12L - ₹20L

AI Officer ₹15L - ₹20L

AI Leader ₹12L - ₹15L

Data Leader ₹12L - ₹18L

Tech Analyst ₹7L - ₹12L

AI Analyst ₹6L - ₹12L

Data Manager ₹9L - ₹12L

AI Architect ₹10L - ₹12L

GenAI Engineer ₹10L - ₹15L

BI Analyst ₹5L - ₹10L

Data Engineer ₹6L - ₹10L

AI Engineer ₹8L - ₹12L

ML Engineer ₹7L - ₹10L

Data Scientist ₹8L - ₹15L

Data Analyst ₹4L - ₹10L

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Masters in AI Powered Data Analytics is designed to help learners get the competencies for mastering artificial intelligence and data analytics. It focuses on the use of AI tools like machine learning, natural language processing, and predictive modeling in making better business decisions. You will learn

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A career post-study in this Masters in AI Powered Data Analytics provides scope in data science, AI engineering, and business analytics. The employers are looking for professionals who are not only good at crunching numbers but also in applying AI models to forecast outcomes and automate processes.

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