About Course

About Course

The AI-Assisted Data Analytics Program is designed to prepare learners for careers in Data Analytics, Business Intelligence, Reporting, and Data Visualization. The program focuses on the most in-demand analytics skills required by organizations today, including SQL, Excel, Python, Data Visualization, and Power BI.

Students will learn how to collect, clean, transform, analyze, and visualize data to generate meaningful business insights. The program also introduces AI-assisted analytics workflows, enabling learners to leverage modern AI tools to improve productivity, automate repetitive tasks, and enhance analytical decision-making.

The curriculum emphasizes hands-on learning through real-world datasets, business case studies, dashboard development, portfolio creation, and interview preparation to ensure learners become industry-ready Data Analysts.

Who Should Enroll

• Fresh Graduates

• Engineering Students

• BCA / BCS Graduates

• BBA / BCom Graduates

• MBA Aspirants

• Career Switchers

• Aspiring Data Analysts

• MIS Professionals

• Reporting Analysts

• Business Analysts

Module 1 – Analytics Foundations & Excel

Topics Covered

Introduction to Data Analytics

• What is Data Analytics?

• Data Analytics Lifecycle

• Types of Analytics

  • Descriptive Analytics

  • Diagnostic Analytics

  • Predictive Analytics

  • Prescriptive Analytics

• Business Intelligence Fundamentals

• Data-Driven Decision Making

Business Analytics Fundamentals

• KPIs and Business Metrics

• Metrics vs Dimensions

• Revenue Analysis

• Profitability Analysis

• Customer Analytics

• Customer Retention

• Customer Churn

• Conversion Rate Analysis

• Executive Reporting Concepts

• Business Performance Measurement

Excel Fundamentals

• Excel Interface

• Data Entry & Formatting

• Cell Referencing

• Formulas & Functions

• Data Validation

• Conditional Formatting

Advanced Excel

• Lookup Functions

• VLOOKUP

• HLOOKUP

• XLOOKUP

• INDEX MATCH

• Data Cleaning Techniques

• Data Transformation

Data Analysis using Excel

• Sorting & Filtering

• Pivot Tables

• Pivot Charts

• Slicers

• What-If Analysis

• Scenario Analysis

Tools & Technologies Covered

• Microsoft Excel

• ChatGPT

• Gemini

Expected Outcomes

Students will be able to:

• Understand analytics and business intelligence concepts

• Analyze business data using Excel

• Create reports and dashboards

• Measure business performance using KPIs

• Utilize AI tools to improve analytics workflows

Module 2 – SQL for Data Analytics

Topics Covered

Database Fundamentals

• Introduction to Databases

• Relational Database Concepts

• Database Design Principles

• Data Warehousing Concepts

SQL Fundamentals

• Database Objects

• Tables

• Data Types

• Constraints

• CRUD Operations

• Data Retrieval

Querying Data

• Filtering Data

• Sorting Data

• Aliases

• Limiting Results

Advanced SQL

• Inner Join

• Left Join

• Right Join

• Full Join

• Aggregations

• Group By

• Having Clause

• Subqueries

Analytical SQL

• Common Table Expressions (CTEs)

• Window Functions

• Ranking Functions

• Running Totals

• Analytical Queries

• Reporting Queries

Business Reporting with SQL

• Sales Analytics Queries

• Customer Analytics Queries

• HR Analytics Queries

• Financial Reporting Queries

SQL Optimization

• Indexes

• Query Optimization

• Execution Concepts

• Best Practices

AI-Assisted SQL Development

• SQL Query Generation

• Query Optimization

• SQL Debugging

• Reporting Query Creation

Hands-on

• Retail Sales Analytics

• HR Analytics Reporting

• Banking Analytics Reporting

• Customer Analytics Queries

• E-Commerce Analytics Reporting

Tools & Technologies Covered

• PostgreSQL

• SQL

• pgAdmin

• ChatGPT

Expected Outcomes

Students will be able to:

• Design and query relational databases

• Write complex SQL queries

• Generate business reports

• Analyze data using SQL

• Optimize database queries

Module 3 – Python for Data Analytics

Topics Covered

Python Fundamentals

• Python Introduction

• Variables & Data Types

• Operators

• Conditional Statements

• Loops

• Functions

Statistics for Data Analytics

• Mean

• Median

• Mode

• Variance

• Standard Deviation

• Quartiles

• Percentiles

• Correlation

• Covariance

• Probability Basics

• Sampling Concepts

• Outlier Detection

NumPy

• Arrays

• Array Operations

• Mathematical Functions

• Statistical Functions

• Data Manipulation

Pandas Fundamentals

• Series

• DataFrames

• Importing Data

• Exporting Data

Data Cleaning & Preparation

• Missing Value Handling

• Duplicate Removal

• Data Formatting

• Data Transformation

• Data Aggregation

Data Analysis Techniques

• Filtering Data

• Sorting Data

• Grouping Data

• Merging Datasets

• Exploratory Data Analysis

AI-Assisted Data Analysis

• Data Exploration using AI

• Python Code Generation

• Data Cleaning Assistance

• Insight Generation using AI

Hands-on

• Customer Analytics Project

• Retail Analytics Project

• HR Analytics Project

• Financial Analytics Project

• Data Cleaning Project

Tools & Technologies Covered

• Python

• Jupyter Notebook

• NumPy

• Pandas

• ChatGPT

Expected Outcomes

Students will be able to:

• Analyze business data using Python

• Apply statistical concepts to analytics

• Clean and prepare datasets

• Perform exploratory data analysis

• Generate meaningful business insights

Module 4 – Data Visualization with Matplotlib & Seaborn

Topics Covered

Data Visualization Fundamentals

• Importance of Data Visualization

• Data Storytelling

• Visualization Best Practices

• Chart Selection Techniques

Matplotlib

• Line Charts

• Bar Charts

• Pie Charts

• Histograms

• Scatter Plots

• Multi-Series Charts

• Chart Customization

Seaborn

• Distribution Plots

• Box Plots

• Violin Plots

• Pair Plots

• Heatmaps

• Correlation Analysis

Business Reporting Visualizations

• KPI Reporting

• Trend Analysis

• Performance Analysis

• Customer Analytics Visualization

Dashboard Visualization Design

• Dashboard Layout Principles

• Executive Reporting Design

• Storytelling Dashboards

AI-Assisted Visualization

• Chart Recommendations

• Visualization Optimization

• Automated Insight Generation

Hands-on

• Sales Trend Analysis

• Customer Behavior Analysis

• Executive KPI Visualization

• Business Performance Dashboard

Tools & Technologies Covered

• Python

• Matplotlib

• Seaborn

Expected Outcomes

Students will be able to:

• Create effective visualizations

• Build analytical reports

• Present business insights visually

• Apply data storytelling techniques

Module 5 – Power BI Development

Topics Covered

Power BI Fundamentals

• Power BI Architecture

• Power BI Desktop

• Data Sources

• Data Loading Techniques

Power Query

• Data Cleaning

• Data Transformation

• Data Preparation

• Data Shaping

Data Modeling

• Fact Tables

• Dimension Tables

• Star Schema

• Snowflake Schema

• Relationships

• Model Optimization

DAX Fundamentals

• Measures

• Calculated Columns

• KPIs

• Basic DAX Functions

Advanced DAX

• CALCULATE

• FILTER

• ALL

• RELATED

• RELATEDTABLE

• Time Intelligence Functions

• Running Totals

• Dynamic Measures

Dashboard Development

• Interactive Dashboards

• Filters & Slicers

• Drill Down

• Drill Through

• Dashboard Navigation

Advanced Power BI

• Row-Level Security

• Incremental Refresh

• Report Publishing

• Power BI Service

• Workspace Management

AI Features in Power BI

• Smart Narratives

• AI Visuals

• Forecasting

• Key Influencers

• Decomposition Tree

AI-Assisted Reporting

• Dashboard Design using AI

• DAX Generation using AI

• Business Insight Generation

• Executive Reporting Support

Hands-on

• Sales Dashboard

• HR Dashboard

• Finance Dashboard

• Retail Analytics Dashboard

• Executive Reporting Dashboard

• Customer Analytics Dashboard

Tools & Technologies Covered

• Power BI Desktop

• Power BI Service

• DAX

• Power Query

Expected Outcomes

Students will be able to:

• Build professional Power BI dashboards

• Create business intelligence reports

• Apply advanced DAX techniques

• Develop interactive reporting solutions

• Deliver actionable business insights

Module 6 – Business Analytics Projects & Placement Readiness

Topics Covered

Real-World Analytics Projects

Working with Real Datasets

• Amazon Sales Dataset

• Blinkit Dataset

• Retail Sales Dataset

• HR Attrition Dataset

• Financial Dataset

• E-Commerce Dataset

End-to-End Analytics Workflow

• Data Collection

• Data Cleaning

• Data Analysis

• Data Visualization

• Dashboard Development

• Business Recommendations

Portfolio Development

• GitHub Portfolio

• Power BI Portfolio

• Project Documentation

• Case Study Creation

Placement Readiness Program

• Resume Building

• LinkedIn Profile Optimization

• SQL Interview Preparation

• Power BI Interview Preparation

• Python Interview Preparation

• Mock Interviews

• Business Case Discussions

AI-Assisted Analytics Workflow

• AI-Based Insight Generation

• AI-Assisted Report Writing

• Presentation Preparation using AI

• Executive Summary Creation

Hands-on

Capstone Projects

• Retail Sales Analytics Dashboard

• Customer Churn Analysis

• HR Attrition Dashboard

• Financial Performance Dashboard

• E-Commerce Analytics Dashboard

• Executive Business Intelligence Dashboard

• Supply Chain Analytics Dashboard

Tools & Technologies Covered

• SQL

• PostgreSQL

• Python

• NumPy

• Pandas

• Matplotlib

• Seaborn

• Power BI

• Excel

• GitHub

• ChatGPT

• Gemini

Expected Outcomes

Students will be able to:

• Execute end-to-end analytics projects

• Build professional analytics portfolios

• Present business insights effectively

• Apply analytical thinking to business problems

• Prepare confidently for Data Analyst interviews

Tools & Technologies Covered Across the Program

• Microsoft Excel

• PostgreSQL

• SQL

• Python

• NumPy

• Pandas

• Jupyter Notebook

• Matplotlib

• Seaborn

• Power BI Desktop

• Power BI Service

• DAX

• Power Query

• GitHub

• ChatGPT

• Gemini

Career Opportunities

Upon successful completion of the program, learners can pursue roles such as:

• Data Analyst

• Business Analyst

• MIS Analyst

• Reporting Analyst

• Power BI Developer

• BI Analyst

• Operations Analyst

• Data Visualization Analyst

• Analytics Associate

• Junior Data Analyst

• Business Intelligence Analyst

Expected Outcomes of the Program

By the end of this program, learners will be able to:

• Analyze business data using SQL and Python

• Apply statistical techniques for data analysis

• Clean and transform datasets effectively

• Create impactful visualizations using Python

• Build professional Power BI dashboards

• Develop business intelligence reports

• Generate actionable business insights

• Utilize AI tools to improve analytics workflows

• Build a professional analytics portfolio

• Prepare confidently for Data Analyst and Business Intelligence careers

AI-Assisted Data Analytics Program
Master SQL, Python, Power BI & Business Analytics to become an Industry-Ready Data Analyst.