Data Analytics — I.P.TECH Computer Institute
I.P.TECH
COMPUTER INSTITUTE — LEARN · PRACTICE · GROW

DataAnalytics

TURN DATA INTO INSIGHTS, INSIGHTS INTO IMPACT — TOTAL DURATION: 6 MONTHS

Master the art of data analysis using Python, SQL, Excel, Power BI and more. This program is designed to make you industry-ready with practical skills and real-world examples.

Python & Data Handling (2 Months) SQL, Excel & Power BI (4 Months)
📅

DURATION

6 Months

📚

TOTAL MODULES

12 Modules

⚙️

PRACTICAL FOCUSED

100% Hands-on

📈

LEVEL

Beginner to Advanced

Course Syllabus
Python & Data Handling (2 Months)
1

Python Fundamentals

20 Days

Introduction to Python programming for data analysis.

Why learn it?

Python is the core language used across the entire data analytics workflow.

You will learn
  • Data Types, Variables, Operators
  • Input/Output, Conditional Statements
  • Loops, Functions
  • Lists, Tuples, Sets, Dictionaries
  • File Handling, Exception Handling
Example: Understanding analytics lifecycle with real-life use cases.
2

NumPy

15 Days

Numerical computing library for fast array operations.

Why learn it?

Foundation for all numerical and scientific computing in Python.

You will learn
  • Introduction to NumPy
  • Arrays & Dimensions
  • Indexing & Slicing
  • Array Operations
  • Mathematical Functions
  • Broadcasting
Example: Sales dashboard using Pivot Tables & Charts.
3

Pandas

20 Days

Powerful library for data manipulation and analysis.

Why learn it?

Industry-standard tool for handling structured, tabular data.

You will learn
  • Introduction to Pandas
  • Series & DataFrame
  • Reading & Writing Data
  • Data Selection & Indexing
  • GroupBy Operations
  • Merging, Joining & Concatenation
Example: Analyse student scores using statistics.
4

Data Cleaning & Preprocessing

15 Days

Preparing raw data for accurate analysis.

Why learn it?

Clean data is essential for reliable insights and models.

You will learn
  • Handling Missing Values
  • Removing Duplicates
  • Data Type Conversion
  • Outlier Detection & Treatment
  • Data Normalization
  • Feature Engineering Basics
Example: Analyse customer orders database.
SQL, Excel & Power BI (4 Months)
5

Data Visualization (Matplotlib & Seaborn)

15 Days

Creating visual representations of data.

Why learn it?

Helps communicate insights clearly through charts and graphs.

You will learn
  • Introduction to Matplotlib
  • Line, Bar, Pie, Histogram Plots
  • Subplots & Customization
  • Introduction to Seaborn
  • Statistical Plots
  • Heatmap, Pairplot, Distribution Plots
Example: Clean and prepare raw data for analysis.
6

SQL Fundamentals

20 Days

Structured Query Language for managing databases.

Why learn it?

Essential for extracting and querying data from databases.

You will learn
  • Introduction to SQL
  • Database & Table Creation
  • SELECT, WHERE, ORDER BY
  • GROUP BY, HAVING
  • Aggregate Functions
  • Joins (INNER, LEFT, RIGHT)
Example: Build interactive Sales dashboard in Tableau.
7

Advanced SQL & Query Optimization

15 Days

Advanced querying techniques for complex data problems.

Why learn it?

Improves query performance and handles complex business logic.

You will learn
  • Subqueries & Nested Queries
  • Views & CTE
  • Indexes & Performance
  • Window Functions
  • Query Optimization Techniques
  • Stored Procedures (Basics)
Example: Understanding analytics lifecycle with real-life use cases.
8

Microsoft Excel Basics

10 Days

Foundational spreadsheet skills for data work.

Why learn it?

Excel remains a core tool for quick business analysis.

You will learn
  • Excel Interface & Basics
  • Data Entry & Formatting
  • Basic Formulas (SUM, AVG, COUNT)
  • Sorting & Filtering
  • Conditional Formatting
  • Data Validation
Example: Sales dashboard using Pivot Tables & Charts.
9

Advanced Excel (Functions, Pivot Table, Charts)

15 Days

Deep dive into powerful Excel features.

Why learn it?

Builds advanced analysis and reporting capabilities.

You will learn
  • Advanced Functions (IF, VLOOKUP)
  • INDEX-MATCH, SUMIF, COUNTIF
  • Pivot Table
  • Charts & Graphs
  • Slicers & Timelines
  • Dashboard in Excel
Example: Analyse student scores using statistics.
10

Power BI Fundamentals

15 Days

Business intelligence tool for data visualization.

Why learn it?

Industry-leading tool for creating interactive dashboards.

You will learn
  • Introduction to Power BI
  • Data Import & Transformation
  • Data Modeling Basics
  • Relationships
  • DAX (Basic Measures)
  • Reports & Visuals
Example: Analyse customer orders database.
11

Power BI Dashboard Development

15 Days

Building advanced, interactive dashboards.

Why learn it?

Delivers polished, decision-ready reports for businesses.

You will learn
  • Advanced DAX Functions
  • Interactive Dashboard Creation
  • Filters, Slicers, Bookmarks
  • Drill Through & Tooltips
  • Publishing to Power BI Service
  • Real-world Dashboard Project
Example: Clean and prepare raw data for analysis.
12

Final Project & Case Studies

10 Days

End-to-end data analysis project using real datasets.

Why learn it?

Applies all learned concepts to a practical, real-world scenario.

You will learn
  • End-to-End Data Analysis Project
  • Real-world Datasets
  • Insights & Report Generation
  • Dashboard Creation
  • Presentation & Project Submission
Example: Build interactive Sales dashboard in Tableau.
What You Will Master
Python for Data Analysis
Data Manipulation with NumPy & Pandas
Data Cleaning & Preprocessing
Data Visualization (Matplotlib & Seaborn)
SQL for Data Analysis
Advanced SQL & Query Optimization
Advanced Excel (Functions, Pivot Table, Charts)
Power BI for Dashboard & Reporting
What You Can Develop After Learning This Course
Business Intelligence DashboardsCreate interactive dashboards for sales, marketing, HR, finance and more.
Data Analysis ReportsGenerate meaningful reports that help businesses make data-driven decisions.
Customer SegmentationGroup customers based on behavior, purchases and demographics.
Sales Performance AnalyticsAnalyze sales trends, profit, loss and forecast future performance.
Marketing Campaign AnalysisMeasure campaign performance, ROI, engagement and conversions.
Financial AnalyticsAnalyze financial data, budgets, costs, revenue and profitability.
Operations & Supply Chain AnalyticsOptimize inventory, logistics, delivery and supply chain efficiency.
HR AnalyticsTrack employee performance, attrition, recruitment and productivity.
Real-time KPI DashboardsMonitor KPIs and track business performance in real time.
Real Life Uses & Examples
Healthcare: COVID-19 data tracking, patient analytics, disease prediction and resource planning.
E-commerce: Product recommendations, customer behavior analysis, sales forecasting and churn prediction.
Banking & Finance: Fraud detection, credit scoring, risk management, loan prediction and portfolio analysis.
Retail: Demand forecasting, inventory optimization, customer segmentation and market basket analysis.
Telecom: Customer churn prediction, usage analysis, network performance and fraud detection.
Education: Student performance analysis, retention prediction, learning analytics and placement analysis.
Course Flow — Learning Path
COLLECT DATASourcing & Import
↓
CLEAN & PREPARE DATAHandling Missing Values
↓
ANALYZE (PYTHON, SQL)Manipulation & Querying
↓
VISUALIZE DATA (EXCEL, POWER BI)Charts & Reports
↓
BUILD DASHBOARDSInteractive Reporting
↓
GENERATE INSIGHTSPattern Discovery
↓
MAKE BETTER DECISIONSData-Driven Strategy
↓
BUSINESS IMPACT & GROWTHReal-World Results
Tools & Technologies
🐍Python
🔢NumPy
🐼Pandas
🗄️SQL
📗Microsoft Excel
📊Power BI
📈Tableau
🐬MySQL
📓Jupyter
☁️Google Colab
🖥️VS Code
🔧Git & GitHub
Projects You Will Build
Sales Performance Dashboard
Customer Segmentation Analysis
Financial Data Analysis Report
HR Analytics Dashboard
Marketing Campaign Analysis
Inventory & Supply Chain Analytics
Student Performance Analysis
Healthcare Data Analysis
E-commerce Sales Forecasting
End-to-End Data Analytics Project
Course Highlights

🏆 Famous Real-World Applications Built Using Data Analytics

  • Google Analytics — Website traffic analysis
  • Netflix — Movie recommendations
  • Amazon — Product recommendations
  • Uber — Demand prediction & route optimization
  • Zomato — Restaurant recommendations
  • Paytm — Fraud detection & risk management
  • Flipkart — Sales forecasting & customer insights
  • YouTube — Content recommendations
  • Facebook/Meta — User behavior analysis & ad targeting
  • Spotify — Music recommendations

✔ Benefits of Learning

  • High demand across every industry
  • Turn raw data into actionable business insights
  • Strong foundation in Python, SQL & BI tools
  • Widely used, versatile and career-flexible skillset
  • Great for corporate roles & freelancing
  • Long-term career growth

💼 Career Opportunities

  • Data Analyst
  • Business Analyst
  • Data Scientist (Foundation)
  • BI Developer
  • SQL Developer
  • Reporting Analyst
  • MIS Executive
  • Freelancer / Consultant
TURN DATA INTO INSIGHTS. BUILD YOUR CAREER WITH DATA ANALYTICS!

Course Outcome

By the end of this course, you will be able to collect, clean, analyze and visualize data to generate meaningful business insights using Python, SQL, Excel and Power BI.

Who Should Join?

Students, Graduates, Working Professionals & anyone who wants to start a career in Data Analytics.

Prerequisites

Basic computer knowledge and interest in working with data and numbers.

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