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Data Analytics Mastery Program

Become a data analytics professional in 6 months. Master Excel, Power BI, Python, and MySQL for data-driven decision making.

Duration: 6 months
Mode: hybrid
Language: Hindi/English
View Curriculum

Curriculum

Module 1: Excel for Data Analysis

4 weeks

Topics Covered:

  • Excel Fundamentals
  • - Excel Interface & Navigation
  • - Data Entry & Formatting
  • - Cell Referencing (Relative, Absolute, Mixed)
  • - Working with Worksheets & Workbooks
  • Data Cleaning & Preparation
  • - Text to Columns, Flash Fill
  • - Remove Duplicates, Data Validation
  • - Find & Replace, Sorting & Filtering
  • - Handling Missing Data
  • Advanced Formulas & Functions
  • - Logical Functions (IF, AND, OR, IFS)
  • - Lookup Functions (VLOOKUP, HLOOKUP, XLOOKUP, INDEX-MATCH)
  • - Text Functions (LEFT, RIGHT, MID, LEN, CONCATENATE, TEXT)
  • - Date & Time Functions (DATE, DAY, MONTH, YEAR, EOMONTH, NETWORKDAYS)
  • - Mathematical Functions (SUMIFS, COUNTIFS, AVERAGEIFS, SUMPRODUCT)
  • - Statistical Functions (AVERAGE, MEDIAN, MODE, STDEV, VAR)
  • Data Analysis Tools
  • - Pivot Tables & Pivot Charts
  • - What-If Analysis (Goal Seek, Data Tables, Scenario Manager)
  • - Solver for Optimization
  • - Power Query for Data Transformation
  • Excel Charts & Visualization
  • - Column, Bar, Line, Pie Charts
  • - Combo Charts, Waterfall, Funnel, Gantt
  • - Conditional Formatting
  • - Sparklines
  • Advanced Excel
  • - Macros & VBA Basics
  • - Array Formulas
  • - Dynamic Arrays (FILTER, SORT, UNIQUE, SEQUENCE)
  • - Excel Dashboard Design Principles

Projects:

  • Sales Data Cleaning & Analysis Dashboard
  • HR Employee Attrition Analysis with Pivot Tables
  • Financial Statement Analysis with Excel

Module 2: SQL for Data Analysis

3 weeks

Topics Covered:

  • Database Fundamentals
  • - Relational Database Concepts
  • - Database Design & Normalization
  • - Data Types in SQL
  • MySQL Setup & Basic Commands
  • - Installation & Configuration
  • - MySQL Workbench Interface
  • - Database Creation & Management
  • SQL Basics
  • - SELECT, WHERE, ORDER BY, LIMIT, DISTINCT
  • - Filtering (AND, OR, NOT, IN, BETWEEN, LIKE)
  • - Handling NULL Values
  • Data Manipulation
  • - INSERT, UPDATE, DELETE
  • - ALTER, DROP, TRUNCATE
  • Aggregate Functions
  • - COUNT, SUM, AVG, MIN, MAX
  • - GROUP BY & HAVING Clauses
  • JOINS
  • - INNER JOIN, LEFT JOIN, RIGHT JOIN
  • - FULL OUTER JOIN, CROSS JOIN, SELF JOIN
  • - Joining Multiple Tables
  • Subqueries & CTEs
  • - Scalar, Row, Table Subqueries
  • - Correlated Subqueries
  • - Common Table Expressions (WITH clause)
  • - Recursive CTEs
  • Window Functions
  • - ROW_NUMBER, RANK, DENSE_RANK
  • - LAG, LEAD, NTILE
  • - Running Totals & Moving Averages
  • Advanced SQL
  • - CASE Statements
  • - UNION, INTERSECT, EXCEPT
  • - Views & Indexes
  • - Stored Procedures & Functions
  • Query Optimization
  • - EXPLAIN, Execution Plans
  • - Indexing Strategies
  • - Query Performance Tuning
  • Connecting Python to SQL
  • - SQLAlchemy, pandas.read_sql

Projects:

  • E-commerce Sales Analysis with Complex SQL Queries
  • Customer Segmentation with RFM Analysis (SQL)
  • Zomato/Swiggy Order Data Analysis

Module 3: Python for Data Analytics

4 weeks

Topics Covered:

  • Python Fundamentals
  • - Python Setup (Anaconda, Jupyter, VS Code)
  • - Variables, Data Types, Operators
  • - Control Flow (if/else, loops)
  • - Functions (def, lambda, map, filter)
  • - Data Structures (Lists, Tuples, Dictionaries, Sets)
  • - String Manipulation
  • - File Handling (CSV, Excel, JSON)
  • - Error Handling (try/except)
  • NumPy
  • - NumPy Arrays (Creation, Indexing, Slicing)
  • - Array Operations (Mathematical, Statistical)
  • - Broadcasting & Vectorization
  • Pandas
  • - Series & DataFrame (Creation, Indexing)
  • - Data Loading (CSV, Excel, SQL, JSON)
  • - Data Inspection (head, info, describe, shape)
  • - Handling Missing Data (isnull, fillna, dropna)
  • - Data Cleaning (Duplicates, Outliers, Type Conversion)
  • - Data Transformation (apply, map, groupby)
  • - Pivot Tables & Cross-tabulations
  • - Merging & Joining (concat, merge, join)
  • - Time Series Data Handling
  • Data Analysis with Pandas
  • - Exploratory Data Analysis
  • - Aggregations & Summary Statistics
  • - Filtering & Conditional Operations
  • - Date/Time Operations
  • Data Visualization with Python
  • - Matplotlib (Line, Bar, Scatter, Histogram, Subplots)
  • - Seaborn (Distribution, Categorical, Relational, Heatmap)
  • - Interactive Visualizations with Plotly

Projects:

  • Sales Data Analysis & Visualization (Pandas + Plotly)
  • COVID-19 Data Analysis & Time Series Trends
  • Customer Purchase Pattern Analysis

Module 4: Power BI Desktop

5 weeks

Topics Covered:

  • Introduction to Power BI
  • - Power BI Ecosystem (Desktop, Service, Mobile)
  • - Power BI Interface & Navigation
  • - Connecting to Data Sources
  • Power Query (Data Transformation)
  • - Importing Data (Excel, CSV, SQL, Web)
  • - Data Cleaning in Power Query
  • - Merging & Appending Queries
  • - Creating Custom Columns
  • - M Language Introduction
  • Data Modeling
  • - Relationships (One-to-One, One-to-Many, Many-to-Many)
  • - Star Schema Design
  • - Creating Calculated Columns
  • - DAX Fundamentals
  • DAX (Data Analysis Expressions)
  • - DAX Syntax & Functions
  • - CALCULATE, FILTER, ALL, RELATED
  • - Time Intelligence (YTD, QTD, MTD, Parallel Period)
  • - SUMX, AVERAGEX, FILTER, EARLIER
  • - Creating Measures
  • - DAX Variables
  • Power BI Visualizations
  • - Basic Visuals (Card, Table, Matrix, Chart Types)
  • - Slicers, Filters, Bookmarks, Buttons
  • - Map Visualizations (Filled Map, Shape Map, ArcGIS)
  • - Custom Visuals (From Marketplace)
  • - AI Visuals (Key Influencers, Decomposition Tree)
  • Power BI Dashboards
  • - Dashboard Design Principles
  • - Creating Interactive Dashboards
  • - Drill-Through & Drill-Down
  • - Bookmarks & Report Navigation
  • - Row-Level Security (RLS)
  • Power BI Service
  • - Publishing Reports to Service
  • - Creating Workspaces & Apps
  • - Sharing & Collaboration
  • - Data Gateway Setup
  • - Scheduled Refresh
  • Advanced Power BI
  • - Parameters & What-If Analysis
  • - DAX Studio & Tabular Editor
  • - Performance Optimization
  • - Power BI Premium Features

Projects:

  • Sales Performance Dashboard (Power BI)
  • HR Analytics Dashboard with DAX Measures
  • Financial KPI Dashboard with Drill-Through
  • Supply Chain Dashboard with Map Visualizations

Module 5: Business Intelligence & Data Storytelling

3 weeks

Topics Covered:

  • Business Intelligence Fundamentals
  • - What is BI & Its Importance
  • - BI vs Data Analytics vs Data Science
  • - BI Lifecycle & Best Practices
  • Understanding Business Context
  • - Identifying Business Problems
  • - Defining KPIs & Metrics
  • - Stakeholder Management
  • Data Storytelling
  • - Storytelling Framework
  • - Choosing Right Visualizations
  • - Color Theory in Dashboards
  • - Creating Executive Summary
  • - Presentation Skills for Analysts
  • Dashboard Design Principles
  • - Layout & Navigation
  • - Interactivity & User Experience
  • - Mobile Optimization
  • - Performance Considerations
  • Real-World Business Domains
  • - Sales & Marketing Analytics
  • - Finance Analytics
  • - HR Analytics
  • - Operations & Supply Chain
  • - Healthcare Analytics
  • Advanced Analytics
  • - What-If Analysis
  • - Trend Analysis & Forecasting
  • - Root Cause Analysis

Projects:

  • Executive Dashboard with Actionable Insights
  • Data Story Presentation for Business Stakeholders
  • Industry-Specific Analytics Project

Module 6: Statistics for Data Analytics

2 weeks

Topics Covered:

  • Descriptive Statistics
  • - Mean, Median, Mode
  • - Variance, Standard Deviation
  • - Skewness & Kurtosis
  • - Percentiles & Quartiles
  • Data Distributions
  • - Normal Distribution
  • - Binomial Distribution
  • - Poisson Distribution
  • Inferential Statistics
  • - Sampling Methods
  • - Central Limit Theorem
  • - Confidence Intervals
  • Hypothesis Testing
  • - Null & Alternative Hypothesis
  • - p-value & Significance Level
  • - Type I & Type II Errors
  • - T-Test (One Sample, Two Sample)
  • - Chi-Square Test
  • - ANOVA
  • Correlation & Regression
  • - Correlation (Pearson, Spearman)
  • - Simple Linear Regression
  • - Multiple Linear Regression
  • - R-Squared & Adjusted R-Squared

Projects:

  • A/B Test Analysis for Marketing Campaign
  • Statistical Analysis for Business Decision Making

Module 7: Advanced Excel & Power BI Integration

2 weeks

Topics Covered:

  • Advanced Excel
  • - Power Query (Get & Transform)
  • - Power Pivot (Data Modeling in Excel)
  • - DAX in Excel Power Pivot
  • - Advanced Pivot Table Techniques
  • - Financial Functions (NPV, IRR, PMT)
  • - Advanced Dashboarding in Excel
  • Power BI & Excel Integration
  • - Importing Excel Data into Power BI
  • - Using Excel as Data Source
  • - Exporting Power BI to Excel
  • - Analyze in Excel Feature
  • Power BI & Python Integration
  • - Using Python in Power Query
  • - Creating Python Visuals in Power BI
  • Power BI & SQL Integration
  • - DirectQuery Mode
  • - Import vs DirectQuery
  • - Composite Models
  • Performance Optimization
  • - DAX Performance Tuning
  • - Query Folding
  • - Aggregation Tables

Projects:

  • Integrated Analytics Solution (Excel + Power BI + SQL)
  • Optimized Dashboard for Large Datasets

Module 8: Capstone Projects & Career Preparation

3 weeks

Topics Covered:

  • Capstone Projects
  • - Problem Definition & Business Context
  • - Data Collection & Cleaning
  • - Exploratory Data Analysis
  • - Dashboard Creation (Power BI + Excel)
  • - Insights & Recommendations
  • - Stakeholder Presentation
  • Portfolio Building
  • - GitHub Repository Setup
  • - Project Documentation
  • - Case Studies Writing
  • Resume & LinkedIn Preparation
  • - ATS-Friendly Data Analyst Resume
  • - LinkedIn Profile Optimization
  • - Writing Effective Projects
  • Interview Preparation
  • - SQL & Excel Interview Questions
  • - Power BI & Python Questions
  • - Business Case Studies
  • - Behavioral Questions
  • Job Search Strategy
  • - Job Portals (Naukri, LinkedIn, Wellfound)
  • - Data Analyst Job Roles
  • - Freelancing & Consulting
  • Certification Preparation
  • - Microsoft PL-300 (Power BI Data Analyst)
  • - Google Data Analytics Certificate

Projects:

  • Capstone 1: Sales & Revenue Analytics Dashboard
  • Capstone 2: HR Employee Analytics & Attrition Dashboard
  • Capstone 3: Marketing Campaign Performance Analysis
  • Professional Data Analytics Portfolio

Learning Objectives

  • ✓Master Microsoft Excel for data cleaning, analysis, and visualization
  • ✓Build interactive dashboards using Power BI and DAX
  • ✓Write complex SQL queries for data extraction and manipulation
  • ✓Use Python with Pandas, NumPy, and Matplotlib for data analysis
  • ✓Perform exploratory data analysis (EDA) on real-world datasets
  • ✓Create compelling data stories and business presentations
  • ✓Understand business intelligence concepts and KPIs
  • ✓Build an end-to-end data analytics portfolio with 10+ projects

Why Choose Data Analytics Mastery Program?

The Data Analytics Mastery Program is a comprehensive 6-month journey that takes you from absolute beginner to job-ready data analyst. This program covers the complete analytics stack - Excel, Power BI, Python, and MySQL - with 10+ real-world projects.

  • Complete Analytics Stack: Excel, Power BI, Python, MySQL — everything you need
  • 10+ Real-World Projects: Build sales dashboards, HR analytics, marketing analysis, and more
  • Industry-Standard Tools: Master Excel (advanced), Power BI (DAX), Python (Pandas), and SQL
  • Business-Focused: Learn business intelligence, KPIs, and data storytelling
  • Portfolio Focus: Every module produces a project for your portfolio
  • Placement Support: Resume building, mock interviews, and job referrals

Who Should Enroll?

  • Fresh Graduates (Any Stream - BCom, BBA, BCA, BSc, BA) wanting a career in analytics
  • Working Professionals wanting to switch to data analytics roles
  • Finance & Accounting Professionals wanting to upgrade analytics skills
  • Marketing Professionals wanting data-driven decision-making skills
  • Business Analysts wanting to strengthen technical skills
  • Anyone passionate about data and business insights

No prior coding experience required! We start from basics.

What You'll Build

Excel Projects

  • Sales Data Cleaning & Analysis Dashboard
  • HR Employee Attrition Analysis
  • Financial Statement Analysis
  • Advanced Excel Dashboards

SQL Projects

  • E-commerce Sales Analysis
  • Customer RFM Segmentation
  • Order & Delivery Data Analysis

Python Projects

  • Sales Data Analysis & Visualization
  • COVID-19 Time Series Analysis
  • Customer Purchase Pattern Analysis

Power BI Projects

  • Sales Performance Dashboard
  • HR Analytics Dashboard with DAX
  • Financial KPI Dashboard
  • Supply Chain Dashboard

Capstone Projects

  • Sales & Revenue Analytics Dashboard
  • HR Employee Analytics
  • Marketing Campaign Analysis

Career Opportunities

Entry-Level (₹3-6 LPA)

  • Data Analyst
  • Business Analyst
  • Junior Data Analyst
  • MIS Executive

Mid-Level (₹6-12 LPA)

  • Data Analyst
  • Business Intelligence Analyst
  • Power BI Developer
  • Analytics Consultant

Senior-Level (₹12-20+ LPA)

  • Senior Data Analyst
  • Analytics Manager
  • BI Lead
  • Data Analytics Consultant

Top Hiring Companies

  • Consulting: Deloitte, EY, KPMG, PwC, Accenture
  • Finance: JPMC, HDFC, ICICI, American Express
  • E-commerce: Amazon, Flipkart, Myntra, Zomato
  • Tech: Microsoft, Google, Salesforce
  • Startups: Razorpay, CRED, Groww
  • FMCG: P&G, Unilever, Nestle

Learning Experience

Learning Format

  • Duration: 6 months
  • Mode: Hybrid (Online/Offline)
  • Schedule: 10-12 hours per week
  • 8 modules from Excel to Power BI & Python

Learning Methodology

  • 20% Theory & Concepts
  • 80% Hands-on Practice & Projects
  • Weekly assignments and coding exercises
  • Capstone projects with mentor evaluation
  • Mock interviews and career preparation

Course Includes

  • Course Material: Notes, datasets, templates, and project guides
  • Power BI Premium: Free access for students
  • Assessments: Weekly quizzes, assignments, and project evaluations
  • Certification: Data Analytics Mastery Certificate
  • Job Support: Resume, LinkedIn, GitHub portfolio, mock interviews
  • Community: Alumni network and peer support

Fee Structure

Course Fee: ₹28,000 (6 months)

Payment Options:

  1. One-time Payment: ₹25,000 (₹3,000 discount)
  2. Quarterly: ₹6,250 × 4
  3. Monthly: ₹4,167 × 6

Frequently Asked Questions

Do I need prior coding experience?

No. This program starts from basics. We teach Excel from scratch, SQL from basics, and Python for analytics from fundamentals.

Why Excel when we have Power BI and Python?

Excel is still the most widely used analytics tool in the industry. Many business decisions are made in Excel. We teach it as a foundation and then build on it with Power BI and Python.

What is the difference between Power BI and Excel?

Power BI is more powerful for creating interactive dashboards and handling large datasets. Excel is great for ad-hoc analysis and is more accessible. Most companies use both.

Do I need to buy Power BI?

No. Power BI Desktop is free. We provide you with access to Power BI Pro features for learning purposes.

Can I get a job after this course?

Yes! With 10+ projects, a deployed dashboard, and career preparation module, you'll be well-prepared for Data Analyst, Business Analyst, and BI Developer roles.

Is Python really needed for data analytics?

Yes, Python is becoming essential for data analytics. It helps with advanced data manipulation, automation, and working with larger datasets. It makes you a more valuable analyst.

What if I don't have a powerful laptop?

Data analytics tools are lightweight. A laptop with 4GB RAM works fine for Excel and Power BI. 8GB is recommended but not mandatory.

Will I get a certificate?

Yes, you will receive a Data Analytics Mastery Certificate upon successful completion of the program and all projects.

Is this course recognized by companies?

Our certificate is recognized by our hiring partners. More importantly, the portfolio you build will speak for itself in interviews.

Tags

Data AnalyticsExcelPower BIPythonMySQLBusiness IntelligenceData VisualizationDashboard

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