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Data Analytics

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Data Analytics

Data Analytics Training

  • Mode : Online / Offline
  • Duration : 4 Months
  • Level : Beginner to Intermediate
  • Prerequisites : Basic Computer Knowledge
  • Tools Covered : Excel, SQL, Python, Power BI, Tableau

Course Overview

This Data Analytics course introduces learners to the fundamentals of collecting, analyzing, and interpreting data for informed decision-making. It covers essential tools such as Excel, SQL, and basic data visualization techniques. The program emphasizes hands-on practice with real-world datasets. It is ideal for beginners, students, and professionals looking to build a career in data analytics.

Course Modules

Month 1: Data Analytics – Excel Foundations

Week 1 : Introduction to Data Analytics

  • What is Data Analytics?
  • Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
  • Data Life Cycle
  • Roles in Data Analytics
  • Real-world use cases

Week 2 : Excel for Data Analysis

  • Excel Basics
  • Sorting, Filtering, Conditional Formatting
  • Charts and Graphs
  • Data Validation
  • Introduction to Pivot Tables

Week 3 : Advanced Excel Functions

  • VLOOKUP, HLOOKUP, INDEX, MATCH
  • IF, SUMIF, COUNTIF, IFERROR
  • Nested Formulas
  • Pivot Tables and Pivot Charts (Advanced)

Week 4 : Excel Dashboards & Mini Project

  • Creating Interactive Dashboards

  • Data Cleaning with Excel

  • Mini Project: Sales Dashboard or HR Analytics

Month 2: SQL for Data Handling

Week 5 : SQL Basics

  • Introduction to Databases
  • What is SQL?
  • SELECT, WHERE, ORDER BY, LIMIT
  • Filtering and Sorting Data

Week 6 : SQL Intermediate

  • Joins (INNER, LEFT, RIGHT, FULL)

  • GROUP BY and Aggregations (SUM, COUNT, AVG)
  • Subqueries, Aliases

Week 7 : SQL Advanced

  • Window Functions (RANK, DENSE_RANK, ROW_NUMBER)
  • CTE (Common Table Expressions)
  • Data Cleaning using SQL

Week 8 : SQL Practice Project


  • Case Study: E-commerce / Bank Transaction Analysis using SQL

  • Hands-on SQL Queries

Month 3: Python for Data Analysis

Week 9 : Python Basics

  • Python Installation and Setup

  • Data Types, Variables, Loops, Functions
  • Working with Lists, Tuples, Dictionaries

Week 10 : Data Analysis with Pandas

  • Reading CSV/Excel files
  • DataFrames and Series
  • Data Cleaning: Handling Nulls, Duplicates
  • Filtering, Sorting, Grouping Data

Week 11 : Data Visualization with Matplotlib & Seaborn

  • Line, Bar, Histogram, Scatter Plots

  • Advanced Visualizations: Heatmaps, Pairplots
  • Plot customization

Week 12 : Python Project

  • Case Study: Customer Churn or Sales Analysis
  • Data Cleaning + EDA (Exploratory Data Analysis)
  • Visualization and Insights

Month 4: Business Intelligence & Dashboards

Week 13 : Power BI Basics

  • Introduction to BI Tools
  • Power BI Interface
  • Importing Data and Data Modeling
  • Creating Visualizations

Week 14 : Power BI Advanced

  • DAX Formulas

  • Slicers, Filters, Drill-through

  • Creating Interactive Reports and Dashboards

Week 15 : Tableau Introduction (Optional Add-on)

  • Interface Overview

  • Connecting Data

  • Visual Analytics

Week 16 : Final Capstone Project & Career Prep

  • End to End Data Analytics Project
  • Excel + SQL + Python + Power BI use
  • Resume Building & Interview Preparation