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Business Analytics

Last Updated:October 31, 2025

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What I will learn?

  • Master data-driven decision-making using advanced analytics techniques.
  • Learn to collect, process, and interpret complex business data.
  • Develop proficiency in statistical analysis, predictive modeling, and visualization tools.
  • Gain practical experience with analytics software and real-world business scenarios

Course Curriculum

Week 1: Introduction to Business Analytics

  • Introduction to Business Analytics
    42:07
  • Data Literacy & Data Sources
    01:04:25
  • Assignment Revision Session
    30:35
  • Test your understanding of Business Analytics Concepts
  • Classifying Data Examples

Week 2: Basic Statistics For Business & Introduction to Excel For Business Analytics

Week 3: Descriptive Statistics in Excel and Data Cleaning Basics

Week 4: Excel Visualizations, Pivot Tables, Pivot Charts, Distribution, and Correlation

Week 5: Business Metrics and Dashboards in Excel

Week 6: Project: Dashboard Creation in Excel and Dashboard Presentation

Week 7: Introduction to SQL – Database Concepts and SQL Basics

Week 8: Introduction to MySQL Workbench: Creating, Managing, and Querying Database

Week 9: SQL Aggregation and HAVING Clause

Week 10: SQL Joins and Advanced Joins

Week 11: SQL subqueries, Common table expressions (CTEs); SQL CASE statements, Window functions

Week 12: SQL Project

Week 13: Data-Driven Decision Making, Advanced Data Visualization and Data Story telling in business

Week 14: Introduction to Tableau and Basic Visualizations in Tableau

Week 15: Calculations and Parameters, Dashboard Design and Story Telling in Tableau

Week 16: Introduction to Power BI and Basic Visualizations in Power BI

Week 17: Power Query for Data Cleaning, DAX, Advanced Visualization, Dashboard Design and Publishing

Week 18: Scenario Planning and What-If Analysis

Week 19: Introduction to Python for Business and Python Basics

Week 20: Introduction to Pandas, Numpy, Data Cleaning and Transformation, EDA, Matplotlib, Seaborn

Week 21: Basic Predictive Analytics: Introduction to Scikit-learn

Week 22: Business Forecasting and Predictive Analysis, Experimentation and Casual Analysis (A/B testing)

Week 23: Capstone Project

Week 24: Capstone Project

Download Courses Curriculum

Material Includes

  • Comprehensive course slides
  • Interactive live class sessions,
  • Hands‑on projects
  • Quizzes, Assignments & Projects
  • Supplemental resources
  • Recorded Live Class Lessons
  • Communities & Mentors
  • Certificate Of Completion

Requirements

  • Access to a Computer or Laptop with Stable Internet
  • Consistent weekly commitment to lectures, coding labs, and project work.
  • Ability to engage in interactive learning and collaborative activities.
  • Basic knowledge of computer operations and file management.
  • Ability to dedicate 8-15 hours per week to lectures, assignments, and hands-on projects

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