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Business Analytics
Curriculum
The Course Curriculam
Week 1: Introduction to Business Analytics
Overview of business analytics: Scope and applications.
Types of analytics: Descriptive, predictive, and prescriptive.
Data types, data collection, and data quality assessment.
Case studies: Real-world applications of business analytics.
Hands-on Practice: Analyzing sample business scenarios using Excel.
Week 2: Data Analysis Using Excel
Data manipulation: Sorting, filtering, and conditional formatting.
Functions and formulas: Statistical, logical, and lookup functions.
Data visualization: Creating charts, graphs, and dashboards.
Hands-on Practice: Develop a dynamic dashboard for sales data.
Week 3: Introduction to Statistical Analysis
Basics of statistics: Mean, median, mode, variance, and standard deviation.
Data distribution and probability concepts.
Hypothesis testing and confidence intervals.
Hands-on Practice: Perform a hypothesis test on customer data using Excel or Python.
Week 4: Introduction to Data Visualization Tools
Basics of data storytelling and visualization principles.
Introduction to Tableau or Power BI: Interface and functionalities.
Creating interactive dashboards and visualizations.
Hands-on Practice: Build a business performance dashboard using Tableau/Power BI.
Week 5: Predictive Analytics
Basics of predictive modeling: Regression and classification.
Introduction to machine learning for business analytics.
Implementing linear regression and decision trees.
Hands-on Practice: Predict sales trends using Python or Excel-based tools.
Week 6: Prescriptive Analytics and Optimization
Introduction to optimization techniques.
Linear programming and decision analysis.
Scenario analysis and sensitivity analysis.
Hands-on Practice: Optimize resource allocation for a business case using Excel Solver.
Week 7: Big Data Analytics and Tools
Overview of big data in business analytics.
Introduction to SQL for querying large datasets.
Basics of cloud platforms (AWS, Azure) for business analytics.
Hands-on Practice: Query a large dataset using SQL and analyze results.
Week 8: Final Project and Industry Insights
Final Project: Develop an end-to-end business analytics solution for a case study (e.g., customer segmentation, market trend analysis).
Industry insights: Discuss trends like AI in analytics, predictive maintenance, and real-time analytics.
Career preparation: Building a portfolio, crafting a data-driven resume, and interview preparation.
Presentation and feedback session.
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