Data science foundation with MS-Exel

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Course Objectives:
Introduce basic data science concepts through Excel.

Build skills in data cleaning, visualization, and statistical analysis.

Apply Excel functions for real-world datasets.

Perform decision-making using Excel tools like pivot tables, charts, and solver.

Module 1: Introduction to Data Science and Excel (Week 1)
What is Data Science?

Role of Excel in Data Science

Interface overview

Types of data (structured/unstructured)

Data types and formats in Excel

Activities: Practice formatting, entering data, and using basic functions.

Module 2: Data Cleaning and Preprocessing (Week 2)
Removing duplicates, missing values, outliers

Text to Columns, Find & Replace, Data Validation

Logical functions: IF, AND, OR, NOT

Activities: Clean a raw dataset and generate summary reports.

Module 3: Exploratory Data Analysis (Week 3)
Descriptive statistics: Mean, Median, Mode, Std Dev

Sorting, Filtering, Conditional Formatting

Frequency tables and cross-tabulations

Activities: Use =AVERAGE(), =STDEV(), etc., on a student or sales dataset.


Module 4: Data Visualization with Excel (Week 4)
Creating Charts: Bar, Line, Pie, Scatter

Dynamic charts with filters

Chart customization and best practices

Activities: Visualize trends in data using multiple chart types.


Module 5: Statistical Analysis (Week 5)
Correlation and Regression (using Data Analysis Toolpak)

Hypothesis Testing: t-test, Chi-square test

Analyzing relationships in data

Activities: Use Toolpak to run statistical tests on sample datasets.

Module 6: Predictive Tools and Decision-Making (Week 6)
What-If Analysis

Goal Seek and Scenario Manager

Introduction to Solver for optimization

Activities: Optimize resource allocation using Solver.

Module 7: Pivot Tables and Dashboards (Week 7)
Creating and modifying Pivot Tables

Pivot Charts

Building simple dashboards in Excel

Activities: Summarize data and present interactive insights.


Module 8: Mini Project and Presentation (Week 8)
Analyze a dataset of choice (e.g., health, education, business)

Apply learned techniques

Present findings using visuals and insights

Deliverable: 5-slide presentation and Excel file with analysis.

Assessment:
Weekly quizzes

Practical assignments

Final project report and presentation.

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