📅 2-Hours-Per-Day Data Analytics Training Plan for College Students - fast track course for future HR leaders

Day 1: Data Analysis Foundations

• Session 1 (1 hr): Introduction to Data Analysis

  • What is Data Analysis? Why is it important?

  • Real-life use cases (Retail, Netflix, etc.)

  • Business terminology in action

• Session 2 (1 hr): Preparing Data for Analysis

  • Data cleaning, transformation & preparation

  • Hands-on: Removing duplicates, handling missing values

  • Real-life examples with survey & e-commerce data

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Day 2: Data Quality & Tools

• Session 3 (1 hr): Common Data Problems

  • Identifying errors, inconsistencies & solutions

  • HR & Banking examples

  • Practical fixes (date formats, currency consistency)

• Session 4 (1 hr): Tools for Data Analysis

  • Intro to Excel, Power BI, Tableau, Python & R

  • Hands-on demo (Excel pivot, Power BI dashboard sample)

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Day 3: Evolution & Types of Analytics

• Session 5 (1 hr): Evolution of Analytics

  • From Excel reports → AI insights

  • Old vs modern methods with industry examples

• Session 6 (1 hr): Four Types of Analytics

  • Descriptive, Diagnostic, Predictive, Prescriptive

  • Hands-on mini case studies (Sales, Supply Chain, AI Pricing)

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Day 4: CRISP-DM & Basics of Statistics

• Session 7 (1 hr): CRISP-DM Model Overview

  • Framework for systematic data analysis

  • Telecom churn example

• Session 8 (1 hr): Univariate Data Analysis

  • Mean, Median, Mode with examples

  • Hands-on with student dataset (marks, expenses, salary distribution)

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Day 5: Data Visualization

• Session 9 (2 hrs): Data Visualization with Charts

  • Line, Bar, Waterfall, Tree Map, Box Plot

  • Real-life applications (traffic, sales, revenue, salaries)

  • Hands-on: Creating charts in Excel/Power BI

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Day 6: Relationships in Data

• Session 10 (2 hrs): Bi-variate Data Analysis (Regression & Correlation)

  • Understanding relationships between variables

  • Hands-on: Advertising vs revenue, Temp vs ice cream sales

  • Using Excel/Power BI for regression

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Day 7: Advanced Analytics with Power BI

• Session 11 (2 hrs): Power BI Forecasting & Prediction

  • Forecasting sales with Power BI

  • Custom prediction using Python integration

  • Hands-on: Create AI-powered forecast chart

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Day 8: Final Project & Certification

• Session 12 (2 hrs): Hands-On Project + Wrap-up

  • Real-life case study datasets (HR attrition, product feedback, sales prediction)

  • Students work in teams & present findings

  • Recap, Q&A, Certification Distribution

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✅ Total = 8 Days × 2 Hours = 16 Hours
🎯 Outcome: Students not only learn theory but also practice real-world business datasets, preparing them for industry applications.