Learn Data Science

Module 1: Introduction to Data Analysis

⏳ 1.5 hours

• Topics: Overview of analysis lifecycle, data formats, project planning.

• Hands-on: Outline a data analysis project and explore sample datasets.

Module 2: Python & Pandas Essentials

⏳ 2 hours

• Topics: Series and DataFrame objects, indexing, filtering, merging.

• Hands-on: Load CSV/Excel data into Pandas and perform basic manipulations.

Module 3: Data Cleaning & Wrangling

⏳ 3 hours

• Topics: Handling missing data, outlier detection, type conversion, feature creation.

• Hands-on: Clean a messy dataset and engineer new variables for analysis.

Module 4: Exploratory Data Visualization

⏳ 2.5 hours

• Topics: Histograms, box plots, scatter plots, pair plots, and heatmaps.

• Hands-on: Visualize distributions and relationships to uncover insights.

Module 5: Statistical Analysis

⏳ 2.5 hours

• Topics: Descriptive statistics, correlation, hypothesis testing, confidence intervals.

• Hands-on: Compute summary metrics and perform t-tests and chi-square tests.

Module 6: SQL for Data Analysis

⏳ 2 hours

• Topics: SELECT statements, joins, aggregations, subqueries, window functions.

• Hands-on: Query a sample relational database to extract and summarize data.

Module 7: Time Series Analysis

⏳ 2 hours

• Topics: Date/time handling, rolling statistics, seasonal decomposition, simple forecasting.

• Hands-on: Analyze sales data over time and generate trend charts.

Module 8: Dashboarding & Reporting

⏳ 2 hours

• Topics: Designing dashboards, interactive widgets with Plotly or Streamlit basics.

• Hands-on: Build a simple dashboard to present key metrics.

Module 9: Capstone Project

⏳ 2.5 hours

• Topics: End-to-end project planning, execution, and presentation.

• Hands-on: Complete a full analysis—from data ingestion to a polished report—and share results.

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