Comprehensive Data Analysis Course Outline Title: Data Analysis with Python, SQL, Power BI & Tableau Duration: 10–12 Weeks (4–6 hours/week) Audience: Aspiring Data Analysts, Business Analysts, Researchers, Graduates, Career Switchers Learning Mode: Blended (Hands-on + Projects + Assessments) 🔹 Module 1: Introduction to Data Analysis Topics: What is Data Analysis? Roles, tools, and workflow of a data analyst Introduction to structured vs unstructured data Course roadmap overview Outcome: Understand the data analysis landscape and tool relevance. 🔹 Module 2: Python for Data Analysis (Weeks 1–3) Topics: Python setup and syntax Data types, variables, operators Control flow and functions Numpy for numerical analysis Pandas for data cleaning and manipulation DataFrames: filtering, sorting, merging Exploratory Data Analysis (EDA) Data visualization with Matplotlib and Seaborn Project: Analyze a CSV dataset and generate insights (e.g., sales, healthcare, or education dataset) Outcome: Clean, transform, and explore data using Python. 🔹 Module 3: SQL for Data Extraction & Analysis (Weeks 4–5) Topics: Introduction to databases & relational models CRUD operations: SELECT, INSERT, UPDATE, DELETE Filtering and sorting data Joins: INNER, LEFT, RIGHT, FULL GROUP BY, HAVING, aggregation functions Subqueries and CTEs Window functions (ROW_NUMBER, RANK, etc.) Exporting SQL results to Excel or CSV Project: Write SQL queries to analyze customer behavior, sales, or performance data from a relational database. Outcome: Query and analyze datasets stored in databases. 🔹 Module 4: Power BI for Business Intelligence (Weeks 6–7) Topics: Power BI Desktop vs Power BI Service Connecting to data sources (Excel, SQL Server, Web) Power Query Editor for data cleaning Data modeling and relationships Creating measures and calculated columns with DAX Visualizations: bar, line, map, matrix, slicers Dashboards, interactivity, and filters Publishing and sharing reports Project: Build a dashboard analyzing sales, inventory, or financial KPIs for a fictional company. Outcome: Create powerful business dashboards with Power BI. 🔹 Module 5: Tableau for Visual Analytics (Weeks 8–9) Topics: Tableau Desktop/Public interface Connecting to and preparing data Building charts: line, bar, scatter, maps Dimensions vs Measures Calculated fields, parameters, and sets Filters and dashboard interactivity Publishing and sharing dashboards Project: Visualize performance metrics and trends using Tableau dashboards for a business scenario (e.g., product sales or market trends) Outcome: Communicate insights effectively using visual storytelling. 🔹 Module 6: Final Capstone Project (Weeks 10–11) Project Scope (choose one domain): Retail Sales & Inventory Analysis Customer Segmentation & Retention Strategy Healthcare Trends Analysis Marketing Campaign Performance Requirements: Clean & analyze data using Python & SQL Visualize data using Power BI and Tableau Create a presentation/report showcasing insights and recommendations Outcome: Demonstrate real-world data analysis skills across the four tools. 🔹 Module 7: Portfolio Building & Career Prep (Week 12) Topics: Creating a data analyst portfolio Hosting dashboards (Tableau Public, Power BI Service) GitHub for code projects Resume & LinkedIn tips for analysts Interview prep: SQL queries, Python scripts, dashboard walkthroughs Outcome: Get job-ready with a solid portfolio and interview confidence. 🎓 Add-ons (Optional) Weekly assignments and mini-quizzes per module Peer review on dashboards and code Certificate upon course completion Mock interviews & live feedback sessions
