Power BI + SQL + Python + Fabric + Projects Course with Swapnjeet S

Power BI Complete Video Course - With AI

Beginner to Advanced (With Projects & DAX) + AI in Power BI

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SQL Complete Video Course (With 3 Projects)

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Python Complete Course (With 3 Projects)

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Microsoft Fabric Complete Course

(With Projects)

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Data Analyst Complete Material (Edition 2026)

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Power BI Project Video Course – 22 Unique Projects Across Multiple Domains

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Power BI Material - 2026 Edition - PDF Notes, Cheat Sheets, PPTs, QnA (all Levels), Notes, Interview Ready Notes, Etc

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SQL Material - 2026 Edition - PDF Notes, Cheat Sheets, PPTs, QnA (all Levels), Notes, Interview Ready Notes, Etc

Course Preview/ Demo - https://youtu.be/6cvFk-VuKHo

Created by: Swapnjeet S

Founder – Data Tutorials YouTube Channel (240K+ Subscribers)

Lead Data Analyst | 12+ Years of Industry Experience

Imp - Sequence to Learn Course -

1. SQL + Projects
2. Power BI + Projects
3. Python Course + Projects
4. Microsoft Fabric + Projects
5. Data Analyst Complete Material for Interview Prep

This all-in-one Data Analyst bundle is designed to take you from beginner to industry-ready professional using the most in-demand tools Microsoft Fabric, Power BI and SQL.

Whether you are a student, working professional, career switcher, or aspiring Data Analyst / Data Engineer, this structured learning path will help you master concepts, build strong projects, and crack interviews confidently.

Detailed Syllabus

https://docs.google.com/document/d/1Ru6G6LmpgtOj87jGA4dZf3D20AQ8PWmgir5UfV_-ZpE/edit?usp=sharing

https://docs.google.com/document/d/1EKoUs5yZuPFR0K8Ppd1s8Pig_pSykZYFcvlikEJQ5Zk/edit?usp=sharing

https://docs.google.com/document/d/1Gjz0J91hDs20E61UHrbGXCEoD_FmNK11HalUxcZbo1k/edit?usp=sharing

https://docs.google.com/document/d/1c1l6QOurI7bJDVXnclj-SZPf65B1mCS_mb3_yAwq4fQ/edit?usp=sharing

Python Course Curriculum:

Module 1: Python Introduction

Module 2: Getting Started

Module 3: Data Types

Module 4: Operators

Module 5: Strings

Module 6: Text Standardization

Module 7: f-Strings

Module 8: Conditional Statements

Module 9: Loops

Module 10: Functions

Module 11: NumPy

Module 12: NumPy Operations

Module 13: NumPy Boolean Indexing and Filtering

Module 14: NumPy Statistical Functions

Module 15: NumPy Searching and Sorting

Module 16: Pandas

Module 17: Pandas Reading CSV and Excel Files

Module 18: Pandas Initial Data Checks

Module 19: Pandas Filtering

Module 20: Pandas Sorting Data

Module 21: Pandas Adding, Renaming and Deleting Columns

Module 22: Pandas Data Cleaning

Module 23: Pandas Statistical Functions

Module 24: Pandas GroupBy

Module 25: Pandas Merge and Joins

Module 26: Matplotlib

Module 27: Matplotlib Line Chart

Module 28: Matplotlib Bar Chart

Module 29: Matplotlib Scatter Plot and Histogram

Module 30: Matplotlib Pie Chart

Module 31: Seaborn

Module 32: Projects

Microsoft Fabric Curriculum:

Module 1: Introduction

Module 2: Creating Azure & Fabric Account

Module 3: Hierarchy in Fabric

Module 4: Fabric Interface

Module 5: Lakehouse

Module 6: Data Factory

Module 7: Data Pipeine_Copy Data Activity

Module 8: SQL Server Integration

Module 9: Data Load Behaviour

Module 10: Data Pipeline_Activities

Module 11: DataFlow Gen 2

Module 12: Warehouse

Module 13: Power BI Integration

Module 14: Data Engineering - Spark

Module 15: Projects

SQL CURRICULUM:

Module 1: Introduction to SQL

Module 2: Creating Database

Module 3: Creating Table

Module 4: Data Types and Constraints

Module 5: DDL Commands

Module 6: DQL Commands

Module 7: Operators

Module 8: DQL – LIMIT, ORDER BY, OFFSET, GROUP BY & HAVING

Module 9: Aggregate Functions

Module 10: Primary & Foreign Key

Module 11: JOINS

Module 12: Subquery

Module 13: Window Functions

Module 14: CTE’s

Module 15: Text Functions

Module 16: Numeric Functions

Module 17: Control Flow Functions

Module 18: Date & Time Functions

Module 19: Views

Module 20: Scenario-Based Interview QnA

Module 21: SQL Complete Material

Module 22: SQL Projects

POWER BI CURRICULUM:

Module 1: Power BI Fundamentals & Overview

Module 2: Data Import & Connectivity

Module 3: Import Mode vs Direct Query Mode

Module 4: Data Types, Field Properties & Summarization

Module 5: Power BI File Formats & Templates

Module 6: Hierarchies, Drill Down & Drill Up

Module 7: Data Visualization & Charts

Module 8: Sorting Techniques in Power BI

Module 9: Filters & Interactivity

Module 10: Slicers & User Controls

Module 11: Groups & Bins

Module 12: Parameters & What-If Analysis

Module 13: Data Cleaning & Transformation (Power Query)

Module 14: Data Modeling & Relationships

Module 15: DAX Fundamentals

Module 16: DAX – Aggregate Functions

Module 17: DAX – Logical Functions

Module 18: DAX – Date & Time Functions

Module 19: DAX – Time Intelligence

Module 20: DAX – Filter Functions

Module 21: DAX – Text Functions

Module 22: Visual Calculations in Power BI

Module 23: Power BI Service & Deployment

Module 24: AI & Advanced Analytics in Power BI

Module 25: Claude AI in Power BI (Complete setup and Real time Analysis)

Module 26: Real-World Projects & Case Studies

Module 27: Important Power BI Handy Notes

Module 28: Interview Questions & Answers (All Levels)

Power BI Projects Included (22 Highly Practical Use Cases)

1. Bank Loan Analysis (Finance)

2. Amazon Sales Dashboard (E-Commerce)

3. Call Center Analytics (Operations/Marketing)

4. Adidas Sales Performance (Retail & Marketing)

5. Car Sales Dashboard (Automotive)

6. Electric Vehicle Insights (EV / Manufacturing)

7. HR Analytics Dashboard (Human Resources)

8. Pizza Sales Dashboard (Food & Service)

9. Ecommerce Sales Analysis (Supply Chain)

10. IPL Analysis (Sports Analytics)

11. Road Accident Report (Transport & Safety)

12. Blinkit Analysis (Quick Commerce)

13. India General Elections Results (Political Data Analytics)

14. Hospital ER Performance (Healthcare)

15. Spotify Music Analysis (Entertainment Streaming)

16. Uber Trip Analysis (Mobility & Ride-hailing)

17. Shopify Funnel Report (Digital Commerce)

18. IPL Advanced Analysis 2008–2025 (Big Data Sports)

19. Sales Performance & Target Report (Corporate Analytics)

20. Insurance Risk & Claims Analytics + Meta Ads (Insurance & Digital Marketing)

Why This Package?

1. Learn with Swapnjeet S — Founder of the Data Tutorials YouTube Channel and Lead Data Analyst with 11+ years of experience.
2. Develop skills in Power BI, SQL, Python, and Microsoft Fabric through a structured learning path.
3. Understand how these tools support different stages of the data workflow.
4. Practice with datasets, business scenarios, and end-to-end projects.
5. Build a stronger technical foundation for analytics, BI, and data engineering career paths.
6. Learn at your own pace, progressing from fundamentals to practical applications.

How This Package Is Taught

1. Step-by-step explanations with practical demonstrations.
2. Concepts explained through datasets and relevant examples.
3. Clear explanations of why, when, and how to use the features covered.
4. Guided practice in data preparation, analysis, reporting, and pipeline development.
5. Project-based learning to help you apply concepts beyond individual lessons.

What You Will Learn?

1. Power BI: Transform data, build data models, write DAX calculations, and create interactive dashboards.
2. SQL: Retrieve, filter, summarize, and combine data using queries, joins, aggregations, and window functions.
3. Python Fundamentals: Work with variables, data types, strings, conditions, loops, and functions.
4. NumPy and Pandas: Perform numerical operations, clean datasets, handle missing values, group records, and merge data.
5. Matplotlib and Seaborn: Create charts, analyze trends, explore distributions, and visualize correlations.
6. Microsoft Fabric: Understand the platform and work with OneLake, Lakehouse, Warehouse, and Shortcuts.
7. Data Pipelines: Use Data Factory activities to move data and build ETL and ELT workflows.
8. Dataflow Gen2: Prepare, clean, and transform data.
9. Spark and PySpark: Use notebooks for data processing and cleaning.
10. Fabric and Power BI: Connect Fabric semantic models with Power BI for reporting.
11. Projects: Apply your skills through end-to-end projects and business scenarios.

Who This Package Is For?

1. Beginners and students looking for a structured starting point in data.
2. Aspiring data analysts who want to build skills across multiple tools.
3. Excel users ready to expand into SQL, Python, and Power BI.
4. Power BI and Tableau developers looking to strengthen their data preparation and engineering skills.
5. SQL and ETL professionals who want to explore Python and Microsoft Fabric.
6. Working professionals preparing to take on broader responsibilities in analytics and reporting.

What You Can Gain?

1. Greater confidence working with messy data and multiple data sources.
2. Practical experience choosing tools for different analysis and reporting tasks.
3. A clearer understanding of the journey from raw data to dashboards and insights.
4. Project experience you can build on and discuss in interviews.

📞 For Support or Queries

📧 Email: [email protected]

📱 WhatsApp: +91 9579005495