Data Analyst Learning Path

  • BeginnerLevel

  • 6052+Students Enrolled

  • 12 Hrs Duration

  • 4.7Average Rating

About this Course

  • Understand the analyst toolkit in a Free Data Analyst Learning Path: Excel for quick analysis, SQL for querying, Power BI/Tableau, plus Python-Pandas for automation and insights.
  • Practice on real datasets and cases to clean, transform, visualize, and present findings that drive decisions. Build a portfolio project in a data analysis learning path online.
  • Go from zero to job-ready with interview prep, resume building, and an AI Agent project mirroring workflows—ideal for a data analyst qualification and online certificate readiness.
  • Get beginner-friendly lessons, cheat sheets, and step-by-step labs that simplify tough topics—apply skills fast in a data analyst course online and move toward certification.

Learning Outcomes

Analyze data with skill

Clean, explore, and draw insights that answer real business questions.

Build powerful dashboards

Model data, design KPIs, present trends in interactive BI reports.

Automate with Python

Use Pandas and scripts to speed up analysis and repeatable workflows.

Who Should Enroll

  • Beginners and career switchers who want a structured, practical roadmap to land their first Data Analyst role.
  • Students and fresh graduates aiming to build a strong foundation in Excel, SQL, BI tools, and Python for analytics.
  • Working professionals in non-tech roles who need data skills to make better decisions and grow in their careers.
  • Aspiring analysts preparing for interviews who want projects, a polished resume, and portfolio-ready work.

Course Curriculum

This learning path bundles ten beginner-friendly courses covering Excel, SQL, Power BI, Tableau, Python, Pandas, EDA with GenAI, interview and resume prep, and a final AI Agent project to simulate real analyst work.

toolstoolstools

  1. 1. Introduction & Basics

  2. 2. Productivity & Shortcuts

  3. 3. Power Query

  4. 4. Functions & Charts

  5. 5. Excel Formulas

  6. 6. Data Structure Query

  1. 1. Introduction to Databases

  2. 2. A Beginners Guide to SQL

  1. 1. Introduction to Power BI

  2. 2. Building An End-to-end Sales Analysis Report in Power BI

  1. 1. Powering Your Decisions with Chart

  2. 2. Tableau in Action: Case Study-Driven Learning

  1. 1. Overview of the Course

  2. 2. Getting Started with Python

  3. 3. Understanding Operators

  4. 4. Variables and Data Types

  5. 5. Conditional Statements

  6. 6. Looping Constructs

  7. 7. Python Functions

  8. 8. Data Structure

  9. 9. Python Lists

  10. 10. Dictionaries

  11. 11. Understanding Standard Libraries in Python

  12. 12. Reading a CSV File in Python

  13. 13. Data Frames and basic operations with Data Frames

  14. 14. Indexing a Data Frame

  15. 15. Data Manipulation and Visualization

  16. 16. Regular Expressions

  17. 17. Cheatsheet for Python

  1. 1. Getting Started with Pandas

  2. 2. Dataset Description

  3. 3. Read & Write Data using Pandas

  4. 4. Pandas Dataframes

  5. 5. Data Exploration using Pandas

  6. 6. Data Manipulation using Pandas

  7. 7. Aggregating data using Pandas

  8. 8. Merging Data using Pandas

  9. 9. Pandas Cheatsheet

  1. 1. EDA Essentials

  1. 1. Can You Really Control an Interview?

  2. 2. Cracking Project-Based Interviews

  1. 1. How the Ideal Resume Looks Like

  2. 2. Resume Building for Data Science Roles

  3. 3. Building a resume from scratch using Rezi.ai

  1. 1. Let's Start Building Data Analyst AI Agent

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Srimugunthan Dhandapani

Technical Lead, WellsFargo

Srimugunthan brings over 12 years of experience in data analytics, specializing in prediction models, recommender systems, and more. With a background in computer science and an Executive MBA in product management.

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Apoorv Vishnoi

Head - Training, Analytics Vidhya

Apoorv is a seasoned AI professional with over 14 years of experience. He has founded companies, worked at start-ups and mentored start-ups at incubation cells.

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Dhruv Singh

Corporate Trainer, Analytics Vidhya

Dhruv Singh is Microsoft Certified Corporate Trainer with deep expertise in Power BI, Power Platform, SQL Server, and Excel. Currently mentoring learners across 50+ global EdTech platforms as a Data Analytics Instructor.

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Kunal Jain

Founder & CEO, Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

Get this Course Now

With this course you’ll get

  • 12 Hours

    Duration

  • Beginner

    Level

Certificate of completion

Complete the course and pass the final assessment to receive an industry-recognized certificate

  • Industry-Recognized Credential
  • Career Advancement Credential
  • Shareable Achievement
certificate

Frequently Asked Questions

Looking for answers to other questions?

Yes, you will build multiple portfolio ready projects, including a comprehensive capstone dashboard. This hands-on approach in our data analyst course online ensures you gain practical experience to showcase to employers in data analytics.

Consider your organization's ecosystem, data governance needs, and sharing capabilities. This Free Data Analyst Learning Path supports both tools, allowing you to pick what fits your team's skills and career goals in data visualization.

It is traditional exploratory data analysis, including profiling and pattern checks, accelerated by GenAI. The AI suggests hypotheses and charts based on your data, speeding up discovery in this data analyst course online.

No prior coding experience is required. The course begins with Excel and SQL fundamentals, then progresses to Python. Each module includes guided labs with real datasets to build your skills from the ground up.

Yes. While not tied to one exam, the curriculum meets core competencies for a general online data analytics certificate, preparing you for roles that value a data analyst certification online.

Excel works for quick exploration, SQL retrieves database data, and Python/Pandas handles scalable cleaning and complex analysis. Together they form a complete modern data workflow essential for any aspiring data professional.

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