My Skill Lab
Data ScienceBeginner

Data Analyst Career Path: Zero to Job-Ready

The roadmap, the tools, the portfolio and the interview.

Taught by Niraj Thapa · Analytics Lead

What you'll learn

  • Describe the daily work of a data analyst and how it differs from data science and data engineering
  • Map the core skill stack (Excel, SQL, Python, BI tools, statistics) to a realistic learning order
  • Write basic SQL queries that filter, aggregate and join tables to answer a business question
  • Plan and scope three portfolio projects that demonstrate end-to-end analysis
  • Prepare a CV, LinkedIn profile and GitHub that pass recruiter and applicant-tracking screening
  • Answer common data analyst interview questions, including live SQL and case-study formats

About this course

This free data analyst roadmap is for career changers, recent graduates and anyone wondering how to become a data analyst without a degree in statistics. You will learn what a data analyst actually does day to day, which skills employers list most often (Excel, SQL, Python, Power BI and Tableau), and in what order to learn them so you do not waste months. You will plan a three-project portfolio that shows real analysis rather than tutorials, write a CV that passes screening, and prepare for the SQL, case-study and behavioural questions that data analyst interviews rely on. No prerequisites beyond basic computer skills. Whether you are following the Google Data Analytics certificate, studying on your own, or moving from finance, marketing or operations into analytics, this course gives you the structure and the next steps.

Course content

7 lessons
  1. 1What a Data Analyst Actually DoesThe real job behind the title: questions, data, cleaning, analysis and communication.Preview
  2. 2The Skills Map and a Realistic Learning OrderExcel, SQL, Python, statistics and BI tools, sequenced so each skill builds on the last.
  3. 3SQL: The Skill Every Analyst Job Asks ForFilter, aggregate and join tables so you can answer business questions straight from the database.
  4. 4Spreadsheets and Python: Which Tool, WhenWhere Excel shines, where it breaks, and how pandas picks up when data outgrows a sheet.
  5. 5Visualisation and BI ToolsChoose the right chart, avoid common misreads, and publish a dashboard in Power BI or Tableau.
  6. 6Building a Portfolio That Gets InterviewsThree projects that show end-to-end analysis, written up so a hiring manager can judge them in two minutes.
  7. 7Landing the Job: CV, Interviews and the First 90 DaysPass screening, handle SQL and case interviews with confidence, and make a strong start once hired.