Switch from Frontend Engineer to Data Analyst in 9 Weeks

This plan helps you move from frontend engineering to data analysis. Follow each step to build your skills, create real projects, and prepare for data analyst job applications.

  • Weekly Hours: 10
  • Estimated Weeks: 9

Phases

Learn Data Basics

Start with core data analysis concepts, spreadsheet handling, and basic data visualization. Build a foundation for later phases by understanding key tools and simple data tasks.

2 weeks

  • Understand what a data analyst does
  • Learn spreadsheet basics
  • Explore how data is represented
  • Create your first simple charts
  • Spreadsheet navigation
  • Data entry and cleaning
  • Simple data visualization
  • Spreadsheets tutorial
  • Data types guide
  • Chart creation walkthrough
  • Complete one spreadsheet exercise with cleaning task
  • Create and label at least two basic charts

Develop Data Handling Techniques

Practice more data handling tasks: sorting, filtering, summaries, and basic formulas. Learn how to prepare data for analysis in common tools.

2 weeks

  • Sort and filter datasets
  • Summarize data with formulas
  • Fix errors in sample data
  • Use functions to organize data
  • Data sorting and filtering
  • Formula writing
  • Error detection in data
  • Sorting/filtering practice sets
  • Formula practice guides
  • Data error worksheet
  • Sort and summarize a dataset using two functions
  • Prepare a clean dataset ready for analysis

Explore Data Analysis with Coding

Start using basic code to work with data. Learn a language like Python or R, focusing only on the parts needed for analysis and simple charts.

2 weeks

  • Write scripts to load and process data
  • Use code to create charts
  • Clean data with basic code
  • Summarize datasets in code
  • Script writing for data
  • Simple data cleaning with code
  • Basic charting in code
  • Intro to data analysis scripts
  • Sample datasets for practice
  • Basic chart creation code
  • Write a script to load, clean, and plot sample data
  • Share a summary chart with clear labels

Build Portfolio Projects

Complete small projects that show your data analysis skills. Use real or sample data to create reports, summaries, and charts you can share.

2 weeks

  • Design a small data analysis project
  • Write a simple project summary
  • Present findings in easy graphs
  • Practice explaining your work
  • Data storytelling
  • Project documentation
  • Presenting findings
  • Sample project ideas list
  • Project writing template
  • Presentation guide for reports
  • Finish one full, shareable data project
  • Summarize findings in a written or visual report

Prepare for Data Analyst Job Search

Get ready to apply for jobs. Update your resume, practice common interview questions, and learn how to present your data projects.

1 weeks

  • Write a data-focused resume
  • Create a project portfolio
  • Practice interview questions aloud
  • Review a sample job description
  • Resume building
  • Interview practice
  • Portfolio creation
  • Resume guide for analysts
  • Interview question list
  • Portfolio example
  • Finish a draft resume with your data work included
  • Practice answering two common interview questions

Weekly Plan

Week Focus Why Tasks Deliverables
1 Understand data analysis basics and spreadsheets Grasp what data analysts do and learn to handle spreadsheet data. Read about data analyst job duties, Watch spreadsheet tutorial videos, Create and organize a sample spreadsheet, Try making simple bar and pie charts Completed spreadsheet file, Two different basic charts
2 Practice cleaning and visualizing data Strengthen your ability to prepare data for analysis. Download a sample messy dataset, Clean up data using spreadsheet features, Highlight missing or incorrect data, Summarize findings in a short written note Cleaned dataset, Short summary of cleaning steps
3 Learn sorting, filtering, and using formulas These are key steps in most data analysis jobs. Try sorting a dataset by different columns, Use filter to isolate specific entries, Practice formulas like sum and average, Write down how each task changes your data Sorted and filtered spreadsheet, Short description of formula results
4 Summarize and organize data with advanced spreadsheet tools Efficient data handling is an important analyst skill. Use conditional formatting to highlight trends, Create pivot tables for deeper summaries, Try out a few more complex functions, Document your steps Pivot table summary file, Notes on function usage
5 Start with basic coding for data analysis Coding saves time on bigger datasets and is widely used. Install a beginner-friendly code editor, Run a starter script that loads data, Edit the script to make simple changes, Read about common data analysis code features Working script that loads sample data, One code edit with documented change
6 Clean, analyze, and visualize data using code Using code opens more ways to explore data. Write code to remove missing values, Summarize columns with code, Plot a chart using data from your script, Practice fixing a small code error Script that cleans and summarizes data, One coded chart
7 Plan and start your first data analysis project Projects show what you can do in real situations. Pick a project idea from a list, Gather or download a dataset, Write a short project outline, Start exploring your data One project outline, Dataset ready for use
8 Finish project, write summary, and create visuals Completed projects are useful for your job applications. Analyze your dataset fully, Create 2–3 clear charts or graphs, Write a short, clear summary of your results, Prepare slides or a file with your findings Full analysis report with visuals, Project presentation file
9 Polish your job applications and practice interviews Being job-ready is your final step toward your first data role. Update your resume with your project and new skills, Build a simple online or PDF portfolio, Practice speaking about your work aloud, Read and answer sample interview questions Data-focused resume, Answered interview questions

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