MDRSS/learning/courses-roadmaps-and-reference/card #901117

180-Day Free Roadmap to Become a Job-Ready Data Analyst

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This roadmap is designed for aspirants with zero experience , focusing on free learning paths , projects , interview prep , and tools that are widely accepted in the industry. Use it as a repeatable review, validation or hardening pass.

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180-Day Free Roadmap to Become a Job-Ready Data Analyst

This roadmap is designed for aspirants with zero experience , focusing on free learning paths , projects , interview prep , and tools that are widely accepted in the industry. Use it as a repeatable review, validation or hardening pass.

Editorial note: curated source snapshot published by Collider.club under the MIT License. Source attribution is preserved in the front matter.

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📚 180-Day Free Roadmap to Become a Job-Ready Data Analyst

This roadmap is designed for aspirants with zero experience, focusing on free learning paths, projects, interview prep, and tools that are widely accepted in the industry.

🎯 GOAL:

To become a job-ready Data Analyst (Entry-Level) within 6 months using only free resources.

🔧 TOOLS & SKILLS YOU WILL MASTER:

Tool Description
SQL Querying databases, joins, aggregations
Python Pandas, NumPy, Matplotlib, Seaborn
Excel Pivot tables, charts, functions
Tableau Public Dashboards, visual storytelling
Power BI Interactive reports, DAX
Git/GitHub Version control, portfolio building

✅ PHASE-WISE ROADMAP (Free Resources Only)

Phase Duration Focus Area Goals
Phase 1 Day 1–30 Basics + SQL + Excel Learn SQL, Excel, and basics of data analysis
Phase 2 Day 31–60 Python + Stats Learn Python, Pandas, basic stats
Phase 3 Day 61–90 Visualization + EDA Master visualization tools (Tableau/Power BI), EDA
Phase 4 Day 91–120 Projects + GitHub Build 3–5 real-world projects
Phase 5 Day 121–150 Interview Prep DSA (SQL, Python), MCQs, Case Studies
Phase 6 Day 151–180 Mock Interviews + Hackathons Final polish, mock interviews, hackathons

🔢 DAY-BY-DAY PLAN (FREE RESOURCES ONLY)

🟩 PHASE 1: BASICS + SQL + EXCEL (Day 1 – Day 30)

Day Topic Activities Free Resources
1-3 Intro to DA What is DA? Roles, Responsibilities Google Data Analytics Certificate - Free
4-7 Excel Basics VLOOKUP, INDEX-MATCH, Pivot Tables Excel Exposure, YouTube Tutorials
8-10 Intermediate Excel Charts, Conditional Formatting Same as above
11-15 SQL Basics SELECT, WHERE, GROUP BY, ORDER BY Mode SQL Tutorial, W3Schools SQL
16-20 SQL Joins & Subqueries INNER JOIN, LEFT JOIN, Nested Queries Mode SQL, LeetCode Easy
21-25 SQL Aggregations & Window Functions SUM, AVG, COUNT, RANK(), ROW_NUMBER() Mode SQL, HackerRank
26-30 Practice SQL + Excel Solve 20+ SQL problems, build dashboard in Excel LeetCode, HackerRank, Kaggle datasets

🟦 PHASE 2: PYTHON + STATISTICS (Day 31 – Day 60)

Day Topic Activities Free Resources
31-35 Python Basics Variables, Loops, Functions Python for Everybody - Coursera
36-40 Numpy & Pandas Arrays, Series, DataFrame Kaggle Python Course
41-45 Data Cleaning Missing Values, Outliers Kaggle Intro to ML
46-50 Descriptive Statistics Mean, Median, Variance, SD Statistics How To
51-55 Inferential Statistics Hypothesis Testing, p-value, CLT Kaggle Intro to Statistics
56-60 Correlation, Regression Scatter Plots, Linear Reg Towards Data Science - Regression

🟨 PHASE 3: VISUALIZATION + EDA (Day 61 – Day 90)

Day Topic Activities Free Resources
61-65 Matplotlib/Seaborn Line, Bar, Pie, Histogram Kaggle Data Visualization
66-70 Tableau Connect Data, Dashboards, Filters Tableau Public
71-75 Power BI Import Data, Reports, DAX Microsoft Learn Power BI
76-80 Exploratory Data Analysis (EDA) Analyze Real Datasets Kaggle EDA Notebooks
81-85 Storytelling with Data Present Insights Visually Storytelling with Data Blog
86-90 Practice Dashboard Create Dashboard using any tool Use Iris, Boston Housing, Superstore dataset

🟥 PHASE 4: PROJECTS + GITHUB (Day 91 – Day 120)

Day Topic Activities Free Resources
91-95 Project 1: Sales Analysis Analyze sales trends, create dashboard Use Walmart/Superstore dataset
96-100 Project 2: Customer Segmentation RFM, Clustering Mall Customers Dataset
101-105 Project 3: HR Attrition Analysis Predict churn, visualize attrition factors IBM HR Dataset
106-110 Project 4: Stock Market Trends Visualize stock trends Yahoo Finance API
111-115 Build GitHub Portfolio Upload all code and dashboards GitHub Pages, README.md
116-120 Resume Building Add Projects, Skills, Certifications Canva Templates (Free), LinkedIn Profile

🟪 PHASE 5: INTERVIEW PREP (Day 121 – Day 150)

Day Topic Activities Free Resources
121-125 SQL Interview Questions Solve 50+ questions LeetCode SQL, StrataScratch
126-130 Python Interview Questions Pandas, Numpy, Strings HackerRank, LeetCode
131-135 MCQs & Aptitude Statistics, Probability, Business Cases Indiabix, PrepInsta
136-140 Case Studies Revenue Drop, User Growth Case in Point PDF (Free), ProductX
141-145 Behavioral Interview STAR Method, Tell me about yourself YouTube videos, Glassdoor
146-150 Mock Interviews Record and analyze responses Pramp, Peer groups, Zoom recordings

🟫 PHASE 6: FINAL POLISH (Day 151 – Day 180)

Day Topic Activities Free Resources
151-155 Hackathon Participation Join Kaggle/Tableau/ML hackathons Kaggle Competitions
156-160 Apply Jobs LinkedIn, Indeed, Glassdoor, AngelList Update resume, apply daily
161-165 Debugging Errors Fix project issues, improve dashboard Review feedback
166-170 Soft Skills & Communication Improve presentation skills TED Talks, Toastmasters (Free online sessions)
171-175 Final Revision All topics, notes, interview prep Your own notes, flashcards
176-180 Full Mock Tests Simulate full interview rounds Take 3 full-length mocks

📌 BONUS: YOUR JOB APPLICATION CHECKLIST

✅ Completed 3–5 projects
✅ GitHub profile with clean documentation
✅ Updated LinkedIn profile with keywords
✅ Tailored resume for each application
✅ Mock interviews recorded and reviewed
✅ Applied to at least 10 jobs per week
✅ Attended at least 2 hackathons
✅ Practiced 100+ SQL & Python questions
✅ Read blogs/books on analytics and communication

📝 TIPS FOR SUCCESS:

  1. Stick to a schedule: Wake up early, set daily goals.
  2. Build a GitHub profile: Showcase all your work.
  3. Document everything: Write blogs on Towards Data Science or Medium.
  4. Apply every day: Don’t wait until Day 180 to start applying.
  5. Track progress: Use Notion or Excel to track your daily tasks.

About Collider.club

This card belongs to the curated knowledge base of Collider.club — a closed business club for entrepreneurs, engineers, investors and domain experts building projects for international markets. Members work across DeFi, AI/ML, FinTech, Web3, banking, hardware and venture capital, and the club runs closed sessions on high-margin niches with anonymous speakers.

  • Club: https://collider.club
  • Collection: Collider.club curated card library (mdrss-card/v2)
  • Maintainer: Collider.club editorial team

License

MIT License — Copyright (c) 2026 Collider.club. Full text: LICENSE · https://opensource.org/licenses/MIT

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