Free for students — data science, MBA, research, engineering

Learn Data Science
by Doing. Not by Watching.

Drop any CSV. See SQL, Python, statistical tests, and ML — explained at every step. Free for students.

✓ Free tier, no card✓ SQL + Python on every result✓ Works in browser

Why learning data science is hard

Three barriers every student hits. WorkLiq removes all three.

SQL syntax errors stop you cold before you even see results

Ask in plain English — see the SQL generated and learn from it

Statistical concepts like p-values feel abstract in textbooks

Run a t-test on your own data and read the result in plain English

Tableau costs $70/mo, Jupyter takes hours to set up

Free tier. Works in browser. Upload and analyze in under 60 seconds

How you actually learn

Every answer shows the code. Copy it. Modify it. Learn it.

Ask “show top products by revenue” → get this:

Top Products by Revenue138ms · rule engine
SQL— copied into your notebook
SELECT product,
  SUM(revenue) AS total
FROM df
GROUP BY product
ORDER BY total DESC
LIMIT 10
Python— run in Jupyter as-is
result = (
  df
  .groupby('product')['revenue']
  .sum()
  .sort_values(ascending=False)
  .head(10)
  .reset_index()
)

What WorkLiq gives students

Four things your university tool probably doesn't have

💻

Free Tier — No Credit Card

1 dataset, 50 queries per month, full SQL + Python output, all chart types. Enough for your entire semester project without spending a rupee.

📄

SQL + Python Side by Side

Every answer shows the SQL query that ran and the equivalent pandas code. Copy it, modify it, run it in your own Jupyter notebook — that is how you actually learn.

🧪

Hypothesis Tests with Plain English

t-test, ANOVA, chi-square, Shapiro-Wilk, Pearson correlation — all with a plain English interpretation at grade-10 reading level. Know what p < 0.05 means for your data.

📓

Reproducible Notebooks

Cell-based notebook interface. Mix queries, markdown explanations, and outputs. Export as JSON (nbformat-compatible) or PDF. Submit your analysis as a notebook.

Student story

Kavya Nair, MBA (Analytics), IIM Kozhikode

Final-year student — dissertation on retail pricing strategy

"I had a 50,000-row dataset for my dissertation and no idea where to start. WorkLiq ran a health check, flagged 3 data quality issues, and suggested 5 questions to ask. I ran an ANOVA on pricing segments and got the p-value with an explanation I could actually put in my report. The SQL and pandas code meant my professor could verify every number. I finished my analysis chapter in one afternoon instead of two weeks."

2 wks

analysis cut to one afternoon

50k

rows analyzed with free plan

ANOVA

ran with one click, zero code

Start with your assignment dataset

Upload any CSV. See SQL + Python on every result. Run statistical tests. Free tier, no credit card, no setup.

Try with sample data →

Free tier: 1 dataset, 50 queries/month. No card required.

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