Learn data science
by doing, not watching.
Drop any CSV. See the SQL, the Python, statistical tests, and ML — explained at every step. Free for students.
Why learning data science is hard
Three barriers every student hits — WorkLiq removes all three.
SQL syntax errors stop you cold before you ever see a result
Ask in plain English — then read the SQL it generated and learn from it
Concepts like p-values feel abstract in the textbook
Run a real t-test on your own data and read the result in plain English
Tableau costs $70/mo; a Jupyter setup can eat an afternoon
Free tier, runs in the browser — upload and analyze in seconds
How you actually learn
Every answer shows the code. Copy it, change it, learn it.
Ask “show top products by revenue” → get this:
SELECT product, SUM(revenue) AS total FROM df GROUP BY product ORDER BY total DESC LIMIT 10
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, 300 credits per month, full SQL + Python output, and every chart type — enough for a whole semester project without spending a rupee.
SQL + Python, side by side
Every answer shows the SQL that ran and the equivalent pandas code. Copy it, change it, run it in your own notebook — that's how you actually learn.
Hypothesis tests, explained
t-test, ANOVA, chi-square, Shapiro–Wilk, Pearson — each with a plain-English interpretation at a grade-10 reading level, so you know what p < 0.05 means for your data.
Reproducible notebooks
A cell-based notebook: mix queries, markdown, and outputs. Export as JSON (nbformat-compatible) or PDF and submit your analysis as a notebook.
The free tier, in plain numbers
Start with your assignment dataset.
Upload any CSV. See SQL + Python on every result, run real statistical tests. Free tier, no card, no setup.
Try with sample data →Free tier: 1 dataset, 300 credits/month. No card required.