SQL · Track 1 · 5 problems
SQL Foundations
The eight-minute questions that open a screen: filtered aggregation, product joins, and the org-tree self-join.
0/5
solved
Data Analyst · BI Analyst · Analytics Engineer · Data Engineer · Data Scientist
SQL warehouse sets and Python (NumPy / PyTorch) sets. Filter by the role you are practicing for.
SQL · Track 1 · 5 problems
The eight-minute questions that open a screen: filtered aggregation, product joins, and the org-tree self-join.
0/5
solved
Data Analyst · BI Analyst · Analytics Engineer · Data Engineer · Data Scientist
SQL · Track 2 · 4 problems
The everyday warehouse screen: anti-joins, rates, daily grain, and a customer dimension that survives LEFT JOIN.
0/4
solved
Analytics Engineer · Data Engineer · BI Analyst · Data Analyst · Data Architect
SQL · Track 3 · 4 problems
Running totals, trailing averages, growth, and share of total — every question here turns on the frame.
0/4
solved
Data Engineer · Analytics Engineer · Data Scientist · Data Analyst
SQL · Track 4 · 3 problems
Latest row per key, top-N per group, and the department-average trap. ROW_NUMBER earns its keep here.
0/3
solved
Data Engineer · Analytics Engineer · BI Analyst · Data Scientist
SQL · Track 5 · 11 problems
Reconciliation, JSON payloads, pivots, median without percentiles, and sessionization. The back half of the loop.
0/11
solved
Data Engineer · ML Engineer · MLOps Engineer · AI Engineer · Data Architect
Python · Track 6 · 6 problems
The pad that opens an analyst or DE screen: means, activations, clip, flatten. Same tests in NumPy, Python, and PyTorch.
0/6
solved
Data Analyst · Data Engineer · Analytics Engineer · Data Scientist · Data Architect
Python · Track 7 · 7 problems
NaN-aware means, variance, median, z-score, and a weighted KPI. Spreadsheet instincts, code you can defend.
0/7
solved
Data Analyst · BI Analyst · Analytics Engineer · Data Engineer
Python · Track 8 · 7 problems
Losses and scores a scientist or ML engineer must implement without sklearn: MSE, R², precision, recall, F1, BCE.
0/7
solved
Data Scientist · ML Engineer · MLOps Engineer · AI Engineer
Python · Track 9 · 8 problems
Softmax, log-softmax, cosine, top-k, KL, Huber — the DS/MLE follow-up after the metric pad.
0/8
solved
Data Scientist · ML Engineer · MLOps Engineer · AI Engineer