Data Science & ML
Python, statistics, data cleaning, visualisation, supervised and unsupervised learning and model evaluation.
What you are tested on
- Python, NumPy and pandas
- Statistics and probability
- Data cleaning and visualisation
- Regression, classification and clustering
- Model evaluation
Practice problems (16 in total)
- Min-Max Normalize a Feature ColumnEasy
- Compute Precision, Recall, F1Medium
- Simple Moving AverageEasy
- Mean, Median and ModeEasy
- Population Standard DeviationEasy
- Z-Score OutliersMedium
- Confusion Matrix and AccuracyEasy
- One-Hot EncodingEasy
- Simple Linear RegressionMedium
- Cosine SimilarityEasy
- k-Nearest Neighbours ClassifierMedium
- MAE and RMSEEasy
Roadmaps
Data Science & Machine Learning Roadmap
Statistics-first path to building and honestly evaluating your first models.
MLOps and Model Deployment Roadmap
Take a trained model to production: packaging, serving, pipelines, monitoring and retraining.
Data Engineering Roadmap: Pipelines, Spark and dbt
Learn to move, clean and model data reliably: SQL, Python, batch and streaming, warehouses and dbt.
Data Literacy and Analytics Roadmap
The skill every role is starting to expect: ask a question, get the data, and show an answer people can trust.
Data Analyst After B.Tech
The fastest route into data roles: SQL, spreadsheets, visualisation and business storytelling.
Machine Learning Engineer Roadmap
From maths and Python to deploying models that real products depend on.
How your Data Science & ML rating works
You start at 1200. Each timed, rated test moves your Data Science & ML rating up or down, the way chess ratings move. Recruiters see the number and the band (Beginner, Intermediate, Advanced or Expert), so they can judge your skill before reading a résumé. See a sample profile.
Questions about Data Science & ML
What should a fresher data analyst know?
SQL, Excel or Python with pandas, basic statistics and how to explain a chart to a non-technical person.
Is a rating useful for ML roles?
It shows you can answer timed questions on fundamentals; pair it with projects and notebooks.