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Track 02
Perform high-performance numerical computations with NumPy, exploratory data analysis, and capstone modeling.
Every module in the order you'll work through it. Each one is practised inside the portal and marked as you go.
Core Python for data science: loops, strings, lists, dictionaries and logic building.
57 challenges: array vs list, creating arrays, properties, indexing, slicing, sorting & searching, statistics, and reshaping.
157 challenges: file I/O, exploration, selection, filtering, sorting, missing values, duplicates, strings and statistics.
53 challenges: line/bar/scatter/pie charts, histograms, titles & legends, subplots, styling and saving figures.
Statistical plots: histograms, box plots, heatmaps and pair plots.
SELECT, WHERE filtering, GROUP BY aggregation and JOINs across relational tables.
45 challenges: central tendency, min/max/range, variance & standard deviation, percentiles & quartiles, frequency, correlation & covariance, and probability.
Train and evaluate regression, classification and clustering models with scikit-learn.
Neural networks: layers, activations, training loops and model tuning.
Text cleaning, tokenization, vectorization and sentiment classification.
Read and transform images, extract features, and build an image classifier.
Serialize a trained model, serve it behind an API, and ship a working demo app.
Work in notebooks: run cells, document analysis with Markdown, and export the finished notebook.
Find datasets and competitions, submit notebooks, and read a leaderboard on Kaggle.
46 tasks across eight sections: setup, starting a repo, the everyday add-commit-push workflow, GitHub remotes, branching, notebooks and datasets, collaboration, and fixing mistakes.
14 topic quizzes, NumPy through Model Deployment, plus the full Python, SQL and Pandas quizzes. Locked once answered.
All hands-on projects in one place: Python, SQL, NumPy, Pandas data cleaning, and the analysis capstone.
Master SQL relational queries, database joins, aggregations, and Pandas data cleaning.
Sharpen keyboard speed and accuracy with live WPM tracking and detailed performance analytics.
Build core programming logic with C: basics, input and output, variables, data types, operators, conditionals, loops, arrays, strings, functions, maths, and advanced searching, sorting & matrix programs — sub-track by sub-track.