Data Scientist Roadmap
Recommended Reading
Phase 1:Python & SQL
beginner4 weeksPython Fundamentals
Variables, functions, loops, data structures, and file I/O.
beginner4 weeksSQL
SELECT, WHERE, JOIN, GROUP BY, subqueries, and window functions.
beginner1 weekGit Basics
Version control for code and notebooks.
Phase 2:Data Analysis
intermediate2 weeksNumPy
Numerical computing, array operations, and mathematical functions.
intermediate4 weekspandas
Load, clean, transform, and analyze structured data with DataFrames.
intermediate2 weeksData Visualization
Communicate insights with matplotlib, seaborn, and plotly.
intermediate4 weeksStatistics
Descriptive statistics, probability distributions, hypothesis testing, and p-values.
Phase 3:Machine Learning
intermediate4 weeksScikit-learn
Classification, regression, clustering, and model evaluation with sklearn.
intermediate2 weeksFeature Engineering
Transform raw data into informative features that improve model performance.
intermediate2 weeksModel Evaluation
Cross-validation, confusion matrices, ROC curves, and avoiding data leakage.
advanced6 weeksDeep Learning
Neural networks, backpropagation, and building models with TensorFlow or PyTorch.
Phase 4:Professional Data Science
advanced3 weeksMLOps Basics
Deploy models to production, monitor drift, and version datasets.
intermediate2 weeksCommunication
Write reports, build dashboards, and present findings to non-technical stakeholders.
advanced8 weeksPortfolio Projects
Build 2-3 end-to-end data science projects with real datasets.
Next steps
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Languages in this roadmap
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