📊 Data Scientist

Fast-track roadmap: from spreadsheets to models that drive decisions.

Community / Career Guidance / Data Scientist

Who this is for

Curious problem-solvers who enjoy finding patterns in data and explaining them. Comfort with basic maths helps - the rest we build step by step.

Phase 1 · Foundations

Python for data

  • Learn Python fundamentals and clean coding habits.
  • Master NumPy and pandas for working with tables of data.
  • Load, filter, and summarise real datasets.
PythonNumPypandas
Phase 2 · Understanding Data

Statistics and exploration

  • Learn descriptive statistics, distributions, and probability basics.
  • Clean messy data and handle missing values.
  • Run exploratory analysis and visualise findings.
StatisticsData cleaningMatplotlib
Phase 3 · Machine Learning

Models that predict and group

  • Build regression and classification models with scikit-learn.
  • Learn clustering to find hidden segments.
  • Evaluate models properly with train/test splits and metrics.
scikit-learnRegressionClustering
Phase 4 · Communicating Insight

SQL and storytelling

  • Query data at the source with SQL.
  • Build clear dashboards and charts for non-technical audiences.
  • Turn results into a recommendation, not just a number.
SQLDashboardsStorytelling
Phase 5 · Job-Ready

Portfolio and competitions

  • Complete 2-3 end-to-end projects on real datasets.
  • Enter a Kaggle competition to benchmark yourself.
  • Publish notebooks with clear explanations of your thinking.
PortfolioKaggleNotebooks

Learn it with Learn2Pro

The Python AI Bootcamp covers Phases 1-3, and the Python Masterclass strengthens your coding base.

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