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Python for Data Science

A hands-on Python foundations course for aspiring data scientists. It moves from variables, control flow, and functions into files, imports, debugging, pandas, and visualization, with notebook-based portfolio work throughout.

4 weeks 12 lessons 2,847 enrolled 4.9 rating

Live access status

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Who This Is For

  • Beginners who need real Python fluency before moving into analytics or machine learning.
  • Learners who want to work with real datasets instead of staying at tutorial level.
  • Career switchers building their first portfolio-ready technical work.

How You'll Train

  • Learn Python through data tasks, not only through abstract exercises.
  • Clean, reshape, and visualize real tabular data using pandas and NumPy workflows.
  • Build confidence through short lessons, labs, debugging practice, and notebook-based mini projects.

Technologies

PythonPandasNumPyMatplotlibSeaborn

What You Leave With

  • Write practical Python for analytical work.
  • Use pandas and NumPy to inspect, clean, and transform datasets.
  • Produce clearer visual and exploratory outputs that can support a portfolio.

Portfolio Outcome

A real-data notebook that demonstrates Python, wrangling, and visualization skills.

Curriculum

Python Setup, Jupyter Workflow, and Data TypesLecture
55 min
Control Flow, Functions, and Collections LabLab
95 min
Syntax and Core Structures QuizQuiz
20 min

Instructor

I
IODS Faculty
Curriculum delivered by practising data & ML engineers