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Data Scientist with Python Career Track

4.7(14,800)·180K enrolled·Updated January 2025
Beginner 88 hours English Career Track Certificate

What you'll learn

Write Python for data analysis using pandas and NumPy
Build interactive visualisations with matplotlib and seaborn
Query relational data with SQL from Python
Build and evaluate supervised ML models with scikit-learn
Engineer features and handle missing data
Communicate findings clearly with charts and reports
Pass real-world coding assessments to earn the track certificate

This course includes

88h
Interactive video
300+
In-browser exercises
25
Skill assessments
Yes
Track certificate
Comparison · LBS

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Prices and ratings refreshed daily. We're not affiliated with any single provider.

Syllabus· 6 courses · 23+ lessons

Expand all →
  • Python basicsLab · 60 min
  • Python listsLab · 45 min
  • Functions and packagesLab · 45 min
  • NumPyLab · 60 min
  • Matplotlib basicsLab · 60 min
  • Dictionaries and pandasLab · 60 min
  • Logic, control flow and filteringLab · 45 min
  • Loops and case studyProject · 75 min
  • Transforming DataFramesLab · 60 min
  • Aggregating dataLab · 60 min
  • Slicing and indexingLab · 60 min
  • Creating and visualising DataFramesProject · 60 min
  • Inner, left, right and outer joinsLab · 60 min
  • SELECT, WHERE, GROUP BYLab · 60 min
  • Joining tables in SQLLab · 60 min
  • SQL from PythonLab · 60 min
  • Summary statistics and distributionsLab · 90 min
  • Hypothesis testingLab · 90 min
  • Sampling and bootstrapLab · 90 min
  • Classification and regressionLab · 90 min
  • Fine-tuning modelsLab · 90 min
  • Clustering for dataset explorationLab · 90 min
  • Final case study and assessmentProject · 3 hours

Instructor

HB
Hugo Bowne-Anderson
Lead instructor · former Head of Data Science Evangelism, DataCamp
650K learners12 courses 4.7 instructor rating

Hugo Bowne-Anderson is a data scientist, educator and podcast host (DataFramed). He led data-science evangelism at DataCamp and has taught hundreds of thousands of learners practical Python, statistics and machine learning.

Requirements

  • A DataCamp subscription (about $29/mo annual)
  • No prior Python or stats background
  • A modern web browser — DataCamp runs in-browser
  • 5–8 hours per week for 2–3 months

Who this course is for

  • Beginners who learn best by doing rather than watching
  • Career switchers who want interactive practice
  • Analysts moving into Python
  • Learners preparing for data-science interviews

About this provider

Dc
DataCamp
University-backed online learning platform · 142M learners · 7,000+ courses
4.6 trust score·Refund within 14 days
Browse all DataCamp courses →

Frequently asked questions

DataCamp is interactive and hands-on with short bites; IBM is video-led and broader (including SQL, ML, and a capstone). DataCamp is faster; IBM gives you a stronger resume credential.
For active learners yes — at ~$29/mo unlimited, you can finish multiple tracks. If you only want one course, single-course platforms like Coursera audit may be cheaper.
It is recognised in data circles but is not as strong a signal as Coursera Pro Certs (IBM, Google). Pair with a public portfolio for best effect.
About 88 hours of content + assessments. Most learners finish in 8–12 weeks at 8 hours/week.
Audit the IBM Data Science Cert on Coursera or take Python for Everybody — both are free for content access. You lose the interactive in-browser practice that makes DataCamp special.
$49/mo
or audit free
View on DataCamp