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IBM Data Science Professional Certificate

4.6(102,000)·950K enrolled·Updated March 2025
Beginner 110 hours English Professional CertificateFREE
Editor's Pick
The most comprehensive beginner-friendly data science path. 10 courses, real IBM tools, no prior experience needed.

What you'll learn

Use Python, SQL, and Jupyter for data work
Clean, analyse and visualise data with pandas and matplotlib
Build ML models with scikit-learn
Work with relational databases using SQL
Tell a data story with dashboards in Cognos and IBM tools
Complete a capstone using real-world data
Earn an IBM digital badge alongside the certificate

This course includes

110h
On-demand video
200+
Readings
40+
Hands-on labs
30+
Graded quizzes
Yes
Certificate + badge
Comparison · LBS

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Syllabus· 6 courses · 20+ lessons

Expand all →
  • Defining data science and the data scientist roleVideo · 20 min
  • Topics and algorithms in data scienceReading · 25 min
  • Day in the life of a data scientistVideo · 18 min
  • Languages: Python, R, SQL, ScalaVideo · 25 min
  • Jupyter Notebooks and JupyterLabLab · 60 min
  • Git and GitHub basicsLab · 45 min
  • IBM Watson StudioLab · 60 min
  • Python basics: types, expressions, variablesLab · 90 min
  • Working with data in Python (lists, dicts)Lab · 75 min
  • Working with NumPy arraysLab · 60 min
  • APIs, web scraping, and working with filesProject · 2 hours
  • Basic SELECT, WHERE, GROUP BYLab · 90 min
  • Joins and subqueriesLab · 75 min
  • Accessing databases from PythonLab · 60 min
  • Importing and cleaning dataLab · 90 min
  • Exploratory data analysis with pandasProject · 2 hours
  • Model development and evaluationLab · 75 min
  • Regression, classification, clusteringVideo · 90 min
  • Recommender systemsLab · 60 min
  • Applied data science capstoneProject · 10 hours

Instructor

IB
IBM Skills Network Team
IBM Skills Network · Data Science instructors
7.5M learners90+ courses 4.6 instructor rating

The IBM Skills Network has trained millions of learners across Coursera and edX. This Professional Certificate is built and maintained by IBM data scientists including Romeo Kienzler, Joseph Santarcangelo and Aije Egwaikhide, drawing on IBM's real-world consulting experience.

Requirements

  • No prior experience required
  • A computer with internet access
  • Free IBM Cloud account (provided)
  • Roughly 4–6 hours per week for 6–11 months

Who this course is for

  • Career switchers entering data science
  • Recent graduates building a job-ready portfolio
  • Analysts moving into more technical roles
  • Anyone who wants an IBM-branded credential

About this provider

C
Coursera
University-backed online learning platform · 142M learners · 7,000+ courses
4.6 trust score·Refund within 14 days
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Frequently asked questions

IBM goes deeper on Python and machine learning; Google focuses on spreadsheets, SQL and Tableau. Pick IBM if you want to become a data scientist; pick Google if you want a data analyst role.
Yes — IBM digital badges are recognised on LinkedIn and verifiable via Credly. They are not equivalent to a degree but they are a credible resume signal for entry-level roles.
IBM says 11 months at 4 hours/week. Most full-time learners finish in 3–4 months. The capstone alone takes 10–15 hours.
Yes — every course in the certificate is enrollable on its own and earns its own Coursera completion certificate.
Audit all 10 courses for free. You lose graded labs and the IBM badge but keep 100% of the lecture content. Combine with Kaggle's free micro-courses for hands-on practice.
Free
Cert $49/mo
View on Coursera