Learn by Source
IBM · on edX

IBM: The Data Science Method

Beginner English Course CertificateFREE
SkillsData scienceMethodologyProblem framingData analysisModelling processDeployment

Is this course right for you?

Our take
Alex Aklson's IBM edX course teaches something most beginners lack: a repeatable method for approaching data-science problems.

Good for: A repeatable methodology for approaching data-science problems.

Skip if: You want hands-on coding or advanced modelling.

Rather than tools or code, it walks a structured process — identifying the real problem, collecting and analysing data, building a model, and interpreting the feedback once it's deployed. That process discipline is what separates data scientists who flail on open-ended problems from those who work methodically, and it's exactly what a newcomer usually doesn't get from a syntax-focused course.

Because it's about method, not implementation, it's the wrong course if you're after actual coding or advanced modelling. Audit it free on edX, with a verified certificate as a paid option and financial assistance available; the certificate documents the learning rather than certifying it. A sound method for framing problems doesn't date (as of 2026).

Comparison · LBS

Compare alternatives for IBM: The Data Science Method

Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
edX
IBM: The Data Science Method
Price
Free
Audit free · earns an IBM digital skill badge (not a verified certificate)
Duration
—
Level
Beginner
Certificate
Course Certificate
Coursera4.6(102,000)
IBM Data Science Professional Certificate
Price
Free
Audit free · Certificate on subscription
Duration
110 hrs
Level
Beginner
Certificate
Professional Certificate
View course →
Google4.7(14,000)
Google Analytics Certification
Price
Free
Completely free, official Google certification
Duration
6 hrs
Level
Beginner
Certificate
Course Certificate
View course →
Google4.7(51,000)
Digital Garage: Fundamentals of Digital Marketing
Price
Free
Completely free · Certified by Google & IAB Europe
Duration
40 hrs
Level
Beginner
Certificate
Course Certificate
View course →
Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.

About this course

Alex Aklson teaches a structured methodology for approaching data science problems: identifying a problem, collecting and analyzing data, building a model, and interpreting feedback after deployment, framed around the six stages of the Cross-Industry Process for Data Mining (CRISP-DM) methodology via a case study.

Browse all Data Science courses Browse all edX courses

Instructor

AA
Alex Aklson
edX instructor

Alex Aklson, Ph.D., is a data scientist at IBM Canada with prior experience designing data-driven healthcare and consulting solutions; he holds a Ph.D. in Biomedical Engineering from the University of Toronto.

Frequently asked questions

No. It is a conceptual course about the process and methodology of data science — how a data scientist approaches a problem from business question to solution — rather than a coding tutorial. You will not be writing much, if any, code here. It complements the hands-on Python and SQL courses in IBM's data-science programs by teaching the disciplined thinking that guides that technical work.

A structured, step-by-step approach to data-science problems: understanding the business problem, framing an analytic approach, collecting and preparing data, modelling, evaluating, deploying, and getting feedback. It mirrors established industry methodologies (in the spirit of CRISP-DM), giving you a repeatable framework so data projects are driven by clear questions and rigour rather than jumping straight to building models.

People learning data science who want to understand how real projects are structured — beginners in IBM's data programs, and analysts or professionals wanting the disciplined process behind the tools. It assumes no coding, so it suits those building conceptual grounding. Experienced data scientists may find it basic; its value is giving newcomers a mental map of the workflow before they dive into technical execution.

It is short — a few hours — as a focused, conceptual course rather than a hands-on program. That brevity makes it an easy way to absorb the data-science workflow, and it sits naturally within the larger IBM data-science certificate, where it provides the methodology backbone that the coding-heavy courses then put into practice.

Yes, you can audit it on Coursera to watch the material at no cost, with graded elements and the certificate behind a subscription. Since it is a concept-focused course rather than hands-on labs, auditing gives you nearly all the value if you just want to understand the data-science method itself.
Free
to audit
Enroll now