CourseVerdict

Associate Data Scientist in Python vs Machine Learning Engineer Nanodegree

Same Bayesian formula, same rubric — so the difference in scores reflects the difference in the courses, not the difference in how we evaluated them.

DataCamp · AI & ML Courses

Associate Data Scientist in Python

3.8/ 5 · 30 opinions
20 positive7 neutral3 negative/ 30 total

Udacity · AI & ML Courses

Machine Learning Engineer Nanodegree

3.8/ 5 · 32 opinions
17 positive8 neutral7 negative/ 32 total

Per-criterion

Content quality3.9 / 5

23 courses are logically sequenced from Python basics through scikit-learn modeling, and the introductory material is genuinely well designed. Reviewers flag repetition between short videos and exercises, and that theory and methodology are treated as secondary to mechanics.

Instructor3.6 / 5

DataCamp uses a specialist instructor per course rather than one host, so presentation is clean but uneven — some instructors are gifted teachers, others are experts who simply present. There is no live instructor or cohort, which leaves some learners wanting guidance.

Value for money3.9 / 5

At roughly $25/month billed annually the subscription unlocks 670+ courses, not just this track, so the break-even is only a handful of courses a year. The monthly plan is poor value by comparison, and the completion certificate carries limited standalone weight with employers.

Support3.3 / 5

The in-browser sandbox removes all setup friction, but support is self-directed: no live instruction, no cohorts, no real-time instructor Q&A. Self-motivated learners cope; those who get stuck have little to fall back on beyond asynchronous help.

Real-world use3.7 / 5

Guided projects use real datasets (housing prices, insurance claims, LA crime, penguin clustering) and build a portfolio. But fill-in-the-blank exercises do not fully build independent coding muscle, and reviewers warn you will not be a job-ready data scientist on the track alone.

Content quality3.8 / 5

Reviewers consistently praise the project curation and AWS SageMaker coverage, but the deep learning section is widely flagged as too short and the lectures lean engineering-first rather than theory-first.

Instructor3.9 / 5

Instructor quality on individual lessons is strong (clear videos, mix of Jupyter notebooks and text), but the program has many authors and no single pedagogical voice across the four-course track.

Value for money3.4 / 5

The biggest drag on the score. Monthly subscription at $249-399 makes the total cost roughly $800-1500+, and reviewers consistently compare it unfavourably to cheaper Coursera, Georgia Tech OMSCS or fast.ai alternatives.

Support4.1 / 5

Mentor-graded project reviews are the most praised feature across the entire sample. Multiple reviewers report personalised written feedback within 30-45 minutes and treat this as the main differentiator vs MOOCs.

Real-world use3.8 / 5

Projects are real and end-to-end (SageMaker deployment, sentiment analysis, capstone) which transfers better than passive video courses, but reviewers flag heavy use of boilerplate code as a brake on independent skill-building.

Scoring methodology applies identically to every course on the site — see the formula.