Program profile · official sources

Supervised Machine Learning in Python

DataCamp offers the Supervised Machine Learning in Python track, a beginner-level program with 25 provider-listed hours. Access requires a Premium subscription, priced at USD 35 per month regular, checked 8 September 2026, which represents one month of access and not a guaranteed total completion cost. The curriculum consists of six courses covering prediction using labeled data, including linear and logistic regression, Support Vector Machines, and tree-based models in scikit-learn, as well as Extreme Gradient Boosting with XGBoost, hyperparameter tuning, and ensemble learning. The track also includes two separate bonus projects. There are no prerequisites for this track. Upon finishing the modules, learners receive a Statement of Accomplishment from DataCamp.

Facts checked 9 Sep 2026

Price
DataCamp Premium — USD 35/month for course content, billed monthly at the regular price
Time
25 hours

Provider-listed track duration; not guaranteed elapsed completion time.

Level
Beginner
Credential
Statement of Accomplishment

Add this credential to your LinkedIn profile, resume, or CV; share it on social media and in your performance review.

Prerequisites
There are no prerequisites for this track.

Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.

Price
DataCamp Premium — USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access is USD 35 with no monthly promotion shown. Annual regular USD 330 and promotional USD 165 are separate billed totals; no promotion expiry or additional account/geographic restriction is stated. Access price is not a guarantee of track completion. · Official pricing
Duration
25 hoursProvider-listed track duration; not guaranteed elapsed completion time.
Level
Beginner
Format
Track
Credential
Statement of Accomplishment
Prerequisites
There are no prerequisites for this track.

Course and activity access

Career and Skill tracks: Basic not included; Premium included.. Official source

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Supervised Machine Learning in Python: USD 35; position among 36 other courses and tracks with accepted USD prices. Payment scopes differ.

See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.

What’s covered

  • Supervised Learning with scikit-learn
  • Linear Classifiers in Python
  • Machine Learning with Tree-Based Models in Python
  • Extreme Gradient Boosting with XGBoost
  • Hyperparameter Tuning in Python
  • Ensemble Methods in Python

Prerequisites: There are no prerequisites for this track.

Explore DataCamp

View official program ↗

What topics are covered in the Supervised Machine Learning in Python track?

The Supervised Machine Learning in Python track by DataCamp includes six main courses that cover prediction using labeled data. Learners study supervised learning with scikit-learn, linear classifiers in Python such as logistic regression and support vector machines, and machine learning with tree-based models. The curriculum also explores extreme gradient boosting with XGBoost, hyperparameter tuning in Python including grid, random, and informed search, and ensemble methods such as bagging, boosting, and stacking. Additionally, the track provides two bonus projects focusing on predictive modeling for agriculture and predicting movie rental durations.

How much does this DataCamp program cost and how long does it take?

The provider states that the Supervised Machine Learning in Python track takes approximately 25 hours on average to complete through self-paced exercises and courses. Access to the program requires a DataCamp Premium subscription, which costs USD 35 monthly at the regular price checked on 8 September 2026. This subscription fee provides one month of access to the platform's career and skill tracks, and it does not represent a guaranteed total cost to finish the curriculum. Because the courses are self-paced, elapsed time varies with the learner, while the final amount depends on the subscription route and billing periods selected.

Are there any prerequisites for enrolling, and what credential is awarded?

According to DataCamp, there are no prerequisites required to begin the Supervised Machine Learning in Python track, and it is explicitly suitable for beginners who are new to machine learning or those specializing in supervised machine learning. Upon completion of the self-paced courses, learners earn a Statement of Accomplishment issued by DataCamp. This statement can be added to a resume, CV, or LinkedIn profile, and shared in performance reviews. The official evidence does not state any expiration date, renewal requirement, or specific certification exam required to earn this statement.

What you actually do

  • Supervised Learning with scikit-learn — Interactive Python predictions using real-world datasets. · Source
  • Linear Classifiers in Python — Logistic regression and support vector machines. · Source
  • Machine Learning with Tree-Based Models in Python — Trees and ensembles for regression and classification using scikit-learn. · Source
  • Extreme Gradient Boosting with XGBoost — Gradient boosting for classification and regression. · Source
  • Hyperparameter Tuning in Python — Grid, random and informed search. · Source
  • Ensemble Methods in Python — Bagging, boosting and stacking. · Source

What the credential is

Credential type
Statement of Accomplishment · www.datacamp.com / supervised-machine-learning-in-python
Credential
Statement of Accomplishment · www.datacamp.com / supervised-machine-learning-in-python
Issuer
DataCamp · www.datacamp.com / supervised-machine-learning-in-python
Sharing
Add this credential to your LinkedIn profile, resume, or CV; share it on social media and in your performance review. · www.datacamp.com / supervised-machine-learning-in-python

Who should skip it

  • Learners looking for an advanced program, as this track is explicitly rated at the beginner level for those new to machine learning. · Source
  • Students who want a program taught in R, as this track entirely focuses on Python and scikit-learn. · Source
  • Individuals seeking a credential that includes a formal certification exam, as no exam is stated for the Statement of Accomplishment. · Source

Alternatives in the registry

Related by topic or level.

  • AWS Certified AI Practitioner (AIF-C01) — USD 100 (One initial exam attempt; check applicable regional pricing and taxes. Optional preparation and retakes are not included.); 90 minutes (exam only; not preparation time).
  • AI Fundamentals — DataCamp Premium — USD 35/month for course content, billed monthly at the regular price; Approximately 9 hours.
  • Machine Learning Fundamentals in Python — DataCamp Premium — USD 35/month for course content, billed monthly at the regular price; 16 hours.

Change log

  • : Registry admission from previously reviewed official evidence; individual fact dates are preserved. · Source
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