Program profile · official sources
Machine Learning in Python
365 Data Science's 'Machine Learning in Python' is an intermediate-level, online, self-paced course that teaches predictive modeling and advanced statistical techniques. Instructed by Iliya Valchanov, the seven-hour curriculum builds upon statistical foundational knowledge, guiding learners through multidimensional spaces, transformations, distributions, linear regression, logistic regression, and K-means clustering using Python and the sklearn library. Earning the provider-issued course certificate requires passing the course exam, with general terms specifying a 60% or higher passing grade. The provider lists 11 CPE credits; acceptance depends on the relevant board. Intermediate Python programming skills and specific tools like a Pinecone account are required, while basic statistics and linear algebra knowledge is recommended.
Facts checked 29 Sep 2026
- Price
- See pricing
Price observation recorded 29 Sep 2026 (not a current price): US observation on 29 September 2026: platform Self-study displays $36/month reference price and $12.50/month billed annually promotional offer; the FAQ separately states $29/month full access. USD is explicit in the saved pricing page state. These are platform access quotes, not a course-completion total. Certificates are included with Self-study.
- Time
- 7 hours (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Credential
- Provider-issued course certificate
Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan.
- Format
- 100% online, self-paced course
- Prerequisites
- Python (version 3.8 or later), Pinecone account and API key, and a code editor or IDE (e.g., VS Code or Jupyter Notebook). Intermediate Python skills are required. Familiarity with basic statistics and linear algebra is helpful but not mandatory. Advanced preparation: Statistics, Introduction to Python.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
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No accepted numeric price in this registry. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Linear Regression
- Linear Regression with sklearn
- Linear Regression Practical Example
- Logistic Regression
- Cluster Analysis (Basics and Prerequisites)
- K-Means Clustering
- Other Types of Clustering
- Course exam
Prerequisites: Python (version 3.8 or later), Pinecone account and API key, and a code editor or IDE (e.g., VS Code or Jupyter Notebook). Intermediate Python skills are required. Familiarity with basic statistics and linear algebra is helpful but not mandatory. Advanced preparation: Statistics, Introduction to Python.
What you actually do
- Linear Regression : 85 min; Section 1 · Source
- Linear Regression with sklearn : 57 min; Section 2 · Source
- Linear Regression Practical Example : 38 min; Section 3 · Source
- Logistic Regression : 41 min; Section 4 · Source
- Cluster Analysis (Basics and Prerequisites) : 15 min; Section 5 · Source
- K-Means Clustering : 50 min; Section 6 · Source
- Other Types of Clustering : 14 min; Section 7 · Source
- Course exam : 110 min; Section 8 · Source
What the credential is
- Credential type
- Provider-issued course certificate · 365datascience.com / machine-learning-in-python
- Credential
- Course Certificate · 365datascience.com / certificates
- Issuer
- 365 Data Science · 365datascience.com / certificates
- Sharing
- Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
- Exam requirement
- Pass the course exam; general certificate terms state 60% or above. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
Who should skip it
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Change log
- : Initial recorded review of official program details. · Source