Program profile · official sources
Machine Learning with K-Nearest Neighbors
365 Data Science's 'Machine Learning with K-Nearest Neighbors' is an intermediate-level, online, self-paced course taught by Hristina Hristova. The provider lists a headline duration of 2 hours, 1 lesson hour, and 25 minutes of practice exams; the curriculum covers the inner workings of the KNN algorithm, distance metrics, random dataset generation, and solving regression tasks. Students use Python's scikit-learn library to build models, visualize decision regions, and optimize parameters with grid search. Earning the provider-issued course certificate requires course completion and passing the course exam, with general terms specifying a 60 percent or higher passing grade. The provider lists 2 CPE credits; acceptance depends on individual state boards. Intermediate Python skills are required, and the formal prerequisites box lists Streamlit and an OpenAI API key.
Facts checked 1 Oct 2026
- Price
- See pricing
Price observation recorded 1 Oct 2026 (not a current price): As shown in the United States on 1 October 2026, the 365 pricing page Self-study card displays $36/month reference price and a promotional $12.50/month equivalent billed annually; the same pricing page 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
- 2 hours (provider headline; 1 hour of lessons and 25 minutes of practice exams are 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), Streamlit library, OpenAI 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: Introduction to Python, Machine Learning in Python.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
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
- KNN Classifier – Theory
- Setting up the Environment
- KNN Classifier – Practical Example
- KNN Regressor
- Pros and Cons of the KNN Algorithm
- Course exam
Prerequisites: Python (version 3.8 or later), Streamlit library, OpenAI 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: Introduction to Python, Machine Learning in Python.
What you actually do
- KNN Classifier – Theory : 13 min; Section 1 · Source
- Setting up the Environment : 5 min; Section 2 · Source
- KNN Classifier – Practical Example : 37 min; Section 3 · Source
- KNN Regressor : 19 min; Section 4 · Source
- Pros and Cons of the KNN Algorithm : 7 min; Section 5 · Source
- Course exam : 30 min; Section 6 · Source
What the credential is
- Credential type
- Provider-issued course certificate · 365datascience.com / machine-learning-with-k-nearest-neighbors
- 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
- Complete the course and pass its course exam with 60% or above under the general certificate terms. 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