Program profile · official sources
Time Series Analysis with Python
365 Data Science's 'Time Series Analysis with Python' is an intermediate-level, online, self-paced course that teaches proven forecasting techniques and manual model selection principles. Instructed by Viktor Mehandzhiyski, the seven-hour curriculum introduces learners to data normalization and visualizing time series types like white noise and random walk. Topics cover AR, MA, ARMA, ARIMA, ARCH, and GARCH models using Python, culminating in practical business case applications and automated model selection with Auto ARIMA. 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. Python 3.8 or later, pandas, a code editor, and basic Python programming skills are required, while NumPy familiarity is recommended.
Facts checked 2 Oct 2026
- Price
- See pricing
Price observation recorded 2 Oct 2026 (not a current price): US observation on 2 October 2026: platform Self-study displays $36/month reference price and $29/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.
Official source · Checked
- 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.
- Prerequisites
- Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code). Basic familiarity with Python programming is required. Familiarity with NumPy is helpful but not mandatory. Advanced preparation: Statistics, Introduction to Python.
- Format
- 100% online, self-paced course
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.
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What’s covered
- Introduction
- Setting Up the Environment
- Introduction to Time Series in Python
- Creating a Time Series Object in Python
- Working with Time Series in Python
- Picking the Correct Model
- The AR Model
- The MA Model
- The ARMA Model
- The ARIMA Model
- The ARCH Model
- The GARCH Model
- Auto ARIMA
- Time Series Forecasting
- Business Case
- Course exam
Prerequisites: Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code). Basic familiarity with Python programming is required. Familiarity with NumPy is helpful but not mandatory. Advanced preparation: Statistics, Introduction to Python.
What you actually do
- Introduction : 4 min; Section 1 · Source
- Setting Up the Environment : 2 min; Section 2 · Source
- Introduction to Time Series in Python : 24 min; Section 3 · Source
- Creating a Time Series Object in Python : 26 min; Section 4 · Source
- Working with Time Series in Python : 40 min; Section 5 · Source
- Picking the Correct Model : 3 min; Section 6 · Source
- The AR Model : 54 min; Section 7 · Source
- The MA Model : 34 min; Section 8 · Source
- The ARMA Model : 41 min; Section 9 · Source
- The ARIMA Model : 45 min; Section 10 · Source
- The ARCH Model : 34 min; Section 11 · Source
- The GARCH Model : 13 min; Section 12 · Source
- Auto ARIMA : 28 min; Section 13 · Source
- Time Series Forecasting : 46 min; Section 14 · Source
- Business Case : 28 min; Section 15 · Source
- Course exam : 15 min; Section 16 · Source
What the credential is
- Credential type
- Provider-issued course certificate · 365datascience.com / time-series-analysis-with-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