Working with Dates and Times in Python
Dates and times trip up even experienced developers—timezone bugs, format mismatches, and scheduling logic derail production code. This course cuts through the confusion with hands-on labs, teaching you to manipulate, parse, and validate temporal data like a professional. You’ll move from datetime basics to real-world patterns you’ll use immediately.
AIU.ac Verdict: Essential for backend developers, data engineers, and anyone building scheduling or logging systems. The course is lean and practical, though it assumes Python fundamentals—you’ll need solid grasp of strings and objects to keep pace.
What This Course Covers
You’ll work through Python’s datetime module, timedelta objects, and timezone-aware operations. Expect labs on parsing ISO 8601 strings, calculating durations, handling daylight saving time edge cases, and formatting dates for APIs and logs. Pashkov covers both naive and aware datetime objects, so you’ll understand when UTC matters and how to avoid common pitfalls.
The practical angle shines in real-world scenarios: scheduling tasks across timezones, validating user input dates, storing temporal data safely in databases, and working with third-party APIs that return timestamps in unexpected formats. By the end, you’ll confidently handle date logic in production code without reaching for external libraries unnecessarily.
Who Is This Course For?
Ideal for:
- Backend and full-stack developers: Building APIs, scheduling systems, or logging infrastructure where temporal accuracy matters.
- Data engineers and analysts: Processing time-series data, ETL pipelines, and reports that depend on correct date arithmetic and timezone handling.
- Python developers stepping up: Solid Python basics but haven’t yet mastered datetime—ready to eliminate timezone bugs and date-handling guesswork.
May not suit:
- Python beginners: You’ll need comfort with strings, objects, and imports. Start with Python fundamentals first.
- Developers seeking advanced temporal libraries: This focuses on the standard library. If you need Arrow, Pendulum, or complex scheduling frameworks, this is a foundation, not the destination.
Frequently Asked Questions
How long does Working with Dates and Times in Python take?
2 hours 2 minutes of video content. Plan 3–4 hours total if you’re working through the hands-on labs and experimenting with code.
What Python version does this course use?
The course covers the standard datetime module, which is stable across Python 3.x versions. The concepts apply to Python 3.8 and later.
Do I need to know about timezones before starting?
No. Pashkov assumes no prior timezone knowledge and builds from naive datetimes through to timezone-aware operations. You’ll learn the why, not just the how.
Are there hands-on labs or just videos?
Pluralsight includes interactive labs and sandboxes. You’ll write and run code against real scenarios, not just watch demonstrations.
Course by Georgy Pashkov on Pluralsight. Duration: 2h 2m. Last verified by AIU.ac: March 2026.
