Dates and Times in Python
Take your data analyst skillset to the next level: master working with dates and times in Python
Start for free
What you get:
- 3 hours of content
- 4 Interactive exercises
- 33 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
Dates and Times in Python
Start for free
What you get:
- 3 hours of content
- 4 Interactive exercises
- 33 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
Start for free
What you get:
- 3 hours of content
- 4 Interactive exercises
- 33 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
What You Learn
- Gain essential Python skills crucial for advancing to full Python proficiency
- Boost your abilities when it comes to working with dates and times
- Master time standards, time zones, and time regulations and implement these skills in real-world challenges
- Translate your theoretical Python knowledge into practical solutions by analysing a sales company’s dataset
- Create compelling data visualizations of date- and time-related data
- Become a proficient Python programmer
Top Choice of Leading Companies Worldwide
Industry leaders and professionals globally rely on this top-rated course to enhance their skills.
Course Description
Dates and Times in Python is the course that will take your data analyst skillset to the next level! The ability to adjust dates and time according to a specific territory is crucial across numerous businesses and industries. In this course, you will master handling both date values that depend on the structure of the different calendars used across the globe, and time values that reflect time-saving regulations, clock changes, and time conversions. You will also discover how to keep track of historical data, use specific date- and time-related libraries, classes, methods, and conversion techniques in Python.
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1.1 What Does the Course Cover
4 min
1.2 Introduction to Working with Dates and Times
3 min
1.3 Time Standards and Regulations: GMT and UTC
6 min
1.5 Principles of Working with Dates and Times in Computing – Unix Time
3 min
1.7 Principles of Working with Dates and Times in Computing – Dates in Python
5 min
1.9 The datetime Module: working with Dates
7 min
Interactive Exercises
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.
Curriculum
- 1. Dates and Times in Python15 Lessons 76 Min
Here, we’ll cover the concepts of time standards, time zones, and time regulations. We will discuss the main principles of working with dates, times, and time zones in computing and will learn how to apply these principles in Python.
What Does the Course Cover4 minIntroduction to Working with Dates and Times3 minTime Standards and Regulations: GMT and UTC6 minPrinciples of Working with Dates and Times in Computing – Unix Time3 minPrinciples of Working with Dates and Times in Computing – Dates in Python5 minThe datetime Module: working with Dates7 minThe datetime Module: working with Time4 minThe datetime Module: working with the datetime class3 min.strftime(): Converting datetime Objects into Strings7 min.strptime(): Converting Strings into datetime Objects5 minpd.to_datetime(): Converting Data into datetime Objects7 minFocus on Working with Timestamps2 minPractical Application of Working with Timestamps in Python9 minConverting between Timezones in Python: the pytz Module9 minConverting between Timezones with pandas2 min - 2. A Practical Example: Working with Dates, Times, and Time Zones8 Lessons 47 Min
This section consists of a practical example covering all the basic, as well as the advanced techniques you’ll need to become a data analyst who can handle dates and times with ease. We will work on an actual data set and will operate on tasks including processes such as data preparation, data manipulation, data analysis, and data visualisation.
Practical Example Exercise - Dates and Times Read now3 minIntroduction6 minPart I - Data Preparation part 13 minPart I - Data Preparation part 27 minPart II - Data Manipulation part 16 minPart II - Data Manipulation part 26 minPart III - Data Analysis8 minPart IV - Data Visualization8 min
Topics
Course Requirements
- Highly recommended to take the Intro to Python course first
- You will need to install the Anaconda package, which includes Jupyter Notebook
Who Should Take This Course?
Level of difficulty: Intermediate
- Aspiring data analysts, data scientists, data engineers, AI engineers
- Existing data analysts, data scientists, data engineers who want to boost their Python programming skills
- Graduate students who need Python for their studies
- Everyone who wants to learn how to code in Python
Exams and Certification
A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.
Meet Your Instructor
Ivan has a background in systems and sound engineering, along with information technologies and communications. In addition, he has professional experience in the media production industry and telecommunications. Ivan believes the value of data is growing every day, and it will soon be the biggest commodity in the world. He describes himself as “forward-looking and visionary”. Besides data analysis, data collection, and Python programming, he is passionate about artificial intelligence, signal processing, sound design, acoustics, and music. He sees these subjects as interconnected, and his work goal is to keep the balance between science and arts.
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