Dates and Times in Python

with Ivan Manov and Martin Ganchev
4.9/5
(339)

Take your data analyst skillset to the next level: master working with dates and times in Python

3 hours of content 4594 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

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

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

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

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

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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What Does the Course Cover

1.1 What Does the Course Cover

4 min

Introduction to Working with Dates and Times

1.2 Introduction to Working with Dates and Times

3 min

Time Standards and Regulations: GMT and UTC

1.3 Time Standards and Regulations: GMT and UTC

6 min

Principles of Working with Dates and Times in Computing – Unix Time

1.5 Principles of Working with Dates and Times in Computing – Unix Time

3 min

Principles of Working with Dates and Times in Computing – Dates in Python

1.7 Principles of Working with Dates and Times in Computing – Dates in Python

5 min

The datetime Module: working with Dates

1.9 The datetime Module: working with Dates

7 min

Curriculum

  • 1. Dates and Times in Python
    15 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 Cover
    4 min
    Introduction to Working with Dates and Times
    3 min
    Time Standards and Regulations: GMT and UTC
    6 min
    Principles of Working with Dates and Times in Computing – Unix Time
    3 min
    Principles of Working with Dates and Times in Computing – Dates in Python
    5 min
    The datetime Module: working with Dates
    7 min
    The datetime Module: working with Time
    4 min
    The datetime Module: working with the datetime class
    3 min
    .strftime(): Converting datetime Objects into Strings
    7 min
    .strptime(): Converting Strings into datetime Objects
    5 min
    pd.to_datetime(): Converting Data into datetime Objects
    7 min
    Focus on Working with Timestamps
    2 min
    Practical Application of Working with Timestamps in Python
    9 min
    Converting between Timezones in Python: the pytz Module
    9 min
    Converting between Timezones with pandas
    2 min
  • 2. A Practical Example: Working with Dates, Times, and Time Zones
    8 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 now
    3 min
    Introduction
    6 min
    Part I - Data Preparation part 1
    3 min
    Part I - Data Preparation part 2
    7 min
    Part II - Data Manipulation part 1
    6 min
    Part II - Data Manipulation part 2
    6 min
    Part III - Data Analysis
    8 min
    Part IV - Data Visualization
    8 min

Topics

PythonProgrammingdata visualizationJupyterDates And TimesTime Zones

Tools & Technologies

python

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.

Exams and certification

Meet Your Instructor

Ivan Manov

Ivan Manov

Course Creator at

6 Courses

1232 Reviews

14453 Students

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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