Pluralsightintermediateen

Core Python 3: Numeric Types, Dates, and Times

Master advanced Python numeric types! Learn beyond basic int/float, solve numerical limitations, and enhance your Python programs.

4.5(56)
56m
Certificate
Austin Bingham
Austin BinghamInstructor

Course Content

Core Python 3: Numeric Types, Dates, and Times is an intermediate-level Pluralsight course taught by Austin Bingham. It runs 56m, is taught in English, and includes a certificate of completion. Learners rate it 4.5 out of 5 from 56 reviews. It is a paid course, first published June 2024.

Dive deeper into Python numeric types with this comprehensive course! While int and float are common, they aren't always the best choice for every calculation. This course, Core Python 3: Numeric Types, Dates, and Times, explores advanced numeric options to meet your programming needs.

You'll learn about:

  • Decimal: Understand when to use the Decimal type for precise decimal arithmetic, avoiding floating-point inaccuracies. Discover how to implement accurate financial calculations and more.
  • Fraction: Master the Fraction type for representing rational numbers exactly, crucial for scenarios requiring precise fractions.
  • Complex Numbers: Explore and utilize complex numbers for working with imaginary and complex number calculations in Python.
  • Numeric Functions: Review versatile functions applicable to a wide range of numeric types, streamlining your calculations.
  • Date and Time Handling: Learn to effectively work with dates and times using Python's powerful datetime package. Implement date and time manipulations for various applications.
  • Practical Applications: See how selecting the correct numeric type can significantly impact the accuracy and outcome of your programs through real-world examples.

By the end of this course, you'll gain a solid understanding of Python's numeric types, including int, float, Decimal, Fraction, and Complex, and how to apply them effectively. Enhance your Python programming skills and gain a deeper appreciation for numerical programming in Python.

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