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Python PCAP: Certified Associate in Python Programming[2024]

Get certified for Python! Prepare for your Python Certification Exam PCAP-31-03 with 6 Practice Tests and 540 questions!
Instructor
Ana Uzelac PhD
174 Students enrolled
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Get certified in Python! Become a Certified Associate in Python Programming! Pass your PCAP-31-03 on the first attempt!

These PCAP-31-03 Practise Exams provide you with realistic test questions and provide interactive, question-level feedback. It provides a solid foundation for further study and career advancement in the field of programming and software development.

This PCAP certification course will prepare you for what it is like to take the PCAP-31-03. The course consists of 6 Practice Tests with 581 unique questions from all knowledge areas that will prepare you to pass the PCAP-31-03 exam at the Python Institute! Every question has an explanation with “Try It Yourself Code” that you can run to test the code. (The download link with code examples will be provided in every practice test)

 

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So, what are you waiting for? Prepare yourself and get your Python Certification!

PCAP-31-03 Exam Information:

Lasts: 65 minutes

Consists of 40 questions

Passing score: 70%

Format: Single and multiple select questions

In this course, you will find a total of 540 questions to learn and practice for the exam!!!

All questions are from four domains of the exam, so you can take and pass the actual PCAP-31-03 Certification Exam with confidence and become a Certified Associate in Python Programming!

The practice test covers all the topics in the new PCAP-31-03 Syllabus – Python Institute

  • Modules and Packages (12%)

    1. Import and use modules and packages

      1. import variants: import, from import, import as, import *

      2. advanced qualifying for nested modules

      3. the dir() function

      4. the sys.path variable

    2. Perform evaluations using the math module

      1. functions: ceil(), floor(), trunc(), factorial(), hypot(), sqrt()

    3. Generate random values using the random module

      1. functions: random(), seed(), choice(), sample()

    4. Discover host platform properties using the platform module

      1. functions: platform(), machine(), processor(), system(), version(), python_implementation(), python_version_tuple()

    5. Create and use user-defined modules and packages

      1. idea and rationale

      2. the __pycache__ directory

      3. the __name__ variable

      4. public and private variables

      5. the __init__. py file

      6. searching for/through modules/packages

      7. nested packages vs. directory trees

  • Exceptions (14%)

    1. Handle errors using Python-defined exceptions

      1. except, except:-except, except:-else:, except (e1, e2)

      2. the hierarchy of exceptions

      3. raise, raise ex

      4. assert

      5. event classes

      6. except E as e

      7. the arg property

    2. Extend the Python exceptions hierarchy with self-defined exceptions

      1. self-defined exceptions

      2. defining and using self-defined exceptions

  • Strings (18%)

    1. Understand machine representation of characters

      1. encoding standards: ASCII, UNICODE, UTF-8, code points, escape sequences

    2. Operate on strings

      1. functions: ord(), chr()

      2. indexing, slicing, immutability

      3. iterating through strings, concatenating, multiplying, comparing (against strings and numbers)

      4. operators: in, not in

    3. Employ built-in string methods

      1. methods: .isxxx(), .join(), .split(), .sort(), sorted(), .index(), .find(), .rfind()

  • Object-Oriented Programming (34%)

    1. Understand the Object-Oriented approach

      1. ideas and notions: class, object, property, method, encapsulation, inheritance, superclass, subclass, identifying class components

    2. Employ class and object properties

      1. instance vs. class variables: declarations and initialization

      2. the __dict__ property (objects vs. classes)

      3. private components (instances vs. classes)

      4. name mangling

    3. Equip a class with methods

      1. declaring and using methods

      2. the self parameter

    4. Discover the class structure

      1. introspection and the hasattr() function (objects vs classes)

      2. properties: __name__, __module__ , __bases__

    5. Build a class hierarchy using inheritance

      1. single and multiple inheritance

      2. the isinstance() function

      3. overriding

      4. operators:

      5. not is, is

      6. polymorphism

      7. overriding the __str__() method

      8. diamonds

    6. Construct and initialize objects

      1. declaring and invoking constructors

  • Miscellaneous (22%)

    1. Build complex lists using list comprehension

      1. list comprehensions: the if operator, nested comprehensions

    2. Embed lambda functions into the code

      1. lambdas: defining and using lambdas

      2. self-defined functions taking lambdas as arguments

      3. functions: map(), filter()

    3. Define and use closures

      1. closures: meaning and rationale

      2. defining and using closures

    4. Understand basic Input/Output terminology

      1. I/O modes

      2. predefined streams

      3. handles vs. streams

      4. text vs. binary modes

    5. Perform Input/Output operations

      1. the open() function

      2. the errno variable and its values

      3. functions: close(), .read(), .write(), .readline(), readlines()

      4. using bytearray as input/output buffer

Why should you learn Python?

Did you know that Python has been used to build YouTube, Instagram, Dropbox and Reddit? But, more to that – Python is extremely easy to learn and use. Although it is a high-level, interpreted programming language its syntax is simple and easy to read. On the other hand, you can do a lot of things in Python, such as web and internet development, scientific and numeric computing, data analysis, artificial intelligence, software development, and more. Python has a large and supportive community, with a wealth of libraries and frameworks available. Python’s design philosophy emphasizes code readability and simplicity, making it a popular choice among developers. Learning Python and getting certified in it may skyrocket your career!

Here are some reasons why learning Python can be beneficial:

  1. Easy to Learn and Use: Python has a simple and clean syntax, making it easy for beginners to learn and use. Additionally, Python has an extensive standard library, which makes it a powerful tool for building complex applications with minimal code.

  2. Versatile: Python is a versatile language that can be used for a wide range of applications, such as web development, machine learning, data analysis, scientific computing, game development, and more. It is widely used in scientific research, data science, finance, and education.

  3. Large Community and Support: Python has a large and active community of developers, which provides excellent support and resources for beginners and experts alike. The Python community has contributed to a wide range of libraries and frameworks that are available for free, making it easier for developers to build powerful applications.

  4. High Demand in the Job Market: Python is one of the most popular programming languages used today, and its popularity is increasing every day. Learning Python can help you build a successful career in various fields, including software development, data science, machine learning, and web development.

Some famous applications that were built using Python are:

  1. YouTube: YouTube is the world’s largest video-sharing platform, and its backend is entirely written in Python.

  2. Instagram: Instagram, one of the most popular social media platforms today, was built using Python.

  3. Dropbox: Dropbox, a popular file-sharing and cloud storage platform, uses Python to manage its vast amounts of data and build its infrastructure.

  4. Reddit: Reddit, one of the most popular online discussion forums, was initially built using Python.

  5. NASA: Python is widely used in scientific research, and NASA uses Python for scientific computing, data analysis, and visualization.

These are just a few examples of the many popular applications built using Python. Python’s versatility and ease of use make it a valuable tool for developers, and its popularity in the job market makes it an excellent language to learn.

How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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