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)
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%)
Import and use modules and packages
import variants: import, from import, import as, import *
advanced qualifying for nested modules
the dir() function
the sys.path variable
Perform evaluations using the math module
functions: ceil(), floor(), trunc(), factorial(), hypot(), sqrt()
Generate random values using the random module
functions: random(), seed(), choice(), sample()
Discover host platform properties using the platform module
functions: platform(), machine(), processor(), system(), version(), python_implementation(), python_version_tuple()
Create and use user-defined modules and packages
idea and rationale
the __pycache__ directory
the __name__ variable
public and private variables
the __init__. py file
searching for/through modules/packages
nested packages vs. directory trees
Exceptions (14%)
Handle errors using Python-defined exceptions
except, except:-except, except:-else:, except (e1, e2)
the hierarchy of exceptions
raise, raise ex
assert
event classes
except E as e
the arg property
Extend the Python exceptions hierarchy with self-defined exceptions
self-defined exceptions
defining and using self-defined exceptions
Strings (18%)
Understand machine representation of characters
encoding standards: ASCII, UNICODE, UTF-8, code points, escape sequences
Operate on strings
functions: ord(), chr()
indexing, slicing, immutability
iterating through strings, concatenating, multiplying, comparing (against strings and numbers)
operators: in, not in
Employ built-in string methods
methods: .isxxx(), .join(), .split(), .sort(), sorted(), .index(), .find(), .rfind()
Object-Oriented Programming (34%)
Understand the Object-Oriented approach
ideas and notions: class, object, property, method, encapsulation, inheritance, superclass, subclass, identifying class components
Employ class and object properties
instance vs. class variables: declarations and initialization
the __dict__ property (objects vs. classes)
private components (instances vs. classes)
name mangling
Equip a class with methods
declaring and using methods
the self parameter
Discover the class structure
introspection and the hasattr() function (objects vs classes)
properties: __name__, __module__ , __bases__
Build a class hierarchy using inheritance
single and multiple inheritance
the isinstance() function
overriding
operators:
not is, is
polymorphism
overriding the __str__() method
diamonds
Construct and initialize objects
declaring and invoking constructors
Miscellaneous (22%)
Build complex lists using list comprehension
list comprehensions: the if operator, nested comprehensions
Embed lambda functions into the code
lambdas: defining and using lambdas
self-defined functions taking lambdas as arguments
functions: map(), filter()
Define and use closures
closures: meaning and rationale
defining and using closures
Understand basic Input/Output terminology
I/O modes
predefined streams
handles vs. streams
text vs. binary modes
Perform Input/Output operations
the open() function
the errno variable and its values
functions: close(), .read(), .write(), .readline(), readlines()
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:
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.
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.
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.
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:
YouTube: YouTube is the world’s largest video-sharing platform, and its backend is entirely written in Python.
Instagram: Instagram, one of the most popular social media platforms today, was built using Python.
Dropbox: Dropbox, a popular file-sharing and cloud storage platform, uses Python to manage its vast amounts of data and build its infrastructure.
Reddit: Reddit, one of the most popular online discussion forums, was initially built using Python.
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.