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PCAP - Certified Associate in Python Programming (PCAP-31-03) Certification Path

The Certified Associate in Python Programming Certification includes only one PCAP-31-03 exam. There are no official prerequisites for the exam, but the applicants are recommended to have little prior knowledge of any programming language, should have very basic knowledge of Mathematics, and have attempted the PCAP-31-03 practice exams.

Reference: https://pythoninstitute.org/certification/pcap-certification-associate/pcap-exam-syllabus/

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Topics of PCAP - Certified Associate in Python Programming (PCAP-31-03) Exam

The syllabus for the PCAP-31-03 exam dumps is listed below in detail of each section and their topics:

1. Control and Evaluations (25%)

Objectives covered by this section:

  • string operators: * +
  • accuracy of floating-point numbers
  • assignments and shortcut operators
  • formatting print() output with end= and sep= arguments
  • bitwise operators: ~ & ^ | « »
  • simple strings: constructing, assigning, indexing, slicing comparing, immutability
  • the pass instruction
  • conditional statements: if, if-else, if-elif, if-elif-else
  • operators: unary and binary, priorities and binding
  • simple lists: constructing vectors, indexing, and slicing, the len() function
  • Boolean operators: not and or
  • numeric operators: * / % // + -
  • controlling loop execution: break, continue
  • building loops: while, for, range(), in, iterating through sequences
  • basic input and output: input(), print(), int(), float(), str() functions
  • expanding loops: while-else, for-else, nesting loops, and conditional statements
  • literals: Boolean, integer, floating-point numbers, scientific notation, strings
  • basic concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
  • relational operators (== != > >= < <= ), building complex Boolean expressions

2. Data Aggregates (25%)

Objectives covered by this section:

  • tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
  • strings in detail: ASCII, UNICODE, UTF-8, immutability, escaping using the \ character, quotes and apostrophes inside strings, multiline strings, copying vs. cloning, advanced slicing, string vs. string, string vs. non-string, basic string methods (upper(), lower(), isxxx(), capitalize(), split(), join(), etc.) and functions (len(), chr(), ord()), escape characters
  • tuples: indexing, slicing, building, immutability
  • lists in lists: matrices and cubes
  • dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items(), and values() methods
  • lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning

3. Functions and Modules (25%)

Objectives covered by this section:

  • pyc file creation and usage
  • Python hashbangs, using multiline strings as module documentation
  • name scopes, name hiding (shadowing), the global keyword
  • constructing and distributing packages, packages vs. directories, the role of the init.py file
  • map(), filter(), reduce(), reversed(), sorted() functions and the sort() method
  • lambda functions, defining and using
  • parameters vs. arguments, positional keyword and mixed argument passing, default parameter values
  • hiding module entities
  • return and yield keywords, returning results, the None keyword, recursion
  • writing and using modules, the name variable
  • defining and invoking your functions and generators
  • import directives, qualifying entities with module names, initializing modules
  • converting generator objects into lists using the list() function
  • the if operator

4. Classes, Objects, and Exceptions (25%)

Objectives covered by this section:

  • the anatomy of an exception object
  • name mangling
  • writing and using constructors
  • hasattr(), type(), issubclass(), isinstance(), super() functions
  • read(), readinto(), readline(), write(), close() methods
  • using predefined exceptions and defining your ones
  • defining your classes, superclasses, subclasses, inheritance, searching for missing class components, creating objects
  • adding your exceptions to an existing hierarchy
  • the role of the str method
  • inheritance and overriding, finding class/object components
  • invoking methods, passing and using the self-argument/parameter
  • class methods: defining and using the self-parameter meaning and usage
  • introspection: dict, name, module, bases properties, examining class/object structure
  • single inheritance vs. multiple inheritances
  • assertions
  • the init method
  • the try-except-else-finally block, the raise statement, the except-as variant
  • class attributes: class variables and instance variables, defining, adding, and removing attributes, explicit constructor invocation
  • exceptions hierarchy, assigning more than one exception to one except branch
  • input/output basics: opening files with the open() function, stream objects, binary vs. text files, newline character translation, reading and writing files, byte array objects

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Python Institute PCAP-31-03 Exam Syllabus Topics:

SectionWeightObjectives
Miscellaneous Concepts and I/O Operations22%- Coding conventions
  • 1. PEP 8 guidelines
- Functional programming tools
  • 1. Iterators and generators
  • 2. Lambda functions
  • 3. Closures and nested functions
- File I/O operations
  • 1. Text vs binary modes
  • 2. Opening, reading, writing, closing files
- List comprehensions
  • 1. Syntax and conditional expressions
- File system and OS interaction
  • 1. os and sys modules basics
Strings and String Operations18%- Character encoding and representation
  • 1. ord(), chr() functions
  • 2. ASCII, UNICODE, UTF-8, escape sequences
- Operations on strings
  • 1. Concatenation, repetition, comparison
  • 2. Membership testing: in, not in
- Indexing, slicing, and immutability
- String methods
  • 1. isalpha, isdigit, isspace, etc.
  • 2. join, split, strip, replace
  • 3. find, index, count, rfind, rindex
Object-Oriented Programming34%- Inheritance
  • 1. Diamond problem and MRO
  • 2. Overriding methods and super()
  • 3. Single and multiple inheritance
  • 4. isinstance(), issubclass()
- Core concepts: class, object, encapsulation, inheritance, polymorphism
- Methods
  • 1. Instance methods, self parameter
  • 2. Special methods: __init__, __str__, __len__, etc.
- Class and instance variables
  • 1. Declaration and initialization
  • 2. __dict__ attribute
  • 3. Private components and name mangling
- Introspection and attributes
  • 1. __name__, __module__, __bases__
  • 2. hasattr(), getattr(), setattr()
Exceptions14%- User-defined exceptions
  • 1. Exception attributes and methods
  • 2. Defining and raising custom exceptions
- Exception hierarchy and built-in exceptions
- Error handling syntax
  • 1. Exception chaining and arguments
  • 2. try, except, else, finally blocks
Modules and Packages12%- Standard modules usage
  • 1. platform module: system, version, implementation details
  • 2. math module: ceil, floor, trunc, factorial, hypot, sqrt
  • 3. random module: random, seed, choice, sample
- Module built-ins and environment
  • 1. sys.path variable
  • 2. dir() function
- Custom modules and packages
  • 1. Public vs private components
  • 2. __name__ variable
  • 3. __pycache__ directory
  • 4. __init__.py file
- Import mechanisms and variants
  • 1. import, from ... import, import ... as, import *
  • 2. Nested modules and qualification

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