
Explore Python basics in this introduction, a language that helps you work quickly, integrate systems, and is easy for beginners, with applications in machine learning, artificial intelligence, and game development.
Explore Python, a versatile programming language, and learn how it supports web development, education, software development, and applications in science, medicine, and machine learning.
Explore Python formatting and outputting data, comparing older style string concatenation with newer formatting techniques using variables like name and color.
Learn how boolean values work in Python, using class variables and functions to obtain true or false, apply boolean operators, and use booleans in conditions and loops.
Define a Python function and explore function arguments, including default arguments, and learn how to call a function with different options using brackets.
Learn how to create and use Python sets, lists, and tuples, including defining them and adjusting bracket syntax for basic data structures.
Learn Python conditional statements and loops by building if statements, combining conditions with and, and iterating with for loops over ranges.
Explore pandas data analysis basics by reading a data file into a DataFrame, selecting samples, and printing columns to learn data frames and simple Python algorithms.
Learn to use NumPy and Matplotlib for data visualization and scientific computing, enabling clear analytics and biotech insights.
Learn how Biton algorithm works and practice Python list operations—append, pop, remove, and print—to manipulate array elements and build basic data structure programs.
Learn to import the math module, define and call functions, create anonymous functions, apply conditional logic, and return a simple algorithm as a function.
Explore the n queens problem by placing queens on a chessboard so no two attack each other, using array indexing and diagonal checks.
Provide a pathway for web development and machine learning via an application development framework, with documentation, process guidance, and access to valuable open-source resources and community support.
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of its features support functional programming and aspect-oriented programming (including by metaprogramming[58] and metaobjects (magic methods)) PCEP – Certified Entry-Level Python Programmer Certification: Exam Syllabus
Exam block #1: Basic Concepts (17%)
Objectives covered by the block (5 exam items)
fundamental concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
literals: Boolean, integer, floating-point numbers, scientific notation, strings
comments
the print() function
the input() function
numeral systems (binary, octal, decimal, hexadecimal)
numeric operators: ** * / % // + –
string operators: * +
assignments and shortcut operators
Exam block #2: Data Types, Evaluations, and Basic I/O Operations (20%)
Objectives covered by the block (6 exam items)
operators: unary and binary, priorities and binding
bitwise operators: ~ & ^ | << >>
Boolean operators: not and or
Boolean expressions
relational operators ( == != > >= < <= ), building complex Boolean expressions
accuracy of floating-point numbers
basic input and output operations using the input(), print(), int(), float(), str(), len() functions
formatting print() output with end= and sep= arguments
type casting
basic calculations
simple strings: constructing, assigning, indexing, immutability
Exam block #3: Control Flow – loops and conditional blocks (20%)
Objectives covered by the block (6 exam items)
conditional statements: if, if-else, if-elif, if-elif-else
multiple conditional statements
the pass instruction
building loops: while, for, range(), in
iterating through sequences
expanding loops: while-else, for-else
nesting loops and conditional statements
controlling loop execution: break, continue
Exam block #4: Data Collections – Lists, Tuples, and Dictionaries (23%)
Objectives covered by the block (7 exam items)
simple lists: constructing vectors, indexing and slicing, the len() function
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
lists in lists: matrices and cubes
tuples: indexing, slicing, building, immutability
tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
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
strings in detail: escaping using the \ character, quotes and apostrophes inside strings, multi-line strings, basic string functions.
Exam block #5: Functions (20%)
Objectives covered by the block (6 exam items)
defining and invoking your own functions and generators
return and yield keywords, returning results,
the None keyword,
recursion
parameters vs. arguments,
positional keyword and mixed argument passing,
default parameter values
converting generator objects into lists using the list() function
name scopes, name hiding (shadowing), the global keyword