Python, C++, R - 3 in 1 Course for non CS students

Explore how an integrated development environment (ide) streamlines writing, building, debugging, and editing Python code with features like IntelliSense and error messages. Use PyCharm to organize large projects.

Download PyCharm from jetbrains.com/pycharm and choose professional with a 30-day trial or the community version for Windows, macOS, or Linux, then install and explore the IDE with main.py.

Learn how the print function in Python outputs data by placing a message or a variable inside parentheses, with examples like printing 'hey there' to display to end users.

Learn to write your first line of code in Python using print to display hello world and multiple lines, while noting Python is case sensitive.

Master the Python print function, its syntax, and how it accepts inputs as messages or data. Python is case sensitive; capital P differs from small p.

Explore variables as the core concept of programming, learn how they store diverse data types, and see how Python dynamically assigns and implicitly detects types.

Practice creating and updating variables in Python using print statements and string concatenation with plus signs and quotes to build dynamic messages across sections and subject updates.

Learn how variables store values, how Python is dynamically typed, and how to insert variables into messages using concatenation with plus signs and quotes.

Explore Python's data types, including numeric, sequence, mapping, set, boolean, and none types. Learn about int, float, list, tuple, dictionary, set, boolean, and none types.

Explore the int data type as a numeric type of whole numbers, including positive, negative, and zero, with no decimals; values with decimals are not int.

Learn to define integer variables in Python, print their values, and use type() to verify that a, b, and c are integers, including zero and negative values.

Explore the float data type within numeric types, how decimals work, and practical examples like 0.9, 22.3, 10.0, 20.5, and 25.0.

Learn how decimals form floats in Python by using a with 10.9 and b with 25.5, printing them, and noting that trailing decimals stay float while integers show as int.

Discover indexing concepts by comparing zero-based string indexing to list indexing, using examples like the string pizza and a list of strings such as Steve, buddy, Delhi, Medina, and Madrid.

Explore strings as a sequence of characters in python, using single or double quotes to define values, including numbers, spaces, and special characters. Learn practical string basics and examples.

Explore strings in Python by creating a message variable, printing it, and checking its type. Compare single and double quotes, learn valid string syntax, and use special characters.

Explore practical string operations in Python and R, including upper and lower conversions, isupper and islower checks, capitalize, isspace, count, index, and split by spaces or delimiters.

Explore string concatenation in Python by joining a first name and last name to form 'Steve Jobs' with a space. Observe how numbers join as strings rather than adding.

Learn about boolean, or bool, a data type that stores true or false values and signals decisions in practical projects.

Learn how to work with booleans by creating a boolean variable is_raining set to true, printing its value, and identifying true and false as the valid boolean values, not strings.

Learn boolean negation in Python and R by using the not operator to invert true and false values, preserving the boolean type, with practical examples.

Discover the list data type, a mutable, ordered collection in sequence types, with syntax using square brackets and comma-separated items like 0, 9, 10, 777.

Explore how Python lists store mixed data types by creating lists of integers, floats, strings, and booleans, printing them, and inspecting their type as list.

Learn how to work with Python lists: create lists, compute length with len, and perform append, extend, insert, remove, pop, sort, and reverse operations.

Explore essential Python list operations on strings, including length, count, index, append, insert, remove, pop, sort, reverse, and extend, with practical city list examples.

Learn to slice and read lists with square brackets and start and end indices. Use [start:end] to get a part of list, and [1:3] to fetch indices 1 and 2.

Learn Python list slicing and indexing by using start and end indices and steps to access, skip, include, or reverse cities in a list.

Learn how tuples, immutable collections of one or more items, differ from lists and use round brackets; see a practical example with numbers like 0.9 and 22.3.

Create and print a cities tuple in Python, listing Dallas, New York, New Delhi, London, and Medina. Use the type function to verify it is a tuple.

Learn to locate items in Python tuples using index() and grasp zero-based indexing in a cities tuple. Understand tuple immutability and use count() to tally items like London.

Explore how to slice and read tuples using a start index, end index, and colon, similar to list slicing, to retrieve all elements or a subrange from a cities tuple.

Create and read a cities tuple to practice slicing and indexing. Use start, end, and step parameters to extract subsets and understand end-exclusive behavior.

Learn the set data type in Python, a collection of unique items stored unordered. Understand that duplicates are not allowed, and see the syntax enclosed in flower brackets with examples.

Create a set of numbers in Python, print its type, and observe how duplicates are ignored, while unique values like 15 are stored.

Explore creating and manipulating sets in Python, including intersection, union, and difference, with practical examples using numbers and cities to show unique items, membership, and that sets cannot be indexed.

Explore dictionaries as a mapping type, a collection of key value pairs, and learn the syntax with practical examples like a student dictionary.

Learn to create and inspect Python dictionaries with key-value pairs, using string, int, float, and boolean types, via curly braces and the dict() function.

Learn how to manipulate Python dictionaries: fetch keys and values with keys, values, and get; remove items with pop; inspect length with len; and update with nested dictionaries.

Explore the none type and its role as a null value representing the absence of value, with an example like x = None.

Learn to initialize an unassigned variable in Python with None. See how None maps to NoneType and can be a default parameter.

Explore Python data types—from int and float to bool, string, list, tuple, set, and dict—along with core operations like indexing, slicing, appending, and None.

Learn how to use the string format in Python by dynamically inserting variables into fixed text, using multiple approaches demonstrated in a practical session.

Explains practical string formatting in Python with the format function, using positional and named arguments to update name, age, and GPA while keeping the rest of the text fixed.

Learn string formatting using the percentage operator in Python, including %s, %d, and %f placeholders, with practical examples of names and ages.

Learn how to format strings with f-strings in Python 3.6+, using placeholders for name and age to produce messages like 'my name is Muhammad and I am 13 years old'.

Explore practical string formatting in python, including format function with placeholders, positional and key-value arguments, percent formatting, and f-strings for dynamic text.

Learn how to collect inputs from the end user with the input function in the console window. It returns a string and can be converted to other data types later.

Learn how to collect end user inputs, display prompts, store values in variables, and tailor messages like welcome with a name and the given number.

Take multiple inputs from the end user by prompting for first name and last name, then print the full name by combining the two inputs.

Capture end-user input with prompts using the input function, convert to a string or number as needed, and concatenate first and last names like Steve Jobs.

Explore how comments in programming languages are ignored by the compiler yet stay inside the code to aid understanding and future reference, including disabling comments without affecting execution.

Explore practical how-to of comments in Python and R by using hash for single-line comments and triple quotation for multiline blocks, understanding how commenting affects code execution and future readability.

Learn how comments are ignored by the interpreter, do not affect program functionality, and can disable code, using single-line hash or multi-line triple-quoted styles that can start anywhere.

Learn typecasting or type conversion, converting data types such as int to float, float to int, and string to int, and vice versa.

Convert a string or float to int using the int function, showing type checks, printed results, and decimal truncation, and noting that invalid strings raise errors.

Learn to convert strings and integers to floats using the float function, with examples like '75.5' becoming 75.5 and 75 becoming 75.0, plus a note on invalid inputs.

Learn to convert int and float to strings in Python using the str function, with practical examples and type checks to show data type changes.

learn how to convert python user input from string to int or float using int() and float(), show default string behavior and how non-numeric input raises errors.

Explore typecasting in Python by converting between string, int, and float using int, float, and str functions, including converting user input and practical examples.

Explore Python operators, including arithmetic, augmented assignment operators, comparison, logical, membership, and identity operators, and learn how to apply them across projects.

Learn how arithmetic operators power Python math, including addition, subtraction, multiplication, division, modulus, and exponentiation; review a chart linking symbols to their functions and see their use in real-time projects.

Learn arithmetic operators practically by applying addition, subtraction, multiplication, division, modulus, and exponentiation, understand base and exponent with double stars, and see how plus handles string concatenation and variables.

Explore augmented assignment operators that update a variable by applying arithmetic operations to its current value, using shorthand forms like +=, -=, *=, /=, %=, and **=.

Learn augmented assignment operators in Python, using both long and short forms (x = x + 5 and x += 5), including add, subtract, multiply, divide, modulus, and exponentiation.

Learn how comparison operators in python and r compare operands to yield booleans, including equals, not equals, greater than, less than, greater than or equals, and less than or equals.

Master Python comparison operators by evaluating values and variables with ==, !=, >, <, >=, and <=, yielding boolean results of true or false.

Explore logical operators in Python and R, including and, or, and not; learn how they evaluate boolean values and expressions to produce true or false results.

Explore how to use logical operators in Python and R by evaluating booleans, operands, and boolean expressions with and, or, not, and comparison operators.

Explore the in and not in membership operators to test if a value exists in a string, list, or tuple, returning true when found and false otherwise, with practical examples.

Explore Python membership operators with a practical num list example, using in and not in to check values like 3 and 6, and see how variables affect membership results.

Explore identity operators, checking whether two variables refer to the same object using is and is not, and determine when values are identical or not.

Demonstrates how identity operators determine if objects are the same, using lists x, y, and z to reveal true identity for identical objects and false for distinct ones.

Master Python operators from arithmetic to logical, including augmented assignment, comparison, membership, and identity operators, with practical usage of plus, minus, star, slash, modulus, and exponentiation.