Python Fundamentals Bootcamp 2026: Beginner to Pro

Explore the fundamentals of Python programming, learn how to install Python, and master basic features such as conditional statements, loops, and functions to write and use Python code.

Empowers professionals pursuing careers in growing Python programming and analytics fields, including research professionals, data analysts, data scientists, BI and reporting professionals, and project managers.

Build your foundation in computer science concepts and sharpen logic formulas and skills as prerequisites for the Python fundamentals bootcamp 2025.

Discover why we need Python: its simple learning curve and base programming language status. Benefit from a community with open-source libraries for natural language processing, data science, and web development.

Explore why Python stands out among languages, with advantages for web development, scripting, and data science analysis, and tap into its vibrant open-source library community.

Discover how Python unlocks value for professionals by enabling real-time interactive data exploration and model development with open source libraries, supporting big data analytics, web development, scripting, and algorithm development.

Explore the course overview and prerequisites, understand why we need Python, compare Python with other languages, and highlight its value to professionals.

Define Python and explore the history of Python as you learn to set up the Python development environment. Explain how to call Python and receive various Python.

Explore Python as a general purpose, interpreted, interactive, object oriented, high level language for a variety of projects, including data mining and text manipulation.

Python combines strong, dynamically typed design with productive coding, reducing variable typing and enabling concise solutions compared with Java, powered by libraries for web development and big data.

Trace Python's history from Guido van Rossum's 1989 creation to its open-source evolution, highlighting its scripting roots, loops and functional programming, and the shift toward Python 3.0 libraries.

Learn how to install Python on an Ubuntu base machine using terminal commands, with notes on pre installed libraries and choosing 32-bit or 64-bit options for Linux and Windows installations.

Learn how to write simple Python programs, create a Hello World script in three steps, save the file, and run it in the terminal to see the output.

In Python fundamentals bootcamp 2025, learn two modes to run Python: script mode, writing all statements in one file and executing them, and interpreter mode, entering code line by line.

Run multiple python commands by using batch script mode, placing them in a .py file, then execute python <scriptname> in the terminal and press enter to run the code.

Learn to use Python in interpreter mode by opening a terminal and starting Python. Enter one line of code at a time as the Python cell starts.

Discover how Python enforces indentation to define blocks, avoid curly brackets, and improve readability, preventing errors from improper formatting.

Explain how to write comments in Python to improve readability as programs grow, documenting non-obvious features and why, using the number sign.

Explore how an IT operations executive from solid technologies considers using Python for a new project, and learn to start Python in interactive mode.

Explore Python as a general purpose interpreter that is interactive, object oriented, and high level. Learn its open source nature, major versions such as 2.7 and 3.9.7, its presence on Ubuntu, and two work modes: simple and interpreter mode.

Explore Python data types and variables, define operators and operands, and explain the relationship between operands and variables. Learn how arithmetic operations apply to numerical values.

Learn how variables hold values and how assignment creates new variables with values using the equals operator. Explore meaningful variable names, their purpose, and rules about length and case.

Explore the six basic Python variable types—string, integer, field, boolean, list, and dictionary—and learn how the type function reveals a variable’s type.

Learn to declare string variables in Python, storing text such as names and addresses. Verify types, concatenate strings, and print the resulting variables.

Explore numeric variables, including integers and decimals, as numeric types and real numbers. Use examples like age 27 and 3.14 to show two ways to use each type.

Learn how boolean variables in Python store true or false values to represent conditions. The lecture explains non empty data as true and empty structures, zero, or none as false.

Explore how lists compare to arrays, focusing on internal design and memory efficiency; learn how a single name can hold different typed values, as shown by a two-element country list.

Learn how to add multiple elements to a list using append and extend, and understand how passing a list differs between extending and appending with England and China as examples.

Access elements of a list by indexing with square brackets and zero-based positions. Demonstrate retrieving the first element, the fourth element, and sublists from the third index to the last.

Explore Python's dictionary data structure, a key-value store similar to a hash map, and learn accessing values by keys and creating an empty dictionary.

Add elements to a dictionary using assignment for single pairs and the update function for multiples, with immutable keys and values that can be lists, including colon syntax.

Learn how to access elements of a dictionary by supplying the exact key in square brackets, and retrieve the corresponding element quickly.

Explore dictionary methods in Python fundamentals by using key-based access and listing keys, values, and items to inspect stored data.

Explore Python fundamentals by examining operators, including addition, subtraction, multiplication, division, modulus, and exponentiation. The lecture shows a complete list of operators with examples in a table.

Explore how Python evaluates boolean expressions with and, or, and not. Learn how and requires all true, how or requires at least one true, and how not negates values.

Explore arithmetic operations on numeric values using operators with variables A and B in Python, including multiplication, addition, subtraction, division, and applying powers to create new variables.

Explore how Python applies operator precedence: parentheses first, then exponentiation, then multiplication and division, and finally addition and subtraction, with left to right evaluation for same precedence.

Explore how string operations work in Python fundamentals, including concatenation with the plus operator and replication via multiplication, and how operators behave with the same type variables.

Learn to compare variables using equality and inequality operators: equal sign, not equal, greater than, less than, and greater than or equal to, less than or equal to.

Explore Python variable types, including string, float, integer, and boolean, and how operators perform arithmetic with operands. Learn how operators evaluate true and false values and compare equality and inequality.

Define path segments in Python, describe the types of conditional segments and their uses in Python, and define the operators to master control statements.

Use a pass statement to create a placeholder when you have no code yet; it performs no operation. Maintain a valid, ready-to-expand body for future implementation.

Learn how conditional statements let a program check conditions and adjust its behavior. Practice using the if segment to execute statements when a condition like x > 0 is true.

Understand how if statements and other conditional forms shape decision making in programming, and preview topics to be covered in upcoming sessions.

Learn how Python if statements evaluate conditions to execute blocks, use if and else, compare values with >, >=, and ==, and build chained conditionals for grades.

Explore nested if statements by placing one condition inside another, such as checking location then age, where the second condition only evaluates if the first is true.

Learn to use the in clause to check if an element exists in a list, using a name list example to determine if Harry is in the list.

Explore 2.5 ternary operators and their syntax to assign values based on a condition, such as if B > 8 then X = 5 else X = 6.

Explore conditional statements that track conditions and change program behavior in Python, covering five types including if, if elif, and if elif else. The next lesson introduces loops.

Explore loops in Python fundamentals, define loops and the range function, and explain break and continue statements, with three loop types guiding sequential execution.

Explore how the range function in Python generates a sequence from 0 to n-1. See range(5) illustrates this by returning 0 through 4, reinforcing its use with loop statements.

Learn how to use a for loop with range to iterate from 1 to 10, assign value to a variable, and display it; apply to lists of strings and floats.

Explore the while loop by starting x at zero, printing x, and incrementing it by one to print values from zero to 200.

Explore how to use nested loops by placing a for loop inside another loop to solve problems, such as finding prime numbers less than 100.

Use a break statement to exit a loop when a condition is met, preventing infinite loops, and pair it with an if condition inside the loop.

The continue statement skips the rest of a loop iteration when a condition is met, demonstrated with a for loop and an if check.

Explore three types of loops in Python and how they control program flow. Learn how loop constructs manage values and continuous control to guide questions and set up next lesson.

Learn how to define a function, its advantages, and the steps to create and call a function, along with its uses.

Master how functions organize code into modular, reusable blocks in Python, create user defined functions, define a function as a named sequence of statements, and call it by name.

Learn to create functions in Python by using the def keyword, naming functions, passing optional parameters, and writing statements that run when called.

Define a function by name, parameters, and a code block in Python. Call it from another function or directly, using the function name followed by brackets and matching argument order.

Define a function with parameters, pass arguments, add them with the plus operator, and return the result. Also set default parameter values so missing arguments use defaults.

Explore recursion by seeing how a function can call itself to compute factorials, using a base case of n <= 1 and recursive multiplication for larger values.

Explore functions by defining and calling them from other functions, repeating actions with different values, as the function calls itself, and preview the next lesson on classes.

Define a class, explain how to add functions to a class, describe different class attributes, and discuss the advantages of creating a class in this Python fundamentals lesson.

Define classes and objects to model real-world things with properties and behavior, using car as an example with model, brand, and operations like start and brake.

Create multiple objects from a class and assign distinct values to each object's properties. Pass initial values to fix property values for different object instances.

Create a basic Python class using the class keyword and a class name, define properties like model name and brand name, and instantiate objects.

Learn to access an object's attributes in Python using the dot operator, print specific variables like the model name, and retrieve multiple fields from the same object through examples.

Learn how to add methods to a class by defining them inside, understand that Python automatically uses self, and call methods like start and stop without passing self.

Explore built-in class attributes, including the dictionary attribute for the class namespace and the class document in string form, plus the name, module attribute, and base group.

Explore Python's __init__ constructor, which initializes a new class instance, allocates object space, and assigns attributes via self, with methods called without passing self.

Define a Python class with attributes name and value, and a constructor that assigns the name from user input; create an object and call its method to return the value.

Learn object oriented basics by using classes as blueprints, creating multiple objects with distinct variable values, and initializing attributes with class constructors. Preview imports and modules.

Explore imports and modules, discuss their uses, and define global and local functions and packages.

Learn how modules organize Python code and make it easier to understand and reuse through import statements. A module is a Python file containing definitions of functions, classes, and variables.

Create modules by turning Python files into code units with variables, functions, and classes. Save the file as a module to use it across projects.

Learn how to turn any python source file into a module, selectively import variables, functions, and classes, and understand module loading once to prevent repeated execution.

When you import a module, the python interpreter searches a defined sequence: current module, then the environment variable, then the default part, with details stored in the system module.

Explore Python namespaces and scoping, distinguishing local from global scopes. See how local variables shadow globals and how to use the global statement.

Discover how the dir function returns a short list of module names. See how it uses a math module, sorts the results, and prints them.

Explore how global and local functions retain names in the global and local namespaces based on the call site. They return a dictionary whose keys reveal the accessible names.

Reload a module explains reloading a previously imported Python module with the reload function and when reimporting may not reload automatically.

Explore how a Python application is organized into packages and modules, create files to expose functions, and use explicit import statements to access classes and variables across modules.

Explore Python modules and imports, explain how a module is a Python file with variables and classes, and show how packages organize modules into directories.