Complete Python Bootcamp for Data Science in 2026

Explore how comments in Python document code, using single line, inline, and multi-line styles; learn to use hash symbols and triple quotes to improve readability and explainability.

Explore Python's basic data types—integers, floats, and complex numbers, plus booleans and strings—learn how to declare them, use print, and inspect types with type().

Explore implicit and explicit Python type casting, learn how Python auto-converts int, float, and bool, and use built-in functions to convert string, list, tuple, and set, including nested forms.

Explore Python string indexing and slicing by applying positive and negative indices, end index plus one rule, and step values to fetch characters, slices, and reverse sequences.

Explore list indexing and slicing in Python, using positive and negative indexes to fetch single or multiple elements, apply steps, and reverse a list.

learn to index and slice tuples in Python and fetch single or multiple elements using positive and negative indexes, including reversing tuples and understanding end and step rules.

Explore creating a dictionary and retrieving values by keys using indexing, slicing, and the get method. Practice accessing skills and languages and specific items by index.

Explore Python arithmetic operators, including addition, subtraction, multiplication, division, exponential, flow division, and modulus, with practical examples on numbers, lists, tuples, and strings.

Master Python assignment operators, including plus equals, minus equals, and multiply equals, to update variables like salary with increments, decrements, and 5% hike.

Explore Python comparison operators, including equal, not equal, greater than, less than, and greater than or equal to and less than or equal to with true or false results.

Create lists in Python with brackets or the list function; lists are ordered, mutable, and allow duplicates, and use len, max, min, sum, range, and enumerate.

Explore creating tuples with parentheses or the tuple() function in Python, accessing via indexing and slicing, and using functions like length, max, min, sum, range, and enumerate, noting immutable nature.

Master python set basics: create sets with curly braces or set(), note they are unordered and store unique values, with immutable elements; use add, discard, remove, pop, clear, union, intersection.

Explore Python dictionaries, learn how to create and access keys and values, and master methods such as keys, values, items, get, update, setdefault, pop, popitem, clear, and delete.

Explore how simple and compound statements form the foundation of Python control flow, and learn how if, else, elif, and nested if enable decision making.

Explore Python's if statement, its syntax with a colon and indentation, and how to evaluate conditions to print outcomes or make decisions based on true or false.

Master Python for loops and iterators, using range and iterable types like lists, tuples, sets, dictionaries, and strings. Apply examples such as printing values, squaring numbers, and filtering even numbers.

Explore practical for loop problems in Python, from summing sequences and products to factorials, character counts, and data-type conversions used in data science tasks.

Learn to solve Python pattern problems with for loops, printing square, right-angle, inverted, pyramid, and diamond patterns using string multiplication and careful spacing.

Master break and continue in Python loops to control iteration. Use break to stop on conditions, continue to skip elements, with prime and palindrome examples.

Master while loops by learning to initialize a counter, set a stopping condition, and increment each step, contrasting them with for loops and examples like printing hello five times.

Define and use custom functions with the def keyword, parameters, and return statements, and compare them with built-in Python functions while learning defaults and docstrings.

Compare print and return in Python, showing how return sends a value back to the caller for storage and reuse, while print merely displays output.

Explore how to write flexible Python functions with *args for positional arguments and **kwargs for keyword arguments. Learn to sum any number of values and pass key-value pairs using items.

In this lecture, explore custom function practice problems in Python, including summing list elements, finding common elements between lists, removing duplicates, and generating factorial and Fibonacci values.

Explains lambda functions as small anonymous one-line expressions in Python, with syntax and examples for squaring numbers, adding numbers, checking positivity, even/odd, and palindromes, plus limits.

Explore how the map function applies a function to every element of an iterable, using lambda for in-line logic and examples like squaring numbers, uppercasing strings, and even/odd classification.

Explore how the Python filter function selects iterable elements with a predicate, returning a filter object that can become a list, with examples like even numbers and palindromes.

Explore the reduce function from a module to cumulatively apply a function to an iterable, yielding a single value, with examples for sums, products, and joining words.

Explore Python comprehensions to build lists, sets, and dictionaries from iterables with single-line expressions, for loops, and optional if conditions; learn examples like filtering values over 500 and computing squares.

Explore object oriented programming as a system built around real world objects to create organized, reusable, and maintainable code through encapsulation, inheritance, polymorphism, and abstraction.

Create class and define object shows building a house class with design, floors, and rooms, objects, and accessing attributes; extend to a calculator class with add, subtract, multiply, and divide.

Learn how class variables stay constant across all objects, while instance variables vary per object, initialized by the init constructor using self, with circle and employee examples.

Encapsulation wraps data and methods into a single unit and restricts direct access to class components, as shown by an ATM that hides balance with private data and controlled methods.

Explore polymorphism in Python by using the same method name across rectangle and triangle classes to compute areas, and see how the plus operator adapts for numbers and strings.

Learn how abstraction hides background details to focus on what a thing does, using abstract base classes and abstract methods to enforce implementation in concrete calculators like addition and multiplication.