Learn Python Fast and Easy Way

Install Anaconda to create a Python development environment with access to over 1000 data science packages, including Jupyter notebooks, on Windows, Mac, or Linux, with guided setup.

Explore installing Anaconda to set up Python and Jupyter Notebook, launch in your browser, write and run simple Python code, practice variables, strings, and basic concepts.

Explore variables, assignments, and printing in Python using practical notebook practice. Master arithmetic, relational and bitwise operators, division, modulo, and rounding to strengthen core programming foundations.

Explore binary operations in Python, including binary and hexadecimal representations, bit shifts, and converting numbers with hex(); examine complex numbers with abs, and use divmod and isinstance for type checks.

Learn isinstance type checks for int, float, complex, and long; perform comparisons, use power and modulo, and apply range with loops alongside input, raw_input, and print to build a calculator.

Learn to use basic Python data structures, including lists, tuples, and sets, explore mutability and immutability, and review common operations like union, intersection, and difference in a Jupyter Notebook.

Learn practical data structures in Python by building and manipulating lists, accessing elements by index, checking length, and exploring negative indexing in a notebook.

Learn to work with nested lists in Python, access and slice elements, and perform common list operations like length, max, min, concatenation, count, and membership checks.

Explore Python data structures: lists, tuples, and sets. Learn tuple immutability, indexing and slicing, and set operations like union and intersection, including how sets remove duplicates.

Explore Python strings from basics to slicing, searching, and indexing, and learn practical string operations, including find, index, and regular expressions, within notebooks.

Explore Python strings with notebook examples, covering endswith, count, join and split, case conversion to lowercase or uppercase, replace, and strip variants with optional start and end indices.

Explore dictionaries in Python by mapping employee id keys to employee objects and performing core key-value operations. Learn to convert lists to dictionaries with zip and inspect keys and values.

Master control flow in Python by using if, else, nested conditions, and loop constructs like for and while, with break and continue to manage execution.

Explore Python control flow with range, for loops, and nested lists, learn shorthand list creation, and apply if conditions to produce and print results.

Define functions with the def keyword, pass multiple arguments, return values (or None), and document them with docstrings while using lambda, map, and filter in Python.

Explore how to return multiple values from Python functions, use implicit arguments with defaults, and harness lambda functions with map and filter to transform lists.

Explore Python object oriented programming by building classes, using constructors and self, creating objects and instances, and calling methods to manipulate class attributes.

Explore object oriented programming in Python by building a simple calculator class, adding instance attributes, using self, and implementing square, cube, and multiplication methods with multiple values.

Create an advanced calculator by inheriting from the simple calculator to reuse base operations, then extend with square and factorial math using the math library.

Learn Python basics by installing Python 2.7 with Anaconda, exploring variables, data structures, functions, control statements, loops, and object-oriented programming, with hands-on notebooks and practice.