Python for Data Science - Great Learning

Install Python from the official site and set up an integrated development environment. Install Anaconda for preloaded data science packages and run your first Python program in a Jupyter notebook.

Learn how variables act as temporary storage in Python, perform assignments, change values, and explore data types such as integers, floats, booleans, strings, and complex numbers.

Learn arithmetic, relational, and logical operators in python using variables, comments, and expressions like + - * / with < > == != and or logic.

Python strings are sequences of characters enclosed by single, double, or triple quotes for multiline text, and you can index, slice, measure length, and transform with upper, lower, and title.

Explore non-primitive data structures in Python, focusing on tuples as immutable, ordered collections that can hold heterogeneous elements; learn to create, index into them, and respect immutability.

Explore lists in Python, learn how lists are mutable compared to tuples, create lists with square brackets, access via indexing and slicing, and modify with append, nested lists, and pop.

Learn to work with dictionaries and sets in python by managing key-value pairs, accessing keys and values, mutating dictionary entries, and understanding set properties like no duplicates and unordered iteration.

Explore Python if else control statements with real-world decision scenarios, comparing values, using multiple conditions to determine the greatest, and applying membership checks in tuples, lists, and dictionaries.

Learn how looping statements in Python repeat tasks until a condition is met using while loops, iterate over lists with for loops, and combine them in nested loops.

Define and invoke Python functions to reuse code, using hello world, a simple addition function, and odd/even checks, with an atm analogy for deposits, withdrawals, and balance.

Explore object oriented programming by modeling world objects with classes and objects, using properties and behavior as a blueprint. See inheritance in action as iPhone extends phone with extra features.

Explore numpy for multi-dimensional arrays, creating 1-D and 2-D arrays, initializing with zeros, full, arange, random values. Learn shaping, summing with axis, and stacking with vstack, hstack, and column_stack.

Learn to manipulate data with pandas using series and data frames, create from dictionaries, load files, inspect with head, tail, describe, and filter with iloc, loc, and boolean conditions.