Python & Data Structures

In this video, we would learn to work on Python, give inputs, and understand how to give comments. We would get introduced to the importance of Python.

Hands on session on Overview of Python concept using Notepad++

In this video we would learn about datatypes and operators. We would get introduced to decision making statements, loops,iterators and generators

Hands on Session on datatypes & Operators using Notepad++

In this video,we would learn about number, string, list, tuple build-in functions. We would get introduced to properties of dictionary, date and time functions and difference between shallow copy and deep copy

Hands on session on build-in functions of Python datatypes using Notepad++

In this video we would learn functions, modules and packages. We would get introduced to function arguments and scope of variables.

Hands on session on using Functions, Modules and Packages using Notepad++

In this video we would learn opening and closing of files, reading from files, writing to files, renaming files and deleting files.We would get introduced to dictionaries

Hands on session on Reading and Writing from files using Notepad++

In this video we would learn about assertions and exceptions. We would also understand How to raise an exception and create userdefined exceptions.

Hands on session on Assertions and Exceptions using Notepad++

This video explores fundamental data structures in Python, empowering you to organize and manipulate information effectively for your coding projects.

Understand How to use Google Colab ?

Will Code a Number Guessing Game and get introduced to various elements of Python

We would understand different Python keywords. As well rules of using them correctly.

Get a hands-on by executing the simple short programs on the 6 data types in Python , namely - Number,  String , List , Tuple, Set and Dictionary.

More on Datatypes

In this video, we will be working on membership & identity Operators and Decision Making.

Files are named locations on disk to store related information. We would Open a file, Read/Write to a file and finally close the file. Any runtime error is called Exceptions. We would use try-except block to handle Exceptions.

We would Open a file, Read/Write to a file and finally close the file. We would learn meaningful operations on file.

Any runtime error is called Exceptions. We would use try-except block to handle Exceptions.

We would learn different cases to understand When Exceptions happen and different ways to handle them.

We would get introduced to the different types of collections, Understand common operations on them -  LINEAR collections, HIERARCHICAL collections, GRAPH collections, UNORDERED collections, and SORTED collections.

Code using higher-order functions - map, filter, and reduce.

We would Determine the rate of growth of an algorithm in terms of its problem size. Understand how to use big-O notation to describe the running time and memory usage of an algorithm and Identify the complexity class of an algorithm -- is it CONSTANT, LOGARITHMIC, LINEAR, QUADRATIC OR EXPONENTIAL.

We learn and code - How much time in secs an Algorithm takes ?

We understand major problems in measuring actual times. Hence we find a better way to estimate the efficiency of the algorithm called - "Counting Instructions"

We estimate the efficiency of the algorithm by Counting Instructions.

We would develop a method for determining the efficiency of algorithms that allows us to rate them independently of platform-dependent timings or impractical instruction counts. This method, called complexity analysis, entails reading the algorithm and using pencil and paper to work out some simple maths.instruction counts. This method, called complexity analysis, entails reading the algorithm and using pencil and paper to work out some simple maths.

We will see several algorithms for searching and sorting lists. We will learn the design of an algorithm and then see its implementation as a Python function.Finally, you 'll see an analysis of the algorithm 's computational complexity.

We will see two important Data structures - ARRAYs and LINKED LIST. We will answer What are Arrays ?, How do they look ? and Where are they used ? As well What is a Linked List ? , How does it look ? and Where is the Linked list used ?

How to create Arrays and perform different Array operations.

Logic building using Arrays

Introduction to Linked List

Building operations on Linked list

Logic building using Linked List

We would learn What are Interfaces?, How to implement them? And What are Polymorphism and its use cases?

We would learn How to code an Abstract Class in Python and How to declare an Interface?

Polymorphism refers to the use of a single type entity , say a method, an operator or an object to behave differently in different scenarios. Lets understand this through practicals

Understand the difference between Method Overriding and Method Overloading via Coding.

We would ans Why does Python support Inheritance ?,Types Of Inheritance, and How to implement them in Python? And Few use cases.

Implementing Inheritance and solving few usecases

Implementing Inheritance via Abstract classes and solving few usecases

STACK is a LIFO data structure. It has 2 operations - PUSH and POP. We would understand How Real Time Applications of STACKS like String Reversal, Browser History, Undo/Redo operations in Excel or Word work.

Implementing Stack Code to solve some use cases.

A linked list is a data structure made of a chain of node objects. Each node contains a value and a pointer to the next node in the chain. Here we would understand some real life applications of Link list.

Trying build in functions on link list

Understanding some real life applications of Link list.

Trees are non-linear data structures that represent nodes connected by edges. In this module we would explore applications of Binary Search Tree(BST).

Coding BST and solving trees usecases

A graph data structure is a collection of nodes that have data and are connected to other nodes. We will see how facebook and google maps use Graph data structure.

We would understand on how to find many spanning trees from a single graph and then calculate the minimum spanning tree distance.

We would understand Prims and Krushals Algorithm to find the minimum spanning tree

Implementing Prims and Krushals Algorithm to find the minimum spanning tree