Category: Data structure iit

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Data structure iit

02.12.2020 Data structure iit

Data Structures are the programmatic way of storing data so that data can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way. This tutorial will give you a great understanding on Data Structures needed to understand the complexity of enterprise level applications and need of algorithms, and data structures. As applications are getting complex and data rich, there are three common problems that applications face now-a-days.

If the application is to search an item, it has to search an item in 1 million 10 6 items every time slowing down the search. As data grows, search will become slower. To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.

Algorithm is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output.

Algorithms are generally created independent of underlying languages, i.

Online course on data structure by IIT Bombay

This tutorial is designed for Computer Science graduates as well as Software Professionals who are willing to learn data structures and algorithm programming in simple and easy steps. After completing this tutorial you will be at intermediate level of expertise from where you can take yourself to higher level of expertise. Before proceeding with this tutorial, you should have a basic understanding of C programming language, text editor, and execution of programs, etc.

Previous Page Print Page. Next Page.Data structures help you organize and process your data. There are many different ways of implementing them depending on available resources and whims of the programmerbut here are the general ideas behind them:. The type of data structure you want to use will often be determined by how quickly you need to be able to do certain things to the data and how often, with compromises sometimes made for hardware or network restrictions.

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A stack is a data structure that supports first-in-last-out access to elements, meaning the most recently added element is the first to be removed. Stacks have two main operations, namely Push and Pop.

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Push adds an element to the top of the stack, while Pop removes the element at the top of the stack. You can think of it as a stack of plates: you can 'push' additional items onto the stack of plates or 'pop' plates from the top of the stack. Think of a linked list as a series of boxes called nodes in a row. Each piece of information or set of information is put into one box with a pointer to the next box.

A doubly linked list is one that also has pointers that go back the other way to the previous box. They have head and tail pointers to help you keep track of where the beginning and end are, and usually at least one pointer that moves around the inside of the structure to point at a box to help you keep your place as you look for things.

For example, suppose you wanted to keep the names, addresses, and birthdays of your friends in a linked list. Each node would have one friend's name, address, and birthday in it, plus a pointer to the next in the list. If you want, the list can be sorted as you add friends to it, based on their name, address, or birthday in whatever way you want.

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If you know that some friends are more important to you and you don't want to go through the whole list to look for them every time, you can add in another variable for each person that can be used to set a sorting priority. A Queue is a data structure that provides first-in-first-out access to elements.

The two basic operations are Enqueue and Dequeue. Enqueue adds an element to the back of the Queue. Dequeue removes an element from the front of the queue. Just like a line at the supermarket, a Queue only supports adding items to the back and removing them from the front. In addition, some implementations allow you to 'peek' at the item in front without removing it. You can think of a tree structure as a linked list with more than one outgoing pointer per node.

This way, it branches out and the ends are called leaves instead of tails.

CS 331: Data Structures and Algorithms (01)

The top node is called the root and the branches, like a real tree, don't merge back together. Thus, the nodes all have one incoming pointer and zero or more outgoing pointers, depending on the type of tree, its location within it, and the set of data that is shaping the tree.

There are three main ways to process data in a tree. Recursion is usually the simplest way to perform such a task, where "traverse left" and "traverse right" below are recursive functions calls with the left and right children, respectively. Data structures lecture notes from University of Maryland, College Park.Introduction to data structure course is a free online course offered by IITx Bombay, this course enables to understand data structures which provide a means to manage large amounts of data for use in databases and internet indexing services.

It is globally recognized for its quality education and strong research programs. Admissions are made through national competitive entrance examinations, considered to be the toughest in India.

Its residential campus is home to over students, faculty members, 14 departments, 6 centers, and 3 interdisciplinary programs. The research program in Education Technology attempts to evolve the most effective learning-teaching processes.

Several national mission projects are handled by the Institute.

data structure iit

Training is offered to teachers on a large scale - up to 10, teachers at a time - using a unique blended mode. Thousands of Careerindia readers receive our evening newsletter. Have you subscribed? By Divya. For Quick Alerts. Subscribe Now. India - 14, World - 2, For Daily Alerts. Allow Notifications. You have already subscribed.

Apply Offline Before April Colleges Exams. G Diploma M. Phil Ph.Stuart Building, Room 10 W. Chicago, IL Computers have changed what we do and how we do it in our homes, in our offices, and throughout our world. The discipline of computer science focuses upon the many challenging problems encountered in the development and use of computing systems and software. Areas of study in computer science range from theoretical analyses into the nature of computing and computing algorithms, through the development of advanced computing devices and networks, to the design and implementation of sophisticated software systems.

The department offers two undergraduate programs in core computer science: a Bachelor of Science B. Both core computer science programs provide an excellent background in the field and allow for ample study in other areas.

Where these programs differ is in the approach they take to computer science. The B. Both programs begin with a set of introductory courses that work together to provide students with a firm foundation in computer science. These introductory courses include regular labs wherein students analyze and solve a variety of problems using accepted software development techniques.

Having completed the introductory core, a student is prepared to work independently within a well-structured design and coding paradigm in the classroom or on the job. The last two years of study build upon this foundation.

Students in this program explore the conceptual underpinnings of computer science—its fundamental algorithms, programming languages, database systems, operating systems, and software engineering techniques. In addition, students choose from a rich set of electives including artificial intelligence, machine learning, biometrics, cloud computing, data mining, natural language processing, computer vision, computer graphics, information retrieval, information security, intelligent text analysis, knowledge management systems, and mobile application development, among others.

Students can opt to complete one of the computer science specializations: data science, distributed and cloud computing, information security, or information and knowledge management systems.

An allotment of free electives allows students to combine study in computer science with study in another field to complete a minor. Students in this program pursue an interdisciplinary course of study that combines a solid foundation in computer science with a focus in another discipline.

This program is designed for students who seek to blend their computer science abilities with skills specific to another domain to solve problems in that domain.

Examples include computing with a business focus e. The program starts with introductory courses in programming, computer science, mathematics, and statistics that provide students with a firm technical foundation. Students are then prepared to learn core AI concepts and techniques including state-space search, game-playing, machine learning, neural networks, planning, computer vision, and language understanding.

CS 331: Data Structures and Algorithms

For breadth of understanding necessary in this interdisciplinary field, students choose from a diverse set of advanced courses in cognitive science, philosophy of mind, and linguistics, and also must complete a minor in another area. Given the societal impact of AI, emphasis is placed on ethics and social responsibility throughout the coursework.

The program also includes a large variety of advanced AI electives to enable students to develop technical mastery in specific sub-fields. The mission statement for the Department of Computer Science may be found on the Department of Computer Science website. The Department of Computer Science also offers the following co-terminal degrees, which enables a student to simultaneously complete both an undergraduate and graduate degree in as few as five years:.

Data Structures for Graphs - Data Structure and Algorithms - NPTEL - IIT-OCW

These co-terminal degrees allow students to gain greater knowledge in specialized areas while, in most cases, completing a smaller number of credit hours with increased scheduling flexibility.This course will cover introduction to digital computers, basics of programming, how to program in C and finally, the different constructs in C-programming langauges.

As the data struttures, we shall cover arrays, linke list, stack, queue, trees and graphs. How to implement some standard algorithms in C-language also will be covered. An outline of the course is as follows. You can also download the Course Calendar for your reference.

Moodle, an online course management system, will be used extensively in this course. You should sign up for the course Moodle at the earliest. Once you click on the link, you would be redirected to the CSE home page where you would find a link for signing up at the bottom of the page.

In case of any doubt on the subject matter and topics covered in the class, you are welcome to participate in the Discussion Forum and post your query. We would get back to you with a response as soon as possible.

Moreover, your friends can help answer your query too! Discussions in the forum may be moderated. Toggle navigation Menu Programming and Data Structures. Click here to see your mark. Solutions to all practice sheets are also available now. Please click the link "Resources". After completing this course, you will learn how to: Computer and its working Basics of C-Programming Standard data structures Sorting and searching algorithm Problem solving skills.

Syllabus An outline of the course is as follows. Kernighan and Dennis M. Ritchie, Prentice Hall of India. Samanta, Prentice Hall of India Additionally, you may look at the following materials. Course Instructor: Dr. Debasis Samanta Dr. Samanta at:. Sreeja g Moodle Moodle, an online course management system, will be used extensively in this course. The End-Sem marks has been announced.

The End-Semester Test will be held as per the schedule given below: Date: The Class Test -2 and Mid-Sem marks have been announced.

The Class Test -I marks have been announced. The Mid-Semester Test will be held as per the schedule given below: Date: The Class Test - I will be held as per the schedule given below: Date: The first class of the course will be held as per the schedule given below: Date: Dictionaries; skip-lists, hashing, analysis of collision resolution techniques.

Trees, traversals, binary search trees, optimal and average BSTs.

data structure iit

Tries and suffix trees. Priority queues and binary heaps. Sorting: merge, quick, radix, selection and heap sort, Graphs: Breadth first search and connected components.

Depth first search in directed and undirected graphs. Disjkra's algorithm, directed acyclic graphs and topological sort. Some geometric data-structures. The language used will be Java. It is expected that you will learn it on your own and will not be covered in any detail class. You are responsible for protecting your design and code against access by others.

Do not leave it where others can find it.

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Do not give it to someone for submission on your behalf. Do no use any fragment of code obtained online or from someone else. Falsifying program output or results is cheating also.

If your submission matches code in our database or another submission, you will be penalized as described below. Students who are caught cheating in an assignment will be given marks in that assignment. Cheating during exams earns marks.

A second violation earns an F. Be aware that code analysis tools will be used on every assignment to detect cases of cheating.

Please see your professor if you have any questions about what is permissible. Late policy: You are allowed up to 24 hours of late submission for each assignment, with a penalty of 1 mark. Submissions later than that will not be graded. Textbook Goodrich, M. Teaching Assistants: TBA.Students M. Tech B.

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Tech Dual Degree B. Tech Join Us! Tech DD M. One objective is to ensure that the student evolves into a competent programmer capable of designing and analyzing implementations of algorithms and data structures for different kinds of problems.

data structure iit

The second objective is to expose the student to the algorithm analysis techniques, to the theory of reductions, and to the classification of problems into complexity classes like NP.

Outcomes: By the end of the course, the students will be able to : design and analyze programming problem statements.

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Randomized Algorithms. Randomized Quicksort, Analysis of Hashing algorithms. Algorithm Analysis Techniques - Amortized Analysis. Application to Splay Trees. Algorithm Analysis and Design Techniques. NP-Completeness and Reductions. Text Books: Introduction to Algorithms, by T. Cormen, C. Lieserson, R. Rivest, and C. Reference Books: Algorithms, by S.

Dasgupta, C. Algorithm Design, by J. Klienberg and E. Tardos, Pearson Education Limited. Website Credits. Parameters Credits.


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