Introduction to algorithms and analysis

3,000.00

 

Prof. Sourav Mukhopadhyay

IIT Kharagpur

*Additional GST and optional Exam fee are applicable.

SKU: IIT Kharagpur Category:

Description

 

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

INTENDED AUDIENCE

UG,PG, B. Tech., M. Tech., M. Sc.

INDUSTRY SUPPORT

IT companies

ABOUT THE INSTRUCTOR

Sourav Mukhopadhyay is an Associate Professor, Department of Mathematics at Indian Institute of Technology Kharagpur. He has completed his B.Sc (Honours in Mathematics) in1997 from University of Calcutta, India. He has done M.Stat (in statistics) and M.Tech (in computer science) from Indian Statistical Institute, India, in 1999 and 2001 respectively. He worked with Cryptology Research Group at Indian Statistical Institute as a PhD student and received his Ph.D. degree in Computer Science from there in 2007. He was a Research Assistant at the Computer Science department of School of Computing, National University of Singapore (NUS). He visited Inria Rocquencourt, project CODES, France and worked as a post-doctoral research fellows at the School of Computer Engineering, Nanyang Technological University (NTU), Singapore. He was a post-doctoral research fellows and a part time Lecturer with School of Electronic Engineering, Dublin City University (DCU), Ireland.

Additional information

Institute

IIT KGP

Total hours

30

Certification Process

1. Join the course
Learners may pay the applicable fees and enrol to a course on offer in the portal and get access to all of its contents including assignments. Validity of enrolment, which includes access to the videos and other learning material and attempting the assignments, will be mentioned on the course. Learner has to complete the assignments and get the minimum required marks to be eligible for the certification exam within this period.

COURSE ENROLMENT FEE: The Fee for Enrolment is Rs. 3000 + GST

2. Watch Videos+Submit Assignments
After enrolling, learners can watch lectures and learn and follow it up with attempting/answering the assignments given.

3. Get qualified to register for exams
A learner can earn a certificate in the self paced course only by appearing for the online remote proctored exam and to register for this, the learner should get minimum required marks in the assignments as given below:

CRITERIA TO GET A CERTIFICATE
Assignment score = Score more than 50% in at least 9/12 assignments.
Exam score = 50% of the proctored certification exam score out of 100
Only the e-certificate will be made available. Hard copies will not be dispatched.”

4. Register for exams
The certification exam is conducted online with remote proctoring. Once a learner has become eligible to register for the certification exam, they can choose a slot convenient to them from what is available and pay the exam fee. Schedule of available slot dates/timings for these remote-proctored online examinations will be published and made available to the learners.

EXAM FEE: The remote proctoring exam is optional for a fee of Rs.1500 + GST. An additional fee of Rs.1500 will apply for a non-standard time slot.

5. Results and Certification
After the exam, based on the certification criteria of the course, results will be declared and learners will be notified of the same. A link to download the e-certificate will be shared with learners who pass the certification exam.

CERTIFICATE TEMPLATE

Course Details

Week 1: Sorting problem, time complexity, asymptotic analysis.
Week 2: Solving recurrence, Divide-and-Conquer.
Week 3: Quicksort and Heap Sort, Decision Tree.
Week 4: Linear time Sorting, Order Statistics.
Week 5: Hash Function, Binary Search Tree (BST) Sort.
Week 6: Randomly build BST, Red Black Tree, Augmentation of data structure.
Week 7: Van Emde Boas, Amortized analysis, Computational Geometry.
Week 8: Dynamic Programming, Graphs, Prim’s Algorithms.
Week 9: BFS & DFS, Shortest path problem, Dijktra, Bellman Ford.
Week 10: All pairs shortest path, Floyd-Warshall, Johnson Algorithm.
Week 11: More amortized analysis, disjoint set data structure.
Week 12: Network flow, computational complexity.

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