Advanced Algorithms (Fall 2005)

Prof. David R. Karger, MIT OpenCourseWare

This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.

  • Free schedule
Course properties:
  • Free:
  • Paid:
  • Certificate:
  • MOOC:
  • Video:
  • Audio:
  • Email-course:
  • Language: English Gb


No reviews yet. Want to be the first?

Register to leave a review

More on this topic:
6-826s02 Principles of Computer Systems
6.826 provides an introduction to the basic principles of computer systems,...
6-046jf05 Introduction to Algorithms (SMA 5503)
This course teaches techniques for the design and analysis of efficient algorithms...
18-238f02 Geometry and Quantum Field Theory
Geometry and Quantum Field Theory, designed for mathematicians, is a rigorous...
Lkq5d-g-umgnk574hji50bkwklgwosqb37yrfyqnh6jqfravvrdppxyufbqfejrkgls-tkeblf43omuuefw=s0#w=436&h=268 Intro to Parallel Programming. Using CUDA to Harness the Power of GPUs
Learn the fundamentals of parallel computing with the GPU and the CUDA programming...
6-896s04 Theory of Parallel Hardware (SMA 5511)
6.896 covers mathematical foundations of parallel hardware, from computer...
More from 'Mathematics, Statistics and Data Analysis':
41e295ce-a84b-4952-a9a7-fa613201d896-43f61d701b2e.small Pre-University Calculus
Prepare for Introductory Calculus courses. Mathematics is the language of Science...
15eed4cc-21c1-4107-80a0-d1057bc8f7ea-186b2ed21c9c.small Operations Research: an Active Learning Approach
Learn the methodology and some prominent techniques of Operations Research to...
55126a5c-2302-483d-b1a1-b32a6e0a997e-f263a2d19516.small Data Science for Construction, Architecture and Engineering
This course introduces data science skills targeting applications in the design...
17920e6b-e3ed-4819-8116-e48854e62cce-90b16a034656.small Deep Learning with Python and PyTorch
This course is the second part of a two-part course on how to develop Deep Learning...
7b2ecb24-2874-402b-ad86-473e246cae0c-aa0d4ca8dc73.small RiceX Linear Algebra Part 1
This course is an introduction to linear algebra. You will discover the basic...
More from 'MIT OpenCourseWare':
1-00s12 Introduction to Computers and Engineering Problem Solving
This course presents the fundamentals of object-oriented software design and...
1-010f08 Uncertainty in Engineering
This course gives an introduction to probability and statistics, with emphasis...
1-011s11 Project Evaluation
1.011 Project Evaluation covers methodologies for evaluating civil engineering...
1-012s02 Introduction to Civil Engineering Design
1.012 introduces students to the theory, tools, and techniques of engineering...
1-017f03 Computing and Data Analysis for Environmental Applications
This subject is a computer-oriented introduction to probability and data analysis...

© 2013-2019