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Computability, Complexity & Algorithms

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Brief Introduction

You will learn a wealth of tools and techniques that will help you recognize when problems you encounter in the real-world are intractable and when there an efficient solution. This can save you countless hours that otherwise would have been spent on a fruitless endeavor or in re-inventing the wheel.

Course Summary

Learn about the theory of computability, complexity, and algorithms with this course from Udacity. Explore the limits of what is computable and gain a deeper understanding of algorithms and their efficiency.

Key Learning Points

Understand the theory of computability and its limits
Learn about complexity theory and the different classes of problems
Gather knowledge on algorithms and their efficiency
Develop problem-solving skills
Explore real-world applications of theoretical concepts

Job Positions & Salaries of people who have taken this course might have

- USA: $102,280
- India: ₹651,292
- Spain: €32,000
- USA: $102,280
- India: ₹651,292
- Spain: €32,000
- USA: $120,931
- India: ₹806,749
- Spain: €41,000
- USA: $102,280
- India: ₹651,292
- Spain: €32,000
- USA: $120,931
- India: ₹806,749
- Spain: €41,000
- USA: $90,920
- India: ₹546,278
- Spain: €27,000

Learning Outcomes

Understanding of the limits of computability
In-depth knowledge of complexity theory
Ability to analyze and design efficient algorithms

Prerequisites or good to have knowledge before taking this course

Basic understanding of computer science
Knowledge of programming languages

Course Difficulty Level

Intermediate

Course Format

Online self-paced course
Video lectures
Hands-on projects
Quizzes and assessments

Similar Courses

Algorithms and Data Structures
Introduction to Theoretical Computer Science

Notable People in This Field

Professor of Computer Science
Professor Emeritus of Computer Science

Related Books

Description

Learn tools and techniques that will help you recognize when problems you encounter are intractable and when there an efficient solution.

Requirements

Students are expected to have a solid grasp of the basics of discrete mathematics. Discrete Mathematics and Its Applications by Ken Rosen provides an excellent background for this course. If you answer "no" to any of the following questions, it may be beneficial to acquire background knowledge concurrently or prior to taking the course. Can you show that the sum of the first n numbers is n(n+1)/2? Can you give the proof as an induction on n? Can you give an O(n log n) algorithm for sorting n numbers? Can you describe the difference between breadth-first and depth-first search? Given an nxn matrix A and an n-dimensional vector b, can you give a polynomial-time algorithm to find a vector x such that Ax=b? See the Technology Requirements for using Udacity.

Knowledge

Instructor videosLearn by doing exercisesTaught by industry professionals

Outline

lesson 1 Computability Languages & Countability Turing Machines The Church-Turing Thesis lesson 2 Complexity P and NP NP-Complete Problems The Golden Ticket lesson 3 Algorithms Dynamic Programming Fast Fourier Transform Maximum Flow

Summary of User Reviews

Read reviews of the Computability, Complexity & Algorithms course at Udacity. Students enjoyed the comprehensive curriculum and engaging lectures. However, some found the assignments to be too challenging and the course pace to be too fast.

Key Aspect Users Liked About This Course

comprehensive curriculum

Pros from User Reviews

Engaging lectures that kept students interested
In-depth coverage of important topics in computer science
Challenging assignments that helped students grow their skills

Cons from User Reviews

Course pace was too fast for some students
Difficult assignments caused frustration for some
Not enough opportunities for interaction with instructors or classmates
Some students found the course to be too theoretical and abstract

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