Princeton University - Computer Science: Algorithms, Theory, and Machines
- Offered byCoursera
Computer Science: Algorithms, Theory, and Machines at Coursera Overview
Duration | 20 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Computer Science: Algorithms, Theory, and Machines at Coursera Highlights
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 20 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Computer Science: Algorithms, Theory, and Machines at Coursera Course details
- This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our intent is to demystify computation and to build awareness about the substantial intellectual underpinnings and rich history of the field of computer science.
- First, we introduce classic algorithms along with scientific techniques for evaluating performance, in the context of modern applications. Next, we introduce classic theoretical models that allow us to address fundamental questions about computation, such as computability, universality, and intractability. We conclude with machine architecture (including machine-language programming and its relationship to coding in Java) and logic design (including a full CPU design built from the ground up).
- The course emphasizes the relationships between applications programming, the theory of computation, real computers, and the field's history and evolution, including the nature of the contributions of Boole, Shannon, Turing, von Neumann, and others.
- All the features of this course are available for free. No certificate will be offered upon completion.
Computer Science: Algorithms, Theory, and Machines at Coursera Curriculum
INFORMATION ABOUT LECTURES 1?10
Information about Lectures 1?10
A typical client
Binary search
Insertion sort
Mergesort
Longest repeated substring
Getting Started
Supplements for Lecture 11
Optional Enrichment on Sorting and Searching
Sorting and Searching
STACKS AND QUEUES
APIs
Clients
Strawman implementations
Linked lists
Implementations
Supplements for Lecture 12
Optional Enrichment on Stacks and Queues
Stacks and Queues
SYMBOL TABLES
APIs and clients
A design challenge
Binary search trees
Implementation
Analysis
Supplements for Lecture 13
Optional Enrichment on Symbol Tables
Symbol Tables
INTRODUCTION TO THE THEORY OF COMPUTING
Overview
Regular Expressions
DFAs
Applications
Limitations
Supplements for Lecture 14
Optional Enrichment on Theory of Computing
Theory of Computing
TURING MACHINES
Context
A simple model of computation
Universality
Computability
Implications
Supplements for Lecture 15
Optional Enrichment on Turing Machines
Turing Machines
INTRACTABILITY
Reasonable questions
P and NP
Poly-time reductions
NP-completeness
Living with intractability
Supplements for Lecture 16
Optional Enrichment on Intractability
Intractability
A COMPUTING MACHINE
Overview
Data Types
Instructions
Operating the machine
Machine language programming
Supplements for Lecture 17
Optional Enrichment on A Computing Machine
A Computing Machine
VON NEUMANN MACHINES
Perspective
A note of caution
Practical implications
Simulation
Supplements for Lecture 18
Optional Enrichment on von Neumann Machines
von Neumann Machines
COMBINATIONAL CIRCUITS
Building blocks
Boolean algebra
Digital circuits
Adder circuit
Arithmetic/logic unit
Supplements for Lecture 19
Optional Enrichment on Combinational Circuits
Combinational Circuits
CENTRAL PROCESSING UNIT
Overview
Bits, registers, and memory
Program counter
Components and connections
Supplements for Lecture 20
Optional Enrichment on the CPU
CPU
Computer Science: Algorithms, Theory, and Machines at Coursera Admission Process
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