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Overview
Key Features
Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language.
In part 1 of this two-part Algorithmic Thinking (Part 1) course offered by Coursera in partnership with Rice University, we will study the notion of algorithmic efficiency and consider its application to several problems from graph theory.
As the central part of the course, students will implement several important graph algorithms in Python and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms.
Recommended Background - Students should be comfortable writing intermediate size (300+ line) programs in Python and have a basic understanding of searching, sorting, and recursion. Students should also have a solid math background that includes algebra, pre-calculus and a familiarity with the math concepts covered in "Principles of Computing".
Programme Structure
Courses include:
- What is Algorithmic Thinking?, class structure, graphs, brute-force algorithms
- Graph representations, plotting, analysis of citation graphs
- Asymptotic analysis, "big O" notation, pseudocode, breadth-first search
- Connected components, graph resilience, and analysis of computer networks
Key information
Duration
- Part-time
- 7 days
- 10 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Web Technologies & Cloud Computing View 408 other Short Courses in Web Technologies & Cloud Computing in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate Level
- This course is aimed at learners with intermediate Python and mathematical skills who want to develop a deeper understanding of algorithmic thinking and graph algorithms for analyzing real‑world data.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This short course is included with Coursera Plus subscription
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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