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Problem Solving Using Computational Thinking
by Chris Quintana- 4.6
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Approx. 11 hours to complete
Have you ever heard that computers "think"? Believe it or not, computers really do not think. Instead, they do exactly what we tell them to do. Programming is, "telling the computer what to do and how to do it. " Thinking through problems this way is Computational Thinking. No prior programming is needed....
Computational Geometry
by Alexander S. Kulikov , Aliaksei Tolstsikau , Kira Vyatkina- 3.9
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Approx. 19 hours to complete
This course represents an introduction to computational geometry – a branch of algorithm theory that aims at solving problems about geometric objects. Its application areas include computer graphics, computer-aided design and geographic information systems, robotics, and many others. Point inclusion in a polygon 1. 1 Introduction 1. 2 Problem statement 1....
Big Data Analysis with Scala and Spark
by Prof. Heather Miller- 4.7
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Approx. 28 hours to complete
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala....
Cloud Computing Concepts, Part 1
by Indranil Gupta- 4.4
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Approx. 23 hours to complete
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises....
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
by Tim Roughgarden- 4.8
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Approx. 14 hours to complete
The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search). Week 1 Single-Source Shortest Paths, Revisted Optimal Substructure The Basic Algorithm I The Basic Algorithm II...
Number Theory and Cryptography
by Alexander S. Kulikov , Michael Levin , Владимир Подольский- 4.5
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Approx. 19 hours to complete
We all learn numbers from the childhood. Some of us like to count, others hate it, but any person uses numbers everyday to buy things, pay for services, estimated time and necessary resources. People have been wondering about numbers’ properties for thousands of years. Famous 20th century mathematician G. H. You will even pass a cryptographic quest!...
Combinatorics and Probability
by Alexander S. Kulikov , Владимир Подольский- 4.6
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Approx. 21 hours to complete
Counting is one of the basic mathematically related tasks we encounter on a day to day basis. The main question here is the following. If we need to count something, can we do anything better than just counting all objects one by one? All these questions are addressed by a mathematical field called Combinatorics....
Algorithms on Graphs
by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes- 4.7
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Approx. 55 hours to complete
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. In this course, you will first learn what a graph is and what are some of the most important properties. You will use these algorithms if you choose to work on our Fast Shortest Routes industrial capstone project....
Excel/VBA for Creative Problem Solving, Part 3 (Projects)
by Charlie NuttelmanTop Instructor- 4.9
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Approx. 16 hours to complete
In this course, learners will complete several VBA projects. It is highly recommended that learners first take "Excel/VBA for Creative Problem Solving, Part 1" and "Excel/VBA for Creative Problem Solving, Part 2". This course builds off of skills learned in those two courses. This is a project-based course. Getting Started Welcome...
Data Structures and Performance
by Christine Alvarado , Mia Minnes , Leo Porter- 4.8
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Approx. 42 hours to complete
How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course....
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