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C Programming: Advanced Data Types

C Programming: Advanced Data Types

Master effective ways to store your data in the C programming language using advanced data types such as structures and linked lists. Receive instant feedback on your code right within your browser.

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  • English
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Accelerated Computer Science Fundamentals

Accelerated Computer Science Fundamentals

Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing and shortest paths. This Specialization sequence is designed to help prospective applicants prepare for the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science.

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  • English
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Data Structures and Algorithms

Data Structures and Algorithms

This course explores data structures and algorithms for back-end development, focusing on performance and scalability.

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  • English
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I/O-efficient algorithms

I/O-efficient algorithms

I/O-efficient algorithms, also known as external memory algorithms or cache-oblivious algorithms, are a class of algorithms designed to efficiently process data that is too large to fit entirely in the main memory (RAM) of a computer. These algorithms are particularly useful when dealing with massive datasets, such as those found in large-scale data processing, database management, and file systems. Operations on data become more expensive when the data item is located higher in the memory hierarchy.

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  • 10 hours
  • English
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Geometric Algorithms

Geometric Algorithms

Geometric algorithms are a category of computational methods used to solve problems related to geometric shapes and their properties. These algorithms deal with objects like points, lines, polygons, and other geometric figures. In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data.

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  • 18 hours
  • English
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Approximation Algorithms

Approximation Algorithms

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example, because the problems are NP-hard. The goal of the Approximation Algorithms course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations.

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  • 15 hours
  • English
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Data Structures and Performance

Data Structures and Performance

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. We recommend this course to learners who have previous experience in software development or a background in computer science, and in particular, we recommend that you have taken the first course in this specialization (which also requires some previous experience with Java).

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  • 42 hours
  • English
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Ordered Data Structures

Ordered Data Structures

In this course, you will learn new data structures for efficiently storing and retrieving data that is structured in an ordered sequence. Such data includes an alphabetical list of names, a family tree, a calendar of events or an inventory organized by part numbers. The specific data structures covered by this course include arrays, linked lists, queues, stacks, trees, binary trees, AVL trees, B-trees and heaps. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.

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  • 19 hours
  • English
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