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Wade Fagen-Ulmschneider

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.

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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 to the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science prepare for the Online MCS Entrance Exam. The Online MCS Entrance Exam allows applicants who do not have graded and transcripted prerequisite CS coursework in the areas of data structures, algorithms, and object-oriented programming to strengthen their applications for admission. Learn more about the Online MCS Entrance Exam.

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What's inside

Three courses

Object-Oriented Data Structures in C++

(0 hours)
This course teaches learners how to write a program in the C++ language. It covers setting up a development environment, writing and debugging C++ code, and implementing data structures as C++ classes.

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. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.

Unordered Data Structures

The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets, and graphs. These fundamental data structures are useful for unordered data, such as a hash table that provides immediate access to data indexed by an arbitrary key value or a graph that represents relationships between items.

Learning objectives

  • Design and implement an object-oriented program in the c++ language, including defining classes that encapsulate data structures and algorithms.
  • Select and implement appropriate data structures that best utilize resources to solve a computational problem.
  • Analyze the running time and space needs of an algorithm, asymptotically to ensure it is appropriate at scale, including for big data.
  • Prepare for advanced courses in cs with the foundational knowledge of object data structures needed to implement and call advanced library functions.

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