Spezialisierung Algorithmen
Learn To Think Like A Computer Scientist. Master the fundamentals of the design and analysis of algorithms.
von
Kompetenzen, die Sie erwerben
Über dieses Spezialisierung
Praktisches Lernprojekt
Learners will practice and master the fundamentals of algorithms through several types of assessments. Every week, there is a multiple choice quiz to test your understanding of the most important concepts. There are also weekly programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. Each course concludes with a multiple-choice final exam.
Einige einschlägige Kenntnisse erforderlich.
Einige einschlägige Kenntnisse erforderlich.
Es gibt 4 Kurse in dieser Spezialisierung
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
Graph Search, Shortest Paths, and Data Structures
The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
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).
von

Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Häufig gestellte Fragen
Erhalte ich akademische Leistungspunkte für den Abschluss der Spezialisierung?
Can I just enroll in a single course?
Kann ich mich auch nur für einen Kurs anmelden?
Can I take the course for free?
Kann ich kostenlos an diesem Kurs teilnehmen?
Findet dieser Kurs wirklich ausschließlich online statt? Muss ich zu irgendwelchen Sitzungen persönlich erscheinen?
Wie lange dauert es, die Spezialisierung abzuschließen?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
Erhalte ich akademische Leistungspunkte für den Abschluss der Spezialisierung?
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