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Dynamic Programming, Greedy Algorithms
Data Science Foundations: Data Structures and Algorithms,
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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| Rating | Not enough ratings |
|---|---|
| Length | 5 weeks |
| Effort | eight to fifteen hours a week for four weeks |
| Starts | Jun 26 (44 weeks ago) |
| Cost | $99 |
| From | University of Colorado Boulder via Coursera |
| Instructor | Sriram Sankaranarayanan |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Algorithms Software Development |
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| Rating | Not enough ratings |
|---|---|
| Length | 5 weeks |
| Effort | eight to fifteen hours a week for four weeks |
| Starts | Jun 26 (44 weeks ago) |
| Cost | $99 |
| From | University of Colorado Boulder via Coursera |
| Instructor | Sriram Sankaranarayanan |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Algorithms Software Development |
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