About this course: Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.
Taught by: Luay Nakhleh, Associate Professor
Computer Science; Biochemistry and Cell Biology
Taught by: Scott Rixner, Professor
Computer Science
Taught by: Joe Warren, Professor
Computer Science
| Basic Info |
Course 6 of 7 in the
Fundamentals of Computing Specialization.
|
| Level | Intermediate |
| Commitment | 4 weeks of study, 7-10 hours/week |
| Language | English, Subtitles: Spanish |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Really like the mix of theory and practical application
This is a challenging course that teaches an invaluable problem solving approach, applicable in many domains.
Great course, problem solving oriented
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