ADVANCED ALGORITHMS
- Instructor: Anand Seetharam
- Open year round
- Delivery: Self-paced online, video lectures, self-assessment quizzes (not graded) and final exam (graded).
- Credentials: The participants who successfully complete the course by passing the final exam will receive the Advanced Algorithms digital badge and will be able to download/print a 黑料视频 issued course completion certificate.
- Who can take this course: This course is open to all engineers, professionals, faculty and students.
ABOUT THE COURSE
This course will provide a solid foundation and background to design and analysis of algorithms. In particular, upon successful completion of this course, students will be able to understand, explain and apply key algorithmic concepts and principles, including:
- Greedy algorithms (Activity Selection, 0-1 Knapsack Problem, Fractional Knapsack Problem)
- Dynamic programming (Longest Common Subsequence, 0-1 Knapsack Problem)
- Minimum Spanning Trees (Prim鈥檚 Algorithm, Kruskal鈥檚 Algorithm)
- Graph Algorithms (Dijkstra鈥檚 Shortest Path Algorithm, Bipartite Graphs, Minimum Vertex Cover)
- Theory of NP and NP-completeness
LEARNING OUTCOMES
At the end of the course, students will be able to:
- Describe and apply complex algorithmic paradigms including greedy algorithms and dynamic programming.
- Describe graphs using adjacency matrices and edge lists, and find the shortest path between vertices in a graph using Dijkstra鈥檚 algorithm.
- Find the minimum spanning tree in a graph using Prim鈥檚 algorithm and Kruskal鈥檚 algorithm.
- Explain and describe maximum matching in bipartite graphs as well as find the minimum vertex cover in a graph.
- Explain the concept of NP and NP-completeness as well as mathematically show that a problem is NP-complete.
ABOUT THE INSTRUCTOR
Anand Seetharam is an assistant professor in Computer Science in the Thomas J. Watson College of Engineering and Applied Science at 黑料视频. Dr. Seetharam is broadly interested in the field of computer networking. His research interests encompasses wireless networks, information-centric networks, ubiquitous computing, Internet of Things (IoT) and smart grids.
COURSE FEES
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$325: Standard/Industry Rate
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$210: BU Faculty, Staff and Alumni
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$135: BU Students and High School Students
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$35: Retake Fee (BU Students)
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$50: Retake Fee (non-students)
PAYMENTS
Payment is made at the time of registration. For questions, contact the Office of Industrial Outreach at wtsnindy@binghamton.edu.
CANCELLATIONS AND REFUNDS
Please note our cancellation and refund policy: All cancellations must be received in writing (email) to the Office of Industrial Outreach. All refunds will be assessed a 10% administrative fee. No refunds for cancellations or non-attendance will be given after you have started the course. Submit your cancellation request to EMAIL: wtsnindy@binghamton.edu.
If the course is canceled, enrollees will be advised and receive a full refund.