MSML606

Algorithms and Data Structures for Machine Learning

Prerequisite: MSML605. Provides both a broad coverage of basic algorithms and data structures. Topics include sorting, searching, graph and string algorithms; greedy algorithm, branch-and-bound, dynamic programming and job scheduling; Arrays, linked lists, queues, stacks, and hash tables; Algorithm complexity, best/average/worst case analysis. Applications selected from machine learning problems.

Spring 2026

Samet Ayhan

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Sujeong Kim

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Summer 2025

Manoj Franklin

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Average rating: N/A

Sujeong Kim

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Spring 2025

Samet Ayhan

0 reviews
Average rating: N/A

Sujeong Kim

0 reviews
Average rating: N/A

Past Semesters

Manoj Franklin

0 reviews
Average rating: N/A

Manoj Franklin

0 reviews
Average rating: N/A

Manoj Franklin

0 reviews
Average rating: N/A

Samet Ayhan

0 reviews
Average rating: N/A

Include P/F semesters During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.06 between 115 students*

A-: 7.83%

A: 23.48%

A+: 8.7%

B-: 8.7%

B: 16.52%

B+: 11.3%

C-: 0.87%

C: 4.35%

C+: 11.3%

D-: 0.87%

D: 0.87%

F: 2.61%

W: 2.61%

* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.