CSCI 3387 Topics in Computational intelligence: Machine Learning Projects

In this project based class, we will introduce several machine learning concepts, and illustrate and practice their use. These topics will, tentatively, include: classification, data processing, dimensionality reduction, model evaluation and tuning, ensemble learning, regression, clustering, multi layer artificial neural networks and their use for classification, regression, generative adversarial networks, and reinforcement learning.

Course overview

Department
Computer Science
School
MCAS
Credits
3
Level
Undergraduate
Offered
Periodically

Catalog details

Prerequisites
MATH2202 and MATH2210 or MCMA2210 and CSCI2243 or MATH2216 and CSCI2244 or MATH4426

Catalog text is imported from the reviewed Boston College course snapshot. Confirm eligibility in EagleApps.

Requirements fulfilled

  • Computer Science B.A.: CSCI 2000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
  • Computer Science B.A.: CSCI 3000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
  • Computer Science B.S.: CSCI 3000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
  • Mathematics B.S.: Natural science, computer science, or economics corequisites (Current University Catalog; students should confirm their catalog year)

Requirement eligibility can vary by school, cohort, and section. Confirm the selected section in EagleApps or with an advisor.

Official evaluation summary

2.87 / 5

Based on 56 aggregate responses from BC Avalanche/Blue evaluations.

Data freshness

Course and evaluation data last updated 2026-08-02. Source details and limitations are documented in Data Sources and Methodology.

Instructors

  • Jose Bento Ayres Pereira
    Fall 2026, Spring 2026, Spring 2025, Fall 2024, Spring 2024, Spring 2023 · Official rating 2.79/5

Sections

  • Section 01
    Fall 2026 · Jose Bento Ayres Pereira · 245 Beacon Street Room 104 MW 10:30AM-11:45AM · Offered