SlugAtlasUC Santa Cruz

NLP 220Data Science and Machine Learning Fundamentals

5 creditsGraduateStudent Option

Covers a broad set of tools and core skills required for working with Natural Language Data. Covers core traditional machine learning methods such as classification methods using Naive Bayes, SVMs, Linear regression and Support Vector Regression, as well as the use of Pytorch and other programming frameworks commonly used in the field. Also includes methods used for collecting, merging, cleaning, structuring and analyzing the properties of large and heterogeneous datasets of natural language, in order to address questions and support applications relying on those data. Course covers working with existing corpora as well as the challenges in collecting new corpora. (Formerly Data Collection, Wrangling and Crowdsourcing.)

Prerequisites

Enrollment is restricted to natural language processing graduate students.

  • Enroll in lecture and associated discussion section.

Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.

When it runs

Fall 2026Open Fall 2026

SectionTypeWhenWhereInstructorSeats
50Lecture
Mon Wed 1:30pm–3:05pm
SiliconValleyCtrL. De AlfaroOpen 16/34

Fall 2025Open Fall 2025

SectionTypeWhenWhereInstructorSeats
50Lecture
Mon Wed 1:30pm–3:05pm
SiliconValleyCtrL. De AlfaroOpen 31/45

Who teaches it

InstructorRatingDifficultyWould take againReviews
Luca De Alfaro3.3 / 53.4 / 559%71

From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.

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