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CS 145: Data Management and Data Systems

Introduction to the use, design, and implementation of database and data-intensive systems, including data models; schema design; data storage; query processing, query optimization, and cost estimation; concurrency control, transactions, and failure recovery; distributed and parallel execution; semi-structured databases; and data system support for advanced analytics and machine learning. Prerequisites: 103 and 107 (or equivalent).
Terms: Aut | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci
Instructors: ; Shivakumar, N. (PI); Badrinath, A. (TA); Bradfield, A. (TA); Chang, J. (TA); Escandon, E. (TA); Li, R. (TA); Maheshwari, E. (TA); Wu, J. (TA)

CS 246: Mining Massive Data Sets

The availability of massive datasets is revolutionizing science and industry. This course discusses data mining and machine learning algorithms for analyzing very large amounts of data. Topics include: Big data systems (Hadoop, Spark); Link Analysis (PageRank, spam detection); Similarity search (locality-sensitive hashing, shingling, min-hashing); Stream data processing; Recommender Systems; Analysis of social-network graphs; Association rules; Dimensionality reduction (UV, SVD, and CUR decompositions); Algorithms for large-scale mining (clustering, nearest-neighbor search); Large-scale machine learning (decision tree ensembles); Multi-armed bandit; Computational advertising. Prerequisites: At least one of CS107 or CS145.
Terms: Win | Units: 3-4 | UG Reqs: WAY-FR
Instructors: ; Leskovec, J. (PI); Agrawal, A. (TA); Allavarpu, E. (TA); Garg, A. (TA); He, B. (TA); Jin, M. (TA); Khurana, A. (TA); Li, Y. (TA); Liu, Y. (TA); Siegel, S. (TA); Zhu, C. (TA)
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