Schedule

Please note that this schedule is subject to change.

Calendar

Date Topic Readings Assignments
08/25 Introduction
08/27 Python Review Python Tutorial
09/01 No Class
09/03 Relational Databases A1
09/08 Relational Databases
09/10 Structured Data Polars Users Guide
09/15 Dataframes Polars Users Guide A2
09/17 Polars and DuckDB DuckDB in Action
09/22 Data Wrangling Kandel et al.
09/24 Data Wrangling Jin et al.
09/29 Data Transformation Yan & He
10/01 Data Cleaning Rekatsinas et al. A3
10/06 Data Integration
10/08 Test 1
10/13 Data Integration Stonebraker & Ilyas
10/15 Data Fusion Dong et al.
10/20 Scalable Databases Gessert et al. A4
10/22 Scalable Databases Pavlo & Aslett
10/27 Scalable Dataframes Petersohn et al.
10/29 Scalable Dataframes Jindal et al.
11/03 Time Series Data Pelkonen et al.
11/05 Graph Data Sahu et al.
11/10 Test 2
11/12 Databases and Visualization Heer & Moritz
11/17 Spatial Data Eldawy et al. A5
11/19 Data Curation Wilkinson et al.
11/24 Provenance Chapman et al.
11/26 No Class
12/01 Reproducibility Collberg & Proebsting
12/03 Databases and Machine Learning Kraska et al.
12/08 Final Exam (12-1:50pm)

Lectures

(08/25) Introduction
(08/27) Python Review
(09/03) Relational Databases
(09/08) Relational Databases
(09/10) Dataframes
(09/15) Dataframes
(09/17) Polars and DuckDB
(09/22) Data Wrangling
(09/24) Data Wrangling
(09/29) Data Transformation
(10/01) Data Cleaning
(10/06) Data Integration
(10/13) Data Fusion
(10/15) Data Fusion
(10/20) Scalable Databases
(10/22) Scalable Databases
(10/27) Scalable Dataframes
(10/29) Scalable Dataframes
(11/03) Time Series Data
(11/05) Graph Data
(11/12) Databases and Visualization
(11/17) Spatial Data
(11/19) Data Curation
(11/24) Provenance
(12/01) Reproducibility
(12/03) Databases and Machine Learning