Please note that this schedule is subject to change.

Calendar

Date Topic Readings Assignments
1/14 Introduction
1/16 Python McKinney, Ch.2-3
1/21 Python A1
1/23 Structured Data McKinney, Ch. 4
1/28 Data and Pandas McKinney, Ch. 5
1/30 Data Wrangling McKinney, Ch. 6 A2
2/04 Data Wrangling Kandel et al.
2/06 Data Cleaning McKinney, Ch. 7
2/11 Data Transformation Jin et al. Reading Response Due
2/13 Data Transformation McKinney, Ch. 8
2/18 Test 1 A3
2/20 Data Integration
2/25 Data Fusion Dong et al. Reading Response Due
2/27 Class Cancelled
3/03 Data Exploration Chapman et al.
3/05 Databases and Visualization
3/10 No Class
3/12 No Class
3/17 Class Cancelled
3/19 Class Cancelled
3/24 Scalable Databases Lakshman & Malik A4
3/26 Scalable Databases Corbett et al.
3/31 Data Curation Wilkinson et al.
4/02 Graph Data Angles
4/07 Time Series Data McKinney, Ch. 11
4/09 Test 2
4/14 Spatial Data Lins et al.
4/16 Provenance Freire et al. A5
4/21 Provenance Freire et al. 2
4/23 Reproducibility Collberg & Proebsting
4/28 Databases and Machine Learning Kraska et al.
4/30 Review
5/05 Final Exam (4-5:50pm)

Lectures

(01/14) Introduction
(01/16) Python
(01/21) Python
(01/23) Structured Data
(01/28) Data and Pandas
(01/30) Data Wrangling
(02/04) Data Wrangling
(02/06) Data Cleaning
(02/11) Data Transformation
(02/13) Data Transformation
(02/20) Data Integration
(02/25) Data Fusion
(03/03) Data Exploration
(03/05) Databases and Visualization
  • Combined with the Big Ideas lecture
(03/24) Scalable Databases
(03/26) Scalable Databases
(03/31) Data Curation
(04/02) Graph Data
(04/07) Time Series Data
(04/14) Spatial Data
(04/16) Provenance
(04/21) Provenance
(04/23) Reproducibility
(04/28) Databases and Machine Learning
(04/30) Review