Please note that this schedule is subject to change.

Calendar

Date Topic Readings Assignments
1/11 Introduction
1/13 Python McKinney, Ch.2-3
1/18 No Class
1/20 Python
1/25 Structured Data McKinney, Ch. 4 A1
1/27 Data and Pandas McKinney, Ch. 5
2/01 Data Wrangling McKinney, Ch. 6
2/03 Data Wrangling Kandel et al. A2
2/08 Data Cleaning McKinney, Ch. 7
2/10 Data Transformation Jin et al.
2/15 Data Transformation McKinney, Ch. 8 A3
2/17 Test 1
2/22 Data Integration
2/24 Data Fusion Dong et al.
3/01 Data Exploration Chapman et al.
3/03 Data Curation Wilkinson et al. A4
3/08 Data Citation
3/10 Scalable Databases Lakshman & Malik
3/15 Scalable Databases Corbett et al.
3/17 Graph Data Angles
3/22 Databases and Visualization Liu et al.
3/24 Spatial Data Lins et al.
3/29 Test 2
3/31 No Class
4/05 Time Series Data McKinney, Ch. 11 A5
4/07 Provenance Freire et al.
4/12 Provenance Freire et al. 2
4/14 Reproducibility Collberg & Proebsting
4/19 Databases and Machine Learning Kraska et al.
4/21 Review
4/26 Final Exam (4-5:50pm)

Lectures

(01/11) Introduction
(01/13) Python
(01/20) Python
(01/25) Structured Data
(01/27) Data and Pandas
(02/01) Data Wrangling
(02/03) Data Wrangling
(02/08) Data Cleaning
(02/10) Data Transformation
(02/15) Data Transformation
(02/22) Data Integration
(02/24) Data Fusion
(03/01) Data Exploration
(03/03) Data Curation
(03/08) Data Citation
(03/10) Scalable Databases
(03/15) Scalable Databases
(03/17) Graph Data
(03/22) Databases and Visualization
(03/24) Spatial Data
(04/05) Time Series Data
  • Slides
  • Reading: McKinney, Ch. 11
(04/07) Provenance
(04/12) Provenance
(04/14) Reproducibility
(04/19) Databases and Machine Learning
(04/21) Review