2nd Session- Big Data

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This session we deal with the following questions:

I. What is "big data"? 

II. What are the opportunities?

III. What are the limitations?

 

 

1- Lecture: Watch the following lectures and answer the interactive questions (which are graded). We recommend to use the following slide print-outs to take notes.

Download 1slidePerPage_UCCSS_Blumenstock.pdf

Download 3slidesPerPage_UCCSS_Blumenstock.pdf

Blumenstock

UCCSS_Blumenstock_1: Fighting Poverty with Data (7min)

UCCSS_Blumenstock_2: Extracting features (9min)

UCCSS_Blumenstock_3: Predicting Poverty (10min)

UCCSS_Blumenstock_4: Who Cares? (9min)

 

Download 1slidePerPage_UCCSS_2ndBigData_Hilbert.pdf

Download 3slidesPerPage_UCCSS_2ndBigData_Hilbert.pdf

I. What is "big data"?

UCCSS 2-01: Big Data lecture overview (2min)

UCCSS 2-02: What is "big data"? (14min)

II. What are the opportunities?

UCCSS 2-03: Digital Footprint (5min)

UCCSS 2-04: Political Data-fusion & No-sampling (19min)

UCCSS 2-05: Real-time (6min)

UCCSS 2-06: Machine Learning (5min)

UCCSS 2-07: ML Recommender Systems (11min)

III. What are the limitations?

UCCSS 2-08: Footprint ≠ Representativeness (10min)

UCCSS 2-09: Data ≠ Reality (6min)

UCCSS 2-10: Meaning ≠ Meaningful (5min)

UCCSS 2-11: Discrimination ≠ Personalization (9min)

UCCSS 2-12: Correlation ≠ Causation (7min)

UCCSS 2-13: Past ≠ Future (11min)

(total 2h 25min)

 

2- Lab:

You will web scrape two different YouTube channels with: http://webscraper.io Links to an external site.

First, get familiar with the task with help of this tutorial video: UCCSS_LAB_webscraping (29min) ; and this PDF tutorial: Download UCCSS_Lab_Webscraping.pdf

You find your individually assigned task here: 2nd Session- Web scraping task

If you run into problems, please feel free to ask questions in Piazza and/or coordinate with others through Study Groups Coordination .

 

 

Optional / Voluntary / Complementary: