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‎README.md

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@@ -37,7 +37,7 @@ In [Computing in Context](https://computing-in-context.afeld.me/), students "exp
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- [Attendance: 12%](#attendance)
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- [Lab work](labs/): 24% (12 x 2% each)
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- Reading responses: 24% (12 x 2% each)
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- [Project](docs/project.md): 40% (divided into eight-ish parts, split to be determined)
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- [Project](docs/project.md): 40% (divided into nine-ish parts, split to be determined)
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There will not be an exam.
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## Schedule
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| Week | Lecure date | Lecture topic(s) | Assignments due (at the start of lecture) | [Lab](labs/) topic(s) | [Lab](labs/) due (at the start of the Lab session) |
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| ---- | ----------- | ----------------------------------------------------------------- | ------------------------------------------------------------------------- | -------------------------------------------------------------- | -------------------------------------------------- |
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| 1 | 1/23 | [Welcome; collaborating on code (GitHub)](lectures/lecture_01.md) | none | [Computer setup; Git workflow](labs/lab_01.md) | none |
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| 2 | 1/30 | [Project/product management](lectures/lecture_02.md) | [Readings](readings/week_02.md) | [Jupyter, pandas, and visualization refresher](labs/lab_02.md) | none |
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| 3 | 2/6 | [Command line; dependency management](lectures/lecture_03.md) | [Readings](readings/week_03.md), [Project Part 1](docs/project.md#part-1) | [Project setup](labs/lab_03.md) | [Lab 2](labs/lab_02.md) |
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| 4 | 2/13 | [Web development](lectures/lecture_04.md) | [Readings](readings/week_04.md) | [Building an API](labs/lab_04.md) | [Lab 3](labs/lab_03.md) |
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| 5 | 2/20 | [Automated testing](lectures/lecture_05.md) | [Readings](readings/week_05.md), [Project Part 2](docs/project.md#part-2) | [Data profiling/quality](labs/lab_05.md) | [Lab 4](labs/lab_04.md) |
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| 6 | 2/27 | [Organizing code](lectures/lecture_06.md) | [Readings](readings/week_06.md), [Project Part 3](docs/project.md#part-3) | [Continuous integration](labs/lab_06.md) | [Lab 5](labs/lab_05.md) |
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| 7 | 3/6 | [Databases](lectures/lecture_07.md) | [Readings](readings/week_07.md) | [Databases](labs/lab_07.md) | [Lab 6](labs/lab_06.md) |
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| 8 | 3/13 | [Guest speaker; data warehousing](lectures/lecture_08.md) | [Project Part 4](docs/project.md#part-4) | [Data loading](labs/lab_08.md) | [Lab 7](labs/lab_07.md) |
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| 9 | 3/20 | none ([Spring Recess][recess]) | none | none ([Spring Recess][recess]) | none |
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| 10 | 3/27 | [Data engineering (pipelines, ETL)](lectures/lecture_10.md) | [Project Part 5](docs/project.md#part-5) | [Data loading, continued](labs/lab_10.md) | [Lab 8](labs/lab_08.md) |
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| 11 | 4/3 | Project presentations; infrastructure / cloud computing | [Readings](readings/week_11.md), [Project Part 6](docs/project.md#part-6) | TBD | [Lab 10](labs/lab_10.md) |
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| 12 | 4/10 | Big data; algorithms | [Readings](readings/week_12.md) | TBD | TBD |
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| 13 | 4/17 | Privacy | [Readings](readings/week_13.md) | TBD | TBD |
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| 14 | 4/24 | buffer | TBD | TBD | TBD |
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| 15 | 5/1 | buffer | TBD | TBD | TBD |
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| Week | Lecure date | Lecture topic(s) | Assignments due (at the start of lecture) | [Lab](labs/) topic(s) | [Lab](labs/) due (at the start of the Lab session) |
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| ---- | ----------- | ---------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- | -------------------------------------------------------------- | -------------------------------------------------- |
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| 1 | 1/23 | [Welcome; collaborating on code (GitHub)](lectures/lecture_01.md) | none | [Computer setup; Git workflow](labs/lab_01.md) | none |
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| 2 | 1/30 | [Project/product management](lectures/lecture_02.md) | [Readings](readings/week_02.md) | [Jupyter, pandas, and visualization refresher](labs/lab_02.md) | none |
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| 3 | 2/6 | [Command line; dependency management](lectures/lecture_03.md) | [Readings](readings/week_03.md), [Project Part 1](docs/project.md#part-1) | [Project setup](labs/lab_03.md) | [Lab 2](labs/lab_02.md) |
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| 4 | 2/13 | [Web development](lectures/lecture_04.md) | [Readings](readings/week_04.md) | [Building an API](labs/lab_04.md) | [Lab 3](labs/lab_03.md) |
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| 5 | 2/20 | [Automated testing](lectures/lecture_05.md) | [Readings](readings/week_05.md), [Project Part 2](docs/project.md#part-2) | [Data profiling/quality](labs/lab_05.md) | [Lab 4](labs/lab_04.md) |
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| 6 | 2/27 | [Organizing code](lectures/lecture_06.md) | [Readings](readings/week_06.md), [Project Part 3](docs/project.md#part-3) | [Continuous integration](labs/lab_06.md) | [Lab 5](labs/lab_05.md) |
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| 7 | 3/6 | [Databases](lectures/lecture_07.md) | [Readings](readings/week_07.md) | [Databases](labs/lab_07.md) | [Lab 6](labs/lab_06.md) |
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| 8 | 3/13 | [Guest speaker; data warehousing](lectures/lecture_08.md) | [Project Part 4](docs/project.md#part-4) | [Data loading](labs/lab_08.md) | [Lab 7](labs/lab_07.md) |
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| 9 | 3/20 | none ([Spring Recess][recess]) | none | none ([Spring Recess][recess]) | none |
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| 10 | 3/27 | [Data engineering (ETL)](lectures/lecture_10.md) | [Project Part 5](docs/project.md#part-5) | [Data loading, continued](labs/lab_10.md) | [Lab 8](labs/lab_08.md) |
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| 11 | 4/3 | [Project presentations; data engineering, continued (pipelines)](lectures/lecture_11.md) | [Readings](readings/week_11.md), [Project Part 6](docs/project.md#part-6) | TBD | [Lab 10](labs/lab_10.md) |
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| 12 | 4/10 | Infrastructure / cloud computing | [Readings](readings/week_12.md), [Project Part 7](docs/project.md#part-7) | TBD | TBD |
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| 13 | 4/17 | Big data; algorithms | [Readings](readings/week_13.md) | TBD | TBD |
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| 14 | 4/24 | Privacy | [Readings](readings/week_14.md), [Project Part 8](docs/project.md#part-8) | TBD | TBD |
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| 15 | 5/1 | Presentations | [Project Part 9](docs/project.md#part-9) | TBD | TBD |
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[recess]: https://registrar.columbia.edu/content/academic-calendar?acfy=49&acschool=18&acterm=6&field_event_type1_tid%255B%255D=23&keys=#!#e=9806
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‎docs/project.md

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- All team members are contributing equal amounts.
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- The Project leverages at least one [dataset that's regularly updated](data.md#datasets-that-are-regularly-updated).
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- The site doesn't need to [read like a blog post](https://computing-in-context.afeld.me/projects.html#requirements) necessarily, but it should explain what's going on.
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- By the end, this should be a polished portfolio piece.
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- _More to come_
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## [Teams](project_teams.csv)
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Next lecture, each group will do a presentation on their Project.
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### Requirements
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- 5-10 minutes
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- 5-8 minutes
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- Slides optional
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- Everyone in the group should speak.
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- Explain the initial [proposal](#proposal) and how it's evolved.
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- Show the live app.
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- Walk through the code.
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- Talk through any findings, even if they're just initial.
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This is meant to be "the quick version" — we'll do longer ones at the end.
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## Part 7
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_IN PROGRESS_
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Set up Airflow
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## Part 8
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_IN PROGRESS_
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Continued work on the Project
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## Part 9
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_IN PROGRESS_
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You'll do a longer version of [the earlier presentation](#presentation).

‎lectures/lecture_10.md

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## Pipelines
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Useful for complex ETL
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---
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## [Airflow](https://airflow.apache.org/)
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There are many alternative "data integration" tools.
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---
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## [Project Part 6](../docs/project.md#part-6)

‎lectures/lecture_11.md

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# Lecture 11
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**Data engineering, continued**
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---
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## [Presentations](../docs/project.md#presentation)
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---
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## Pipelines
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Useful for complex ETL
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---
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## [Airflow](https://airflow.apache.org/)
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There are many alternative "data integration" tools.
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---
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## [Project Part 7](../docs/project.md#part-7)

‎readings/week_11.md

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- [Append Load vs Incremental Load vs Truncate and Load](https://medium.com/@santosh_beora/the-3-most-commonly-used-etl-processes-explained-through-everyday-analogies-a7aa9f7a3754)
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- [Timing Function[s] in Python](https://builtin.com/articles/timing-functions-python)
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- Pipeline assignment
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- Airflow
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- [Cracking the Cloud_Open](https://www.redhat.com/en/command-line-heroes/season-1/crack-the-cloud-open)
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- [Overview of Cloud Computing](https://dc.arcabc.ca/islandora/object/dc%3A54375?solr_nav%5Bid%5D=c0f46853d72e7e533f04&solr_nav%5Bpage%5D=0&solr_nav%5Boffset%5D=0), Chapters 1-2
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- Airflow
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Now [submit a response](../README.md#responses).

‎readings/week_12.md

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[General information](../README.md#readings)
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1. [Crash Course Computer Science: Algorithms](https://thecrashcourse.com/courses/intro-to-algorithms-crash-course-computer-science-13/)
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1. [Introduction to Sorting Algorithms in Python](https://realpython.com/courses/intro-sorting-algorithms/) through "Time Complexity Overview"
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1. [Quick sort](https://www.youtube.com/watch?v=ywWBy6J5gz8)
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- The specifics here aren't important, just giving you a visual of an algorithm.
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- Your response to this part can be an in-class recital 😉
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1. [Understanding Program Efficiency, Part 1](https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lecture-10-understanding-program-efficiency-part-1/)
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1. Optional: [Part 2](https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lecture-11-understanding-program-efficiency-part-2/)
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1. [How the Internet Really Works](../README.md#readings), Chapter 8 (pages 67-73)
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1. [Stitch Fix Algorithms Tour](https://algorithms-tour.stitchfix.com/)
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- [Cracking the Cloud_Open](https://www.redhat.com/en/command-line-heroes/season-1/crack-the-cloud-open)
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- [Overview of Cloud Computing](https://dc.arcabc.ca/islandora/object/dc%3A54375?solr_nav%5Bid%5D=c0f46853d72e7e533f04&solr_nav%5Bpage%5D=0&solr_nav%5Boffset%5D=0), Chapters 1-2
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Now [submit a response](../README.md#responses).

‎readings/week_13.md

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[General information](../README.md#readings)
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1. [50 Things That Made the Modern Economy: Public Key Cryptography](https://www.bbc.co.uk/programmes/p04vqrwy)
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1. [How the Internet Really Works](../README.md#readings), pages 46-51
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1. [Alexa Takes the Stand: Listening Devices Raise Privacy Issues](https://time.com/4766611/alexa-takes-the-stand-listening-devices-raise-privacy-issues/)
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1. [Study Reveals Extent of Privacy Vulnerabilities With Amazon's Alexa](https://news.ncsu.edu/2021/03/alexa-skill-vulnerabilities/)
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1. [Amazon Echo Dot Privacy & security guide](https://foundation.mozilla.org/en/privacynotincluded/amazon-echo-dot/)
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1. Complete [Digital Privacy and Security for Normal People](https://personal-security.afeld.me/) "Low-hanging fruit"
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1. [A simple way to anonymize data with Python and Pandas](https://dev.to/r0f1/a-simple-way-to-anonymize-data-with-python-and-pandas-79g)
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## Optional
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- [The Privacy Risks of Your Smart Speaker](https://vpnoverview.com/privacy/devices/privacy-risks-smart-speaker/)
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1. [Crash Course Computer Science: Algorithms](https://thecrashcourse.com/courses/intro-to-algorithms-crash-course-computer-science-13/)
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1. [Introduction to Sorting Algorithms in Python](https://realpython.com/courses/intro-sorting-algorithms/) through "Time Complexity Overview"
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1. [Quick sort](https://www.youtube.com/watch?v=ywWBy6J5gz8)
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- The specifics here aren't important, just giving you a visual of an algorithm.
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- Your response to this part can be an in-class recital 😉
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1. [Understanding Program Efficiency, Part 1](https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lecture-10-understanding-program-efficiency-part-1/)
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1. Optional: [Part 2](https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lecture-11-understanding-program-efficiency-part-2/)
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1. [How the Internet Really Works](../README.md#readings), Chapter 8 (pages 67-73)
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1. [Stitch Fix Algorithms Tour](https://algorithms-tour.stitchfix.com/)
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Now [submit a response](../README.md#responses).

‎readings/week_14.md

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# Week 14 readings
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[General information](../README.md#readings)
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1. [50 Things That Made the Modern Economy: Public Key Cryptography](https://www.bbc.co.uk/programmes/p04vqrwy)
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1. [How the Internet Really Works](../README.md#readings), pages 46-51
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1. [Alexa Takes the Stand: Listening Devices Raise Privacy Issues](https://time.com/4766611/alexa-takes-the-stand-listening-devices-raise-privacy-issues/)
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1. [Study Reveals Extent of Privacy Vulnerabilities With Amazon's Alexa](https://news.ncsu.edu/2021/03/alexa-skill-vulnerabilities/)
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1. [Amazon Echo Dot Privacy & security guide](https://foundation.mozilla.org/en/privacynotincluded/amazon-echo-dot/)
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1. Complete [Digital Privacy and Security for Normal People](https://personal-security.afeld.me/) "Low-hanging fruit"
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1. [A simple way to anonymize data with Python and Pandas](https://dev.to/r0f1/a-simple-way-to-anonymize-data-with-python-and-pandas-79g)
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## Optional
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- [Alexa and Third Parties' Reasonable Expectation of Privacy](https://www.law.georgetown.edu/american-criminal-law-review/aclr-online/volume-54/alexa-and-third-parties-reasonable-expectation-of-privacy/)
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- [The Privacy Risks of Your Smart Speaker](https://vpnoverview.com/privacy/devices/privacy-risks-smart-speaker/)
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Now [submit a response](../README.md#responses).

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