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zmuhls · Sep 12, 2024 · 81928ae · 81928ae
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diff --git a/.DS_Store b/.DS_Store
diff --git a/activities.md b/activities.md
@@ -6,45 +6,45 @@ has_children: false
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 - # Low-Stakes Activities
 
-  ## Collaborative Annotations
-  
-  For critical readings linked in the [schedule](/schedule.md), please use Hypothesis to annotate the text so that you can share your insights with peers and myself as part of our private annotation group. Annotations should range from 25 to 75 words, focusing on analytical depth, stylistic clarity, and interaction with peers. Hypothesis will serve not only as a platform for engaging with readings but also as a tool for managing and reflecting on scholarly information. 
-  
-  If you have not yet joined our private annotation group or cannot see your annotations, please do not hesitate to contact me; failing that, check out the [Hypothesis help](https://web.hypothes.is/help/) portal for support.
-  
-  ## Programming Activities
-  
-  Upload your work to the "Activities" folder of your portfolio project on GitHub and commit two files for each submission:
-  
-  * one **~250 word reflection** in Markdown (e.g., `a1_reflection.md`)
-  * one completed Jupyter notebook (e.g., `a4_notebook.ipynb`).
-  
-  #### Activity 1: Building Blocks
-  
-  - Due: 09/26 (Thur) 
-  - Downloadable [Instructions: Activity 1](https://colab.research.google.com/github/zmuhls/CCNY-Data-Science/blob/main/assets/activities/activity_1.ipynb)
-  - Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
-  
-  #### Activity 2: Python Primer
-  
-  - Due: 10/17 (Thur)
-  - Downloadable [Instructions: Activity 2](https://colab.research.google.com/github/zmuhls/CCNY-Data-Science/blob/main/assets/activities/activity_2.ipynb)
-  - Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
-  
-  #### Activity 3: Practicing Pandas
-  
-  - Due: 11/07 (Thur)
-  - Downloadable [Instructions: Activity 3](https://colab.research.google.com/github/zmuhls/CCNY-Data-Science/blob/main/assets/activities/activity_3.ipynb)
-  - Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
-  
-  #### Activity 4: Writing Docs
-  
-  - Due: 11/14 (Thur)
-  - Downloadable [Instructions: Activity 4](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/activities/activity_4.md)
-  - Submission format: .md (Markdown) and .ipynb (Jupyter Notebook) 
-  
-  #### Activity 5: Data Visualization
-  
-  - Due: 11/26 (Tue)
-  - Downloadable [Instructions: Activity 5](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/activities/activity_5.pdf)
-  - Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
+## Collaborative Annotations
+
+For critical readings linked in the [schedule](https://zmuhls.github.io/ccny-data-science/schedule/), please use Hypothesis to annotate the text so that you can share your insights with peers and myself as part of our private annotation group. Annotations should range from 25 to 75 words, focusing on analytical depth, stylistic clarity, and interaction with peers. Hypothesis will serve not only as a platform for engaging with readings but also as a tool for managing and reflecting on scholarly information.
+
+If you have not yet joined our private annotation group or cannot see your annotations, please do not hesitate to contact me; failing that, check out the [Hypothesis help](https://web.hypothes.is/help/) portal for support.
+
+## Programming Activities
+
+Upload your work to the "Activities" folder of your portfolio project on GitHub and commit two files for each submission:
+
+- one **~250 word reflection** in Markdown (e.g., `a1_reflection.md`)
+- one completed Jupyter notebook (e.g., `a4_notebook.ipynb`).
+
+### Activity 1: Building Blocks
+
+- Due: 09/26 (Thur)
+- Downloadable [Instructions: Activity 1](https://colab.research.google.com/github/zmuhls/ccny-data-science/blob/main/assets/activities/activity_1.ipynb)
+- Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
+
+### Activity 2: Python Primer
+
+- Due: 10/17 (Thur)
+- Downloadable [Instructions: Activity 2](https://colab.research.google.com/github/zmuhls/ccny-data-science/blob/main/assets/activities/activity_2.ipynb)
+- Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
+
+### Activity 3: Practicing Pandas
+
+- Due: 11/07 (Thur)
+- Downloadable [Instructions: Activity 3](https://colab.research.google.com/github/zmuhls/ccny-data-science/blob/main/assets/activities/activity_3.ipynb)
+- Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
+
+### Activity 4: Writing Docs
+
+- Due: 11/14 (Thur)
+- Downloadable [Instructions: Activity 4](https://github.com/zmuhls/ccny-data-science/blob/main/assets/activities/activity_4.md)
+- Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
+
+### Activity 5: Data Visualization
+
+- Due: 11/26 (Tue)
+- Downloadable [Instructions: Activity 5](https://github.com/zmuhls/ccny-data-science/blob/main/assets/activities/activity_5.pdf)
+- Submission format: .md (Markdown) and .ipynb (Jupyter Notebook)
diff --git a/datasets.md b/datasets.md
@@ -7,15 +7,15 @@ nav_order: 05
 # Datasets
 For ease of retrieval, please make sure to save the datasets in the same folder as your Jupyter Notebook (.ipynb) file.
 
-- [Bellevue Almhouse Dataset](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/datasets/bellevue_almshouse_modified.csv)
-- [Refugee by Arrival Dataset](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/datasets/refugee-arrivals-by-destination.csv)
-- [Trans-Atlantic Slave Trade of Americas Dataset](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/datasets/Trans-Atlantic-Slave-Trade_Americas.csv)
-- [U.S. Inaugural Addresses Dataset](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/datasets/US_Inaugural_Addresses.zip)
-- [Trump Twitter Archive](https://github.com/zmuhls/CCNY-Data-Science/blob/main/assets/datasets/Trump-Tweets_2009-2021.csv)
+- [Bellevue Almhouse Dataset](https://github.com/zmuhls/ccny-data-science/blob/main/assets/datasets/bellevue_almshouse_modified.csv)
+- [Refugee by Arrival Dataset](https://github.com/zmuhls/ccny-data-science/blob/main/assets/datasets/refugee-arrivals-by-destination.csv)
+- [Trans-Atlantic Slave Trade of Americas Dataset](https://github.com/zmuhls/ccny-data-science/blob/main/assets/datasets/Trans-Atlantic-Slave-Trade_Americas.csv)
+- [U.S. Inaugural Addresses Dataset](https://github.com/zmuhls/ccny-data-science/blob/main/assets/datasets/US_Inaugural_Addresses.zip)
+- [Trump Twitter Archive](https://github.com/zmuhls/ccny-data-science/blob/main/assets/datasets/Trump-Tweets_2009-2021.csv)
 - [Social Network Datasets](https://github.com/melaniewalsh/sample-social-network-datasets)
 - [Data 8 List of Datasets](https://github.com/data-8/textbook/tree/main/assets/data)
 
-Except for Data 8's list of datasets, the one used in class are retrieved from Melanie Walsh's [Introduction to Cultural Analytics & Python](https://melaniewalsh.github.io/Intro-Cultural-Analytics/00-Datasets/00-Datasets.html) and related work of hers on GitHub. 
+The datasets used in class (except for Data 8's list) are retrieved from Melanie Walsh's [Introduction to Cultural Analytics & Python](https://melaniewalsh.github.io/Intro-Cultural-Analytics/00-Datasets/00-Datasets.html) and her related work on GitHub.
 
 The _COVID-19 Vaccine Twitter Archive_ is modified from [Gabriel Preda's COVID-19 All Vaccines Tweets dataset](https://www.kaggle.com/datasets/gpreda/all-covid19-vaccines-tweets).
 
diff --git a/overview.md b/overview.md
@@ -20,7 +20,7 @@ The competencies learned in this course will provide students with skills that w
 
 ## Course Materials 🗂️
 
-All required reading materials, activities, and instructions are provided on the [Schedule](https://zmuhls.github.io/CCNY-Data-Science/schedule/) page. Additionally, datasets are provided on the [Datasets](https://zmuhls.github.io/CCNY-Data-Science/datasets/) page, and assets for the course website are hosted [here](https://github.com/zmuhls/ccny-data-science). 
+All required reading materials, activities, and instructions are provided on the [Schedule](https://zmuhls.github.io/ccny-data-science/schedule/) page. Additionally, datasets are provided on the [Datasets](https://zmuhls.github.io/ccny-data-science/datasets/) page, and assets for the course website are hosted [here](https://github.com/zmuhls/ccny-data-science). 
 
 **Technical Readings**: These readings draw from Melanie Walsh's open-access [Introduction to Cultural Analytics and Python ](https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html)(2021), an online textbook written for students in humanities and social sciences to gain hands-on experience with the Python programming language within the context of critical-cultural analysis. The textbook demonstrates how Python can be applied to a wide range of cultural materials, such as magazine articles, classic novels, TV scripts, technical manuals, social networks, and so more.