expand activity instructions and fix syllabus link

activities.md

@@ -10,14 +10,20 @@ has_children: false
 
 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.
+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:
+We will use [GitHub](https//github.com) as a class submission portal for each programming activity. To get started with GitHub, please set up a project repository, initiate a README, and create two folders where you can upload completed notebooks and reflections for each programming activity.
 
-- one **~250 word reflection** in Markdown (e.g., `a1_reflection.md`)
-- one completed Jupyter notebook (e.g., `a4_notebook.ipynb`).
+**[See here for an example](https://github.com/zmuhls/ccny-coding-portfolio/tree/main)**
+
+### GitHub Instructions
+
+1. Create a new repository: Go to GitHub and create a new repository for your project. Name it appropriately, like `social-coding-portfolio`. . <br>
+2. Add a README: In the repository, add a README.md file. This file serves as an introduction and should outline the purpose of the repository, its structure, and any important information.<br>
+3. Create folders: Create two folders: `Notebooks` for Jupyter Notebook files and `Reflections` for Markdown reflections. [Click here](https://stackoverflow.com/questions/12258399/how-do-i-create-a-folder-in-a-github-repository) for guidance on how to create folders on GitHub.<br>
+4. Commit your work: Upload each submission as two files (one .ipynb in `Notebooks` and one .md in `Reflections`) and commit them with descriptive messages.<br>
 
 ### Activity 1: Building Blocks
 

syllabus.md

@@ -19,7 +19,7 @@ This course does <strong>not</strong> satisfy degree requirements for Computer S
 
 ## 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 a practical introduction to the Python programming language within the context of 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.