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diff --git a/ArcGISPro.md b/ArcGISPro.md
@@ -4,43 +4,37 @@ title: Moving from ArcMap to ArcGIS Pro
 nav_order: 9
 ---
 
-## Making the Move from ArcMap to ArcGIS Pro
+<img src="assets/img/ArcMapArcPro.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/ArcMapArcPro.png" alt="Workshop Title Slide" width="720">
+# Making the Move from ArcMap to ArcGIS Pro
 
 Are you an ArcGIS Desktop user who is curious about the differences between ArcMap and ArcGIS Pro? This workshop is geared towards existing ArcMap users who are interested in making the switch to ArcGIS Pro and will cover topics such as: the timeline of support for ArcMap, licensing and access, differences and similarities between the two programs, and how to import files from ArcMap and share your content. 
 
-Presentation by Christine Homuth, Spatial Information (GIS) Specialist.
+Presentation by Christine Homuth, Spatial Information (GIS) Specialist.  
 [Get in touch with Christine.](https://library.mcmaster.ca/homuth-christine)
 
-# Workshop preparation 
+## Workshop preparation 
 
 Preparation for this tutorial consists of two steps: [Getting the software](#get-the-software) and [the data](#get-the-data). See below. 
 
-## Get the software
+### Get the software
 To follow along with the tutorial, you will require access to ArcGIS Pro.
 
 Current McMaster students, staff, and faculty can request a license for ArcGIS Pro through the [ArcGIS Software Request Form](https://library.mcmaster.ca/services/gis) available on the Library's website.
 
 [Free trials](https://www.esri.com/en-us/arcgis/products/arcgis-pro/trial) of the software are also available from Esri.
 
-## Get the data
+### Get the data
 This tutorial uses a sample .mxd file. You can choose to [download the sample .mxd](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap_to_ArcGISPro_MXD.zip) or work with your own file. 
 
-# Workshop Slides
+## Workshop Slides
 
-<div style="position:relative;padding-top:66.25%;">
-<iframe src="//docs.google.com/viewer?url=https://github.com/scds/dash-webinars/raw/main/assets/docs/ArcMap-to-ArcGISPro-Slides.pdf?dl=0&hl=en_US&embedded=true" class="gde-frame" style="position:absolute;top:0;left:0;width:100%;height:100%;border:none;" scrolling="no"></iframe>
-</div>
+<embed src="assets/docs/ArcMap-to-ArcGISPro-Slides.pdf" style="border:none;" width="100%" height="466px">
 
-[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap-to-ArcGISPro-Slides.pdf)
-<br>
+[Download as PDF.](assets/docs/ArcMap-to-ArcGISPro-Slides.pdf)
 
-# Workshop Tutorial
+## Workshop Tutorial
 
-<div style="position:relative;padding-top:66.25%;">
-<iframe src="//docs.google.com/viewer?url=https://github.com/scds/dash-webinars/raw/main/assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf?dl=0&hl=en_US&embedded=true" class="gde-frame" style="position:absolute;top:0;left:0;width:100%;height:100%;border:none;" scrolling="no"></iframe>
-</div>
+<embed src="assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf" style="border:none;" width="100%" height="466px">
 
-[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf)
-<br>
+[Download as PDF.](assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf)
diff --git a/ArcGIS_Assistant.md b/ArcGIS_Assistant.md
@@ -34,9 +34,3 @@ Below are the steps involved in copying content between accounts using the ArcGI
 - _In some cases content is copied as a reference to the original source item; in other cases the content is migrated over to the second account_
 
 For more information on this process and the supported item types, please refer to the [User Guide](https://guide.assistant.esri-ps.com/docs).
-\
-\
-\
-Continue to the next section on using [Jupyter Notebooks](https://scds.github.io/dash-webinars/Jupyter.html)
-
-Return to the [tutorial home page](https://scds.github.io/dash-webinars/Copy_ArcGIS_Content.html)
diff --git a/Copy_ArcGIS_Content.md b/Copy_ArcGIS_Content.md
@@ -1,14 +1,16 @@
 ---
 layout: default
 title: Copy ArcGIS Content
-nav_order: 16
+nav_order: 15.5
 has_children: true
 ---
 
+<img src="assets/img/Copy_ArcGIS_Content.png" alt="Workshop Title Slide" width="100%"> 
+
 # How to Copy ArcGIS Online Content Between Accounts
-<img src="assets/img/Copy_ArcGIS_Content.png" alt="Workshop Title Slide" width="720"> 
 
 ## Introduction 
+
 Current students, staff, and faculty have access to ArcGIS Online through an Educational Institution Agreement. Content created in the ArcGIS web applications will remain online following graduation but won’t be maintained or updated and are subject to availability of the application. 
 
 Did you know you can copy some content from your McMaster ArcGIS Online account to a personal account? This asynchronous online tutorial will provide you with resources and tools to copy content between accounts. 
@@ -17,7 +19,8 @@ Online module created by Christine Homuth, Spatial Information (GIS) Specialist.
 
 For more information [contact Christine](mailto:[email protected]) or [schedule a consultation](https://libcal.mcmaster.ca/appointments/gis). 
 
-## Migrating Content 
+## Migrating Content
+
 The workshop outlines two of the methods available that can be used to copy your content between ArcGIS accounts. 
 
 This content has been adapted from the following [Esri Canada Getting Technical](https://resources.esri.ca/getting-technical) articles:
@@ -36,8 +39,6 @@ To get started:
 2. Choose to *Sign In* with your ArcGIS account.
 3. Choose *Save As* to save a copy of the map to your account.
 
-
-
 ### Continue
 
 Continue on with the workshop by exploring the options to copy content, listed below in the Table of Contents.
diff --git a/IntermediatePython.md b/IntermediatePython.md
@@ -4,27 +4,27 @@ title: Intermediate Python Programming
 nav_order: 8
 ---
 
-## Intermediate Python Programming
+<img src="assets/img/IntPyth.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/IntPyth.png" alt="Workshop Title Slide" width="720">
+# Intermediate Python Programming
 
 Python is a powerful and easy-to-learn programming language used by many scientists. From web scraping to bioinformatics, Python is bound to have a module that could be useful to you. This workshop will include a brief review of variable types and control flow before moving on to functions, variable scope, object-oriented programming, and several of Python’s important science libraries.
 
 Presentation by Isaac Kinley, DASH Support Assistant and PhD Candidate in Psychology, Neuroscience, and Behaviour.
 [Book an appointment with Isaac or another member of the DASH Team.](https://library.mcmaster.ca/services/dash)
 
-# Workshop preparation 
+## Workshop Preparation 
 
 Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. 
 
-## Get the data
+### Get the data
 Access the workshop file in [Notebook form](https://colab.research.google.com/drive/1IRh2fHy6pK0Yu4qUUCQ9UQ-T9qMdxu5N?usp=sharing) or in [.py and .pynb extensions](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EkSTOJueZqVGlz3uujESxMkBaC2onNUG6aJfJMRyURw4Ew?e=ZV4vRS)
 
-## Get the software
+### Get the software
 This hands-on workshop uses [**Python**](https://www.python.org/downloads/), a software application for data analysis. The program is free to download.
 
 ## Workshop Recording
 
-<iframe height="480" width="853" allowfullscreen frameborder=0 src="https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public"></iframe>
+<iframe height="416" width="100%" allowfullscreen frameborder=0 src="https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public"></iframe>
 
-View the original [here](https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public). 
+[View the original here.](https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public)
diff --git a/Intro-Geospatial-Data.md b/Intro-Geospatial-Data.md
@@ -4,20 +4,17 @@ title: Intro to Geospatial Data
 nav_order: 14
 ---
 
-## Introduction to Geospatial Data
+<img src="assets/img/GeoSpatial.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/GeoSpatial.png" alt="Workshop Title Slide" width="720">
+# Introduction to Geospatial Data
 
 Geospatial data is data about objects or features on or near the surface of the Earth and can be mapped using Geographic Information Systems (GIS) software. This workshop introduces participants to geospatial data formats and concepts as well as sources for this data. 
 
 Presentation by Christine Homuth, Spatial Information (GIS) Specialist.
 [Get in touch with Christine.](https://library.mcmaster.ca/homuth-christine)
 
-# Workshop Slides
+## Workshop Slides
 
-<div style="position:relative;padding-top:66.25%;">
-<iframe src="//docs.google.com/viewer?url=https://github.com/scds/dash-webinars/raw/main/assets/docs/Intro_Geospatial_Data_Slides.pdf?dl=0&hl=en_US&embedded=true" class="gde-frame" style="position:absolute;top:0;left:0;width:100%;height:100%;border:none;" scrolling="no"></iframe>
-</div>
+<embed src="assets/docs/Intro_Geospatial_Data_Slides.pdf" style="border:none;" width="100%" height="466px">
 
-[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/Intro_Geospatial_Data_Slides.pdf)
-<br>
+[Download as PDF.](assets/docs/Intro_Geospatial_Data_Slides.pdf)
diff --git a/IntroPython.md b/IntroPython.md
@@ -4,9 +4,9 @@ title: Intro to Python Programming
 nav_order: 7
 ---
 
-## Introduction to Python Programming
+<img src="assets/img/Python.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/Python.png" alt="Workshop Title Slide" width="720">
+# Introduction to Python Programming
 
 This beginner level workshop will introduce you to the basic concepts of one of the world’s most popular programming languages, Python. In this tutorial, you’ll learn how to store data using Python’s data types and variables, control the flow of a program using control structures, and create reusable code using functions. No prior knowledge of Python is required.
 

diff --git a/Jupyter.md b/Jupyter.md
@@ -93,8 +93,3 @@ cloned_items = gis_destination.content.clone_items(items=[item], copy_data=True)
 
 print("Completed!") 
 ``` 
-
-\
-Continue to see [Resources](https://scds.github.io/dash-webinars/ArcGIS_Python_Resources.html) on this process and working with Python in ArcGIS.
-
-Return to the [tutorial home page](https://scds.github.io/dash-webinars/Copy_ArcGIS_Content.html).
diff --git a/Kmeans.md b/Kmeans.md
@@ -4,9 +4,9 @@ title: Machine Learning with R - K-Means Clustering
 nav_order: 2
 ---
 
-## Machine Learning with R: K-Means Clustering
+<img src="assets/img/Machine Learning - K Means - White BG.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/Machine Learning - K Means - White BG.png" alt="Workshop Title Slide" width="720">
+# Machine Learning with R: K-Means Clustering
 
 Clustering is an unsupervised machine learning approach for finding subgroups of observations within a data set. This workshop will introduce participants to the theoretical part of the most common clustering method, K-means clustering. Afterwards, participants will gain hands-on experience in how to conduct K-means clustering in R, as well as how to interpret and visualize their results. 
 
@@ -15,29 +15,25 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth,
 
 This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. 
 
-# Workshop preparation 
+## Workshop Preparation 
 
 Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. 
 
-## Get the data
+### Get the data
 
 [Access the RMD and CSV files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvZSraT60XZFlhNtCbbEQr0Bxb0pt53qnqJ-LnrFlKEvXA?e=wGkIvS)
 
-## Get the software
+### Get the software
 This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download.
 
 ## Workshop Recording
 
-<iframe height="480" width="853" allowfullscreen frameborder=0 src="https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public"></iframe>
+<iframe height="416" width="100%" allowfullscreen frameborder=0 src="https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public"></iframe>
 
-View the original [here](https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public). 
+[View the original here.](https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public) 
 
 ## Workshop Slides
 
-<div style="position:relative;padding-top:66.25%;">
-<iframe src="//docs.google.com/viewer?url=https://github.com/scds/dash-webinars/raw/main/assets/docs/DASHWorkshop-K-means-clustering_ShailaJamal.pdf?dl=0&hl=en_US&embedded=true" class="gde-frame" style="position:absolute;top:0;left:0;width:100%;height:100%;border:none;" scrolling="no"></iframe>
-</div>
-
-[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvZSraT60XZFlhNtCbbEQr0Bxb0pt53qnqJ-LnrFlKEvXA?e=wGkIvS)
-<br>
+<embed src="assets/docs/DASHWorkshop-K-means-clustering_ShailaJamal.pdf" style="border:none;" width="100%" height="466px">
 
+[Download as PDF.](assets/docs/DASHWorkshop-K-means-clustering_ShailaJamal.pdf)
diff --git a/Machine-learning-python.md b/Machine-learning-python.md
@@ -4,27 +4,27 @@ title: Machine Learning with Python
 nav_order: 10
 ---
 
-## Machine Learning with Python
+<img src="assets/img/Python-Rescheduled.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/Python-Rescheduled.png" alt="Workshop Title Slide" width="720">
+# Machine Learning with Python
 
 Machine Learning is an exciting way to get more insight out of your data. Working with Python, this workshop will cover some basic theory and algorithms for feature learning, classification, and regression. 
 
 Presentation by Isaac Kinley, DASH Support Assistant and PhD Candidate in Psychology, Neuroscience, and Behaviour.
 [Book an appointment with Isaac or another member of the DASH Team.](https://library.mcmaster.ca/services/dash)
 
-# Workshop preparation 
+## Workshop preparation 
 
 Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. 
 
-## Get the data
+### Get the data
 Access the workshop file in [Notebook form](https://colab.research.google.com/drive/1Bn9RlzIizqAuGKI5oZxjjNSWce-Z_Ujj?usp=sharing) or in [.py and .pynb extensions](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/ErRDPuXg88NMteEABkzQbHABH7vW3s0M_P2zRlF4bfIndg?e=6vZFDd)
 
-## Get the software
+### Get the software
 This hands-on workshop uses [**Python**](https://www.python.org/downloads/), a software application for data analysis. The program is free to download.
 
 ## Workshop Recording
 
-<iframe height="480" width="853" allowfullscreen frameborder=0 src="https://echo360.ca/media/dd02dd21-aa07-407b-8cdd-f2af0a445e0d/public"></iframe>
+<iframe height="416" width="100%" allowfullscreen frameborder=0 src="https://echo360.ca/media/dd02dd21-aa07-407b-8cdd-f2af0a445e0d/public"></iframe>
 
 View the original [here](https://echo360.ca/media/dd02dd21-aa07-407b-8cdd-f2af0a445e0d/public). 
diff --git a/Matlab.md b/Matlab.md
@@ -4,28 +4,28 @@ title: Data Visualization with MATLAB
 nav_order: 12
 ---
 
-## Data Visualization with MATLAB
+<img src="assets/img/Matlab-Final.png" alt="Workshop Title Slide" width="100%">
 
-<img src="assets/img/Matlab-Final.png" alt="Workshop Title Slide" width="720">
+# Data Visualization with MATLAB
 
 This asynchronous module discusses how you can create publication-quality figures using MATLAB or its free alternative, Octave. The module covers plotting options for one- and two-dimensional continuous and categorical data and explore options for customizing your figure's appearance. 
 
 Presentation by Subhanya Sivajothy (Data Analysis and Visualization Librarian).
 
 [Book an appointment with Subhanya or another member of the DASH Team.](https://library.mcmaster.ca/services/dash)
 
-# Workshop preparation 
+## Workshop preparation 
 
 Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. 
 
-## Get the data
+### Get the data
 Access the data file [in .xlsx extension](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EsD3ng2kvL9OqNGogNshky4BmAGqsCRixEDZpdFhheR-VA?e=lMjuNh).
 
-## Get the software
+### Get the software
 This hands-on workshop uses [**MATLAB**](https://matlab.mathworks.com/), a software application for data visualization, and [**Octave**](https://octave.org/), its free alternative. 
 
 ## Asynchronous Video Module
 
-<iframe height="480" width="853" allowfullscreen frameborder=0 src="https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public"></iframe>
+<iframe height="416" width="100%" allowfullscreen frameborder=0 src="https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public"></iframe>
 
-View the original [here](https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public). 
+[View the original here.](https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public)
diff --git a/README.md b/README.md
@@ -1,14 +1,11 @@
-# DASH Webinars
-Materials for DASH Workshops 
-
-This repository contains workshop files, as well as files used to create the [workshop webpage](https://scds.github.io/dash-webinars) with GitHub Pages. 
+# 2022-23 DASH Webinars
+Materials for the **2022-2023 DMDS Webinars**.  
 
+This repository contains workshop files, as well as files used to create the [webpage](https://scds.github.io/dash-webinars) with GitHub Pages. 
 
 Contributions by the following individuals: 
 - Workshop content created by Christine Homuth, John Fink, Vivek Jadon, Shaila Jamal, and Isaac Kinley.
-- Content edited for online use by Veronica Litt
+- Content edited for online use by Veronica Litt and Richie Motorgeanu
 - Online pages created by Veronica Litt
-
-
 
-All content is made available under a GNU General Public License v3.0.
+All content is made available under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).