Update links for Numpy etc assignments

book/extracredit/programming.md

@@ -1,10 +1,10 @@
 # Extra Credit Problems for Jupyter, Python, Numpy, etc.
 
-You can complete additional courses on LinkedIn Learning or other venues for additional points. The below links are curated to be especially helpful and useful, but almost any online activity that you complete and can document the completion of is acceptable. To get credit, add to the list of courses you have completed in your `Course-Certificates` GitHub repository.
+You can complete additional courses on LinkedIn Learning or other venues for additional points. The below links are curated to be especially helpful and useful, but almost any online activity that you complete and can document the completion of is acceptable. To get credit, add to the list of courses you have completed in your `Course-Certificates` GitHub repository. You can add courses anytime before the end of the term, but be sure that you get your points, as I might not check your repository unless you tell me to do so.
 
 ## [Codecademy Python 2](https://www.codecademy.com/learn/learn-python)
 
-- This is Python 2, but Python 3 isn't very different, and the Python 3 course requires a (paid) subscription to Codecademy, while the Python 2 course does not. To do this assignment, sign up for Codecademy (free) and work through the 12 topical modules by reading about Python syntax and solving the interactive web-based exercises on your own. If you get stuck, you'll be provided with instructive hints. This [course](https://www.codecademy.com/learn/learn-python) will take *much* less than the time they estimate, because you can skip projects and quizzes that are accessible only through a (paid) PRO account. When you're finished, take a screenshot of the certificate of completion add it to the list of certificates in your `Course-Certificates` repository. See image below.
+- This is Python 2, but Python 3 isn't very different, and the Python 3 course requires a (paid) subscription to Codecademy, while the Python 2 course does not. (You can get a free trial from Codecademy, though.) To do this assignment, sign up for Codecademy (free) and work through the 12 topical modules by reading about Python syntax and solving the interactive web-based exercises on your own. If you get stuck, you'll be provided with instructive hints. This [course](https://www.codecademy.com/learn/learn-python) will take *much* less than the time they estimate, because you can skip projects and quizzes that are accessible only through a (paid) PRO account. When you're finished, take a screenshot of the certificate of completion add it to the list of certificates in your `Course-Certificates` repository. See image below.
 
 ![image](../linkedFiles/codecademy.png)
 
@@ -15,37 +15,29 @@ You can complete additional courses on LinkedIn Learning or other venues for add
 
 You can complete relevant LinkedIn Learning courses to earn extra points. For example, you can choose to complete some of the courses you've already (partly) seen in the course material. Simply add the LinkedIn Learning certificate of completion to the list in your `Course-Certificates` repository.
 
-- [Programming Foundations: Fundamentals](https://www.linkedin.com/learning/programming-foundations-fundamentals-3/the-fundamentals-of-programming?u=56982905)
-- [Programming Foundations: Version Control with Git](
-   https://www.linkedin.com/learning/programming-foundations-version-control-with-git)
-- [Learning GitHub](https://www.linkedin.com/learning/learning-github)
-- [GitHub Essential Training](https://www.linkedin.com/learning/github-essential-training)
+- [Programming Foundations: Fundamentals](https://www.linkedin.com/learning/programming-foundations-fundamentals-3?u=56982905). Other courses in the "programming foundations" series are also acceptable. The courses [beyond fundamentals](https://www.linkedin.com/learning/programming-foundations-beyond-the-fundamentals?u=56982905) and [numerical mathematics](https://www.linkedin.com/learning/programming-foundations-numerical-mathematics-and-calculations?u=56982905) are especially relevant.
+- [Learning GitHub](https://www.linkedin.com/learning/learning-github-18719601?u=56982905)
+- [GitHub Essential Training](https://www.linkedin.com/learning/github-essential-training-1-the-basics?u=56982905)
 - [Python for Engineers and Scientists](https://www.linkedin.com/learning/python-for-engineers-and-scientists)
-- [Python Data Analysis](https://www.linkedin.com/learning/python-data-analysis-2/get-started-in-data-analysis-with-python?u=56982905)
-- [Julia Power like Python, Speed like C](https://www.linkedin.com/learning/learning-julia/julia-power-like-python-speed-like-c)
+- [Working with Data](https://www.linkedin.com/learning/advanced-python-working-with-data?u=56982905)
+- [Intermediate Numpy](https://www.linkedin.com/learning/numpy-essential-training-2-matplotlib-and-linear-algebra-capabilities)
+- [Julia Power like Python, Speed like C](hhttps://www.linkedin.com/learning/learning-julia?u=56982905)
 
 
-## GitHub Learning Lab
-
-The [GitHub Learning Lab](https://lab.github.com/) has a lot of great courses. You can complete them for extra points. The certificates-of-completion from these courses can be uploaded to your `Course-Certificates` repository. Among the most relevant courses are:
-- [First Week on GitHub](https://lab.github.com/githubtraining/first-week-on-github)
-- [Introduction to Python](https://lab.github.com/everydeveloper/introduction-to-python)
-- [Intermediate Python](https://lab.github.com/everydeveloper/intermediate-python)
-
 ## Online Python Tests
 
-- [**Python Exercises from W3Schools**](https://www.w3schools.com/python/exercise.asp) 95 simple interactive questions grouped by topic. 
+- [**Python Exercises from W3Schools**](https://www.w3schools.com/python/exercise.asp) 95 simple interactive questions grouped by topic.
 
   - Instructions: Try to solve an exercise by filling in the missing parts of code. If you got stuck, hit the "Show Answer" button to see what you've done wrong. If you need to practice a certain topic more, you can go directly to the associated interactive tutorial. At the end, submit a screenshot showing "Completed 95 of 95 Exercises" for extra credit.
 
-- [**Python Quiz from W3Schools**](https://www.w3schools.com/quiztest/quiztest.asp?qtest=PYTHON) 25 multiple-choice questions. 
+- [**Python Quiz from W3Schools**](https://www.w3schools.com/quiztest/quiztest.asp?qtest=PYTHON) 25 multiple-choice questions.
 
   - Instructions: Your total score and the correct answers will be displayed at the end of the quiz. Take a screen shot of this page and receive points (depending on your score).
 
-- [**PYnative Python Quizzes**](https://pynative.com/python-quizzes/) 14 topic-specific quizzes each with ~15 questions each. 
+- [**PYnative Python Quizzes**](https://pynative.com/python-quizzes/) 14 topic-specific quizzes each with ~15 questions each.
   - Instructions: Click on “Solve Quiz” to test your knowledge on each topic. Upon submitting, your score, correct answers are displayed. Take a screenshot of the "passed" quizzes and submit them.
 
-- [**Interactive Python Quizzes from Real Python**](https://realpython.com/quizzes/) A collection of short interactive quizzes. 
+- [**Interactive Python Quizzes from Real Python**](https://realpython.com/quizzes/) A collection of short interactive quizzes.
   - Instructions: Take the quizzes and then submit a screenshot of the score reports to show that you passed the quiz.
 
 - [**Exercism**](http://exercism.io/) Free mentor-based learning pathways for [Python](https://exercism.io/tracks/python), [Julia](https://exercism.io/tracks/julia), and much more.

book/ipynb/jupyter.ipynb.md

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+# /C:/Users/ayers/Repositories/QC-Edu/IntroQM/book/ipynb/jupyter.ipynb
+

book/jupyter.ipynb.md

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+# /C:/Users/ayers/Repositories/QC-Edu/IntroQM/book/jupyter.ipynb
+

book/main_content.md

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   - Know, understand, and apply approximate computational strategies and their associated practical computational methods
 
 ## Assessment
-- **Assignments** are provided via [Github Classroom](https://classroom.github.com/). To learn more about Github Classroom, see our [tutorial](Tutorial_0.ipynb). Each assignment is graded automatically on GitHub (for correctness and quality)
+- **Assignments** are provided via [Github Classroom](https://classroom.github.com/). To learn more about Github Classroom, see our [tutorial](problems/Tutorial_0.ipynb). Each assignment is graded automatically on GitHub (for correctness and quality)
 - **Extra Points** may be earned by [making pull requests](contributing.md) to [this repository](https://github.com/QC-Edu/IntroQM). The aim is to encourage you to contribute/refine content that benefits other students. While all contributions ar   e encouraged, if you wish to ensure that extra credit will be granted, ask for prior approval/guidance from the instructor. [More information is available here.](extracredit/overview.md) Points are earned commensurate with the contribution, so even something as simple as correcting a typographical error in a notebook will receive some reward.
 - **Auditing** the course is allowed. This course was designed to help self-motivated independent learners. GitHub classroom assignments should be accessible, and auto-graded, without issue. Personal support is, unfortunately but necessarily, much more limited.
 

book/problems/JupyterPythonNumpy.md

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 # Assignment: GitHub, Jupyter, Python, Numpy
 This assignment consists of LinkedIn Learning courses that that cover Jupyter, programming concepts, Python programming, and Numpy. Upon completing each course, you will need to download your certificate of completion and upload it as your assignment. You can also add the certificate to your LinkedIn profile.
->Before you get started, it's helpful to [log into LinkedIn Learning](https://lnkd.in/gj-9Xgg). (However, the links provided should automatically prompt you to log in if you are not already.) If you already have a LinkedIn account associated with a different e-mail, you can link your accounts.  
+>Before you get started, it's helpful to [log into LinkedIn Learning](https://www.linkedin.com/login/en). (However, the links provided should automatically prompt you to log in if you are not already.) If you already have a LinkedIn account associated with a different e-mail, you can link your accounts.
 
-1. Go through the course's [introduction to computer programming and computer programming tools](../ipynb/jupyter.ipynb).
-1. Go to your user dashboard on GitHub and create a new repository called `Course-Certificates`. Experiment with the features within that repository to familiarize yourself with them. 
+1. Go through the course's [introduction to computer programming and computer programming tools](../jupyter.ipynb).
+1. Go to your user dashboard on GitHub and create a new repository called `Course-Certificates`. Experiment with the features within that repository to familiarize yourself with them.
 2. In the `README.md` file in the repository, explain that the purpose of this repository is to store your LinkedIn Learning Certificates. Make a numbered list of certificates, with the name of the course as the title, linked to the file containing the certificate. [See the example repository.](https://github.com/McMasterQM/Course-Certificates) You can look at the sequence of revisions in the example repository to learn more about how to construct the `README.md` file.
 3. Upload the certificates for [using Jupyter notebooks](../problems/Jupyter.md), [Python programming](../problems/python.md), and [using Numpy](../problems/numpy.md).
-4. Invite Rik [(username: `RichRick1`)](https://github.com/RichRick1) and Paul [(username: `PaulWAyers`)](https://github.com/PaulWAyers) as external collaborators with "write" permission to this repository. 
+4. Invite Rik [(username: `RichRick1`)](https://github.com/RichRick1) and Paul [(username: `PaulWAyers`)](https://github.com/PaulWAyers) as external collaborators with "write" permission to this repository.
 
 > Completing these four items suffices for an **S-** grade. For an **S** grade, complete one [additional activity](../extracredit/programming.md). For an **S+** grade, complete a total of at least three [additional activities](../extracredit/programming.md). The certificates and/or proofs-of-completion for these activities should be added to the `README.md` file in your `Course-Certificates` repository. Further activities can be added to this repository over the course of the term for (even more) additional points.

book/problems/numpy.md

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 # Numpy
 
 Numpy is the most important external library we will use in this course, and it is important to become very comfortable with it. To start, please go through:
-
+- Watch the following [short LinkedIn Learning video](https://www.linkedin.com/learning/python-data-analysis-2/numpy-overview?u=56982905).
 - [Numpy Introduction from W3Schools](https://www.w3schools.com/python/numpy_intro.asp). This interactive tutorial introduces you to the Numpy library and, helpfully, you can run the examples directly in the browser.
-- Watch the following short LinkedIn Learning videos. These
-  - give you an [overview of Numpy](https://www.linkedin.com/learning/python-data-analysis-2015/numpy-overview).
-  - explain [how to create Numpy arrays](<https://www.linkedin.com/learning/python-data-analysis-2015/creating-numpy-arrays>)
-  - teach you [how to do mathematical operations with and on arrays](https://www.linkedin.com/learning/python-data-analysis-2015/doing-math-with-arrays)
-  - show how to [index and slice arrays into pieces](https://www.linkedin.com/learning/python-data-analysis-2015/indexing-and-slicing)
 - Numpy's official website provides a valuable additional resource, [Numpy: The absolute basics for beginners](https://numpy.org/devdocs/user/absolute_beginners.html)
 
-Once you have a basic familiarity with Numpy, you can complete the LinkedIn Learning [Numpy Essential Training 1: Foundations of NumPy](https://www.linkedin.com/learning/numpy-essential-training-1-foundations-of-numpy/) and submit your certificate to complete this assignment. 
+Once you have a basic familiarity with Numpy, you can complete the LinkedIn Learning [Numpy Essential Training 1: Foundations of NumPy](https://www.linkedin.com/learning/numpy-essential-training-1-foundations-of-numpy?u=56982905) and submit your certificate to complete this assignment.
 
 ![numpy Certificate](../linkedFiles/numpy.png)
-

book/problems/python.md

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 # Python Programming
 
-Go through the content of the LinkedIn Learning [Python Quick Start](https://www.linkedin.com/learning/python-quick-start/) course step-by-step and take the time to practice the material covered in a Jupyter notebook. Upon completing this course, add your certificate of completion to your `Course-Certificates` GitHub repository and reference it in `README.md`.
+Go through the content of the LinkedIn Learning [Python Quick Start](https://www.linkedin.com/learning/python-quick-start-22667553) course step-by-step and take the time to practice the material covered in a Jupyter notebook. Upon completing this course, add your certificate of completion to your `Course-Certificates` GitHub repository and reference it in `README.md`.
 
 ![Python Certificate](../linkedFiles/python.png)