Embedded Files
Course Survey - Mid Term: https://forms.gle/Y6pP2sr4v3dfxE1w8
Link to Teams Meeting for C hour 1045-1140 on Day 1 (Open with Teams App):
Mathletes,
Welcome to MA486 - Mathematical Computation! I hope everyone had a great summer and is looking forward to getting back to work this next semester. LTC Clark and I are excited to get to work with you this semester in developing your programming and computational problem solving skills.
Due to the social distancing rules and classroom availability, this course will be taught remotely (yes, sad face emoji). You will be required to watch the videos for the lesson, use the text as a resource, read the Juypter Notebooks and complete quizzes to ensure that you understand the material prior to class. Class will be held remotely on MS Teams where you will be introduced to material (if needed), have the opportunity to ask questions, and work in groups to complete programming assignments. It will be beneficial for you to have two screens for this class since we will work programming problems in class that I expect you to be typing in as we do it (if we were in class, I would be projecting that onto the screen).
Please take a few minutes to read the email, visit the course website, and complete the following tasks. You will need to do the following before the first day of class:
1. Visit and bookmark the website:
https://sites.google.com/view/ma486/home
2. Download the Course Guide (https://drive.google.com/file/d/1c4Tos1ag8TkaUbba1Dpl7Zi-tc_H_5ij/view) and Instructor Memo (https://drive.google.com/file/d/1Ar9el_0bBYaSyttHlPm8SX0dfER2eIG1/view).
3. Print the course calendar for your reference (https://drive.google.com/file/d/1cUTkOKXtQBk3ya_s0u34s4yeAkuHS-Of/view).
4. Download and install the Anaconda Python installation Python 3.8 is the latest version. Click download (https://www.anaconda.com/products/individual#download-section).
5. There are two books needed for this course.
Block 1&3 are from
Langtangen, Hans Peter. A Primer for Scientific Programming (5th edition)
Blocks 2&4 come from:
VanderPlas, Jake. Python Data Science Handbook
6. Bookmark the MIT Open Course: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/lecture-videos/
These are the MIT videos that are referenced in the course guide and will assist you in understanding some of the computer science aspects of programming.
7. Due to the remote learning environment, we will be using Jupyter notebooks in cocalc. This is simply a way for you to run a Jupyter notebook (python code with a markup language) on another computer (on the cloud) and share code between users. Sign up for a cocalc account $14 for the semester at www.cocalc.com. Once you have your account established, send your instructor the email account that you registered it with so that they can add you to the course.
8. Lesson preparation. From the course website, you will see 4 videos for lesson 1, The “What is computation?” Is an Open Courseware video from MIT which will help you understand programming from a computer scientist’s perspective. Although it is focused on python, most of the ideas in these videos deal with programming in general. Videos 1,2,3 (under “Module”) are MA486 course specific and support the problems that you are assigned for each lesson. There is a Jupyter Notebook for you to read with problems assigned in each of them as well. For each lesson, do the following:
1) Watch the MIT video (What is Computation?)
2) Watch Module 1 (Course Introduction) -> Open the Jupyter Notebook 1-1 -> Answer the questions in Quiz01_1
3) Watch Module 2 (Variables and Operators) -> Open the Jupyter Notebook 1-2 -> Answer the questions in Quiz01_2
4) Watch Module 3 (F-strings) -> Open the Jupyter Notebook 1-3 -> Answer the questions in Quiz01_3
5) Do as many programming exercises that you can before class (Suggested Problems from the book – see course guide, Jupyter Notebook Exercises)
You are not required to do every programming exercise, there are many for you to choose from that will get points for your weekly homework – see the course introduction video.
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