2 semester hours
Thursday Evenings 6:00 p.m. – 7:30 p.m. in Online
Instructor: Ray Toal, Doolan 110, rtoal@lmu.edu, +1 310.338.2773
Learning Outcomes
By the end of this course, students will have:
- Created a solid presence on both GitHub and LinkedIn
- Gained experience in solving typical interview problems
- Participated in an agile development process
- Demonstrated competency in a web application stack, particularly with React
- Acquired knowledge of established technology company processes related to business and software development concerns
Prerequisites
You should have experience equivalent to at least one semester of programming, but more importantly you must bring: (1) a growth mindset, (2) a respectful attitude, and (3) a willingness to work hard, to never give up, to accept feedback, and to strive to avoid imposter syndrome and stereotype threat.Warning: Undefined variable $readings in /home/ray/cs.lmu.edu-ray/syllabus.php on line 57
Workload
In accordance with the LMU Credit Hour Policy, this 2-unit course will require 6 hours of work per week (including the time spent in lecture and lab).
Assignments and Grading
This class is graded CR/NC only. You must participate in class activities and complete all projects and retrospectives to receive credit.
Student Rights and Responsibilities
You have the right to:
- A syllabus with stated learning outcomes
- Have those learning outcomes addressed
- Chats with the instructor during office hours
- Have questions answered via email (one-day turnaround max)
- Video and text chats with the instructor
- Feedback on your work
- A challenging experience (you should be working a little outside your comfort zone)
- All lecture sessions recorded and stored online for you to access
- An experience beyond what you would get from books, websites, online tutorials, and discussion forums
- Feel like you belong (if you are experiencing impostor syndrome or stereotype threat, please see the instructor)
- Leave the course better skilled than when you came in
In return, you are expected to:
- Use the lab resources, TA time, and instructor time when you need them
- Stay on top of all course announcements, both on BrightSpace and Slack
- Watch the course recording if you miss class
- Perform work conscientiously, neatly, and in a timely manner
- Be considerate and respectful to your fellow students
- Be honest with yourself and others
- Finish the course or withdraw by the withdrawal deadline
For online courses, I recommend your camera be turned on unless you have bandwidth problems or need to step away.
Two Tips for Success
You've probably seen hundreds of these, but there are two that stand out.
- Be aware of how students trick themselves into thinking they’re learning. Cramming, rereading, and highlighting do not move information from your working memory into long-term memory. Short-term working memory is not “learned.” Recall is the most effective way to load your long-term memory. Please work through Nicky Case’s interactive essay How to remember everything forever-ish. (Also, this article backs up the importance of recall.)
- Use checklists, as these are incredibly effective. Read Atul Gawande’s The Checklist and think about how you apply these to your studies.
Generative AI and Your Learning
Academic honesty includes the appropriate use of technology as an aid for learning and productivity. This includes but is not limited to LLM-based generative artificial intelligence tools such as ChatGPT, Gemini, and Copilot.
Modern GenAI provides fast solutions to a variety of computing problems but must be used responsibly to get the most out of your education. GenAI will not always be helpful, especially when asked to write code for scenarios it cannot recognize. It cannot independently validate the code that it produces, and will frequently produce bugs and security vulnerabilities, making things worse for you. It will not be available for job interviews. As a student and future software professional, you have a moral and ethical responsibility to deeply understand every line of the software you author and should therefore employ GenAI in your coursework sparingly, especially when its use might rob you of the stretch-zone learning that comes from crafting programs on your own.
That said, there are several acceptable use cases of GenAI in programmatic assignments, including:
- Generating short documentation strings and type hints.
- Finding examples and explanations for syntactic forms (e.g., how to use the spread operator; how to assign variables directly from an array or object; how to construct a dictionary comprehension; how to unwrap an optional, and so on). Prompt the AI for the how-to’s, not your final code.
- Interpreting error messages, as these might be pretty cryptic! Sometimes the AI can be a useful tutor when explaining things it is familiar with.
- Generating unit tests for edge cases. When it finds something you overlooked, make a mental or written note so you can find these cases on your own next time.
- Brainstorming new ideas for apps.
Remember the four AsDO use technologies such as GenAI to augment ✅, amplify ✅, and accelerate ✅ your learning; NEVER use technology to avoid ❌ learning.
Be responsible!Generally, using GenAI and related tools without knowing what you are doing often leads to poor homework submissions that rarely achieve a grade higher than an F on their own merits, simply due to hallucinations and an inability to carry out tasks as they were assigned (even with good prompts).
Also, instructors and TAs are GenAI users themselves and will be able to easily detect inappropriate student use of these tools. The teaching staff will try to steer you back on track should we feel like you are giving up on your learning.
If you would like to use GenAI appropriately as a learner, see this short introductory article. If you are a TA, see this article by Jeff Olson on how to help teach students to use GenAI.
Topics
The following week-by-week schedule is tentative; however, you can be assured of:
- An interview problem nearly every week
- Occasional code alongs, and I-do, we-do, you-do lab sessions
- Three Projects:
- Weeks 1-3: Guided project (while we learn React)
- Weeks 4-9: Build an MVP for project based on given APIs
- Weeks 10-16: Buildout third and final project application
- Various guest speakers on topics such as Scrum, Entrepreneurship, and Startups.
- One or two visits by Erica Privott for Resume prep, Interviewing tips, LinkedIn presence, etc.
| Week | Date | Activities |
|---|---|---|
| 1 | Jan 14 |
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| 2 | Jan 21 |
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| 3 | Jan 28 |
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| 4 | Feb 4 |
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| 5 | Feb 11 |
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| 6 | Feb 18 |
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| 7 | Feb 25 |
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| 8 | Mar 4 | SPRING BREAK (NO CLASS) |
| 9 | Mar 11 |
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| 10 | Mar 18 |
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| 11 | Mar 25 |
|
| 12 | Apr 2 | EASTER BREAK (NO CLASS) |
| 13 | Apr 8 |
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| 14 | Apr 15 |
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| 15 | Apr 22 |
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| 16 | Apr 29 |
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| 17 | May 6 |
|
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Additional Information
Tentative Nature of the Syllabus. If necessary, this syllabus and its contents are subject to revision; students are responsible for any changes or modifications announced or distributed in class or posted online.
Course Evaluation. Student feedback on this course provides valuable information for continued improvement. All students are expected to fairly and thoughtfully complete a course evaluation for this course. Course evaluations for the Seaver College of Science and Engineering are administered online through the Blue™ evaluation system. You will receive an e-mail notification at your Lion e-mail address when the evaluation form is available. You may also access the evaluation form on Brightspace during the evaluation period. A few minutes of class time will be reserved for you to complete a course evaluation near the end of the semester. Please bring a laptop, smart phone, tablet or other mobile device to class on this date so that you can access the online evaluation platform.
Academic Honesty. Loyola Marymount University is a community dedicated to academic excellence, student- centered education and the Jesuit and Marymount traditions. As such, the University expects all members of its community to act with honesty and integrity at all times, especially in their academic work. Academic honesty respects the intellectual and creative work of others, flows from dedication and pride in performing one’s own best work, and is essential if true learning is to take place. As an LMU Lion, you are pledged to join the discourse of the academy with honesty of voice and integrity of scholarship.
Academic dishonesty will be treated as an extremely serious matter with severe consequences that can range from receiving no credit for an assignment or test to failing the class, to expulsion. It is never permissible to turn in any work not been authored by you without properly acknowledging the source. It is your responsibility to make sure that your work meets the standard of academic honesty set forth in the “LMU Honor Code and Process” which appears in the LMU Bulletin.
Special Accommodations. Students with special needs who require reasonable modifications, special assistance, or accommodations in this course should promptly direct their request to the Disability Support Services (DSS) Office. Any student who currently has a documented disability (ADHD, Autism Spectrum Disorder, Learning, Physical, or Psychiatric) needing academic accommodations should contact the DSS Office in Daum Hall, as early in the semester as possible. All discussions will remain confidential. Please visit LMU DSS for additional information. Please request any needed assistance as early in the semester as possible.
Wellness. Please familiarize yourself with, and make use, of the resources at Lion Wellness as needed.
Reporting Requirements of Sexual or Interpersonal Misconduct. As responsible employees, faculty are required to report any case of suspected sexual or interpersonal misconduct and cannot protect student confidentiality. For information about confidential counseling on campus and for general information about consensual relationships, sexual harassment, and sexual assault, please visit LMU Cares.
Emergency Preparedness. To report an emergency or suspicious activity, phone the LMU Department of Public Safety (x222 or 310-338-2893) or at the nearest emergency call box. In the event of an evacuation, follow the evacuation signage throughout the building to the designated safe refuge area where you will receive further instruction from Public Safety or a Building Captain. For more safety information and preparedness tips, visit LMU DPS.