Teaching assistant
SYLLABUS – EE 547: Spring 2025 (2 units)
Applied and Cloud Computing for Electrical Engineers
Instructor: Brandon Franzke Office: EEB 504B
Thursday: 16:10 – 17:30
This course introduces tools and concepts to build and deploy full stack software solutions in modern com- puting environments. It is a project-driven course that develops from concept to application. The course is intended for graduate electrical engineering students with prior programming experience. Students will learn about technologies and practices essential for modern application deployment. The course covers three main areas: (1) cloud technologies and integration, (2) frontend and backend programming, and (3) deployment in global computing infrastructure. Students gain hands-on experience with virtualization and cloud environments and learn about concepts that apply across computing platforms.
Lecture Tuesday (section: 31250) 15:30 – 17:20 Discussion Friday (section: 30404) 12:00 – 12:50
Enrollment is in-person ONLY. Attendance is mandatory to all lectures. Taping or recording lectures or discussions is strictly forbidden without the instructor’s explicit written permission.
[1] Cloud Native Architecture and Design, Goniwada, S. R., Apress, 2022. online, USC libraries.
[2] Cloud Native Patterns: Designing change-tolerant software, Davis, C., Manning, 2019. online,
USC libraries.
[3] The Good Parts of AWS, Vassallo, D., Pschorr, J., 2020. (optional).
[4] Exploring JavaScript – ES2024 edition, Rauschmayer, A., 2024. online, https://exploringjs.com/ js/index.html.
[5] Learning Web Design: A Beginner’s Guide to HTML, CSS, JavaScript, and Web Graphics, 5th edition, Robbins, J., O’Reilly Media, 2018. online, USC libraries.
[6] Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement, Perkins, L., Redmond, E., Wilson, J. R., Pragmatic Bookshelf, 2018. online, USC libraries.
[7] The Road to React, Wieruch, R., 2023. (optional), online, https://github.com/the-road-to-learn-react/ the-road-to-react.
“AI”policy. YoumayuseAI-poweredtoolsinthiscoursetoenhanceyourlearningandproductivity.Use AI as a collaborative tool for understanding concepts, generating ideas, and troubleshooting. Approach AI-generated content critically and use it responsibly. Engage with AI as you would with a knowledgeable peer or tutor, using iterative conversations to deepen your understanding. You must attribute all AI- generated content in your work, including the prompts you used. You are fully accountable for the accuracy and appropriateness of any AI-assisted work. AI should supplement, not substitute, your own critical thinking and problem-solving. For assignments, you may use AI to clarify concepts or resolve issues, but submitted work must be your own. Submitting AI-generated work as your own without proper attribution or understanding is academic misconduct and will be treated as such.
You must develop complete mastery of all course material independent of AI assistance. Your knowledge and skills will be evaluated in contexts where AI tools are not accessible, mirroring real-world scenarios where you must rely solely on your own expertise. This ensures you can perform effectively in any situation, with or without AI support. Violations of this policy will result in severe academic penalties. The goal is to prepare you to use AI effectively in your future work while ensuring you develop a strong, self-reliant foundation in the course material.
Learning objectives
Upon completion of this course, a student will be able to:
• Understand and apply key concepts in cloud computing, such as serverless architectures and mi- croservices.
• Develop full-stack applications using modern backend and frontend technologies, integrating asyn- chronous programming and data security principles.
• Deploy and manage applications on cloud platforms, utilizing a range of cloud services and under- standing deployment strategies.
• Implement and manage databases, selecting appropriate data models and storage solutions for application needs.
• Utilize containerization technologies effectively for development and deployment of applications.
• Employ best practices in software lifecycle management, including continuous integration and deployment.
Course Outline
Topics Required Reading Homework
Week 1 14 Jan
Architecture (local vs. distributed), containers, virtualization, cloud com- puting.
[1] Ch. 1–2, 16∗, [2] Ch. 1–3.
HW 1 assigned.
Week 2 21 Jan
JavaScript and Node.js. HTTP servers.
[4] Ch. 9–10, 13–18, 22– 23, 25, 45–47.
HW 2 assigned.
Week 3 28 Jan
REST APIs. Backend: Express mid- dleware and routing.
[4] Ch. 26–27, 30–31, 39.
HW 3 assigned.
Week 4 04 Feb
Asynchronous Node.js. Debugging techniques. Testing frameworks.
[4] Ch. 29, 41-44.
HW 4 assigned.
Week 5 11 Feb
Frontend: HTML, CSS, Javascript.
[5] Ch. 4–9, 11–15, 21– 22.
HW 5 assigned.
Week 6 18 Feb
Cloud computing fundamentals: scaling, roles, services.
[1] Ch. 4, [2] Ch. 5, [3] Pt. 1.
HW 6 assigned.
Week 7 25 Feb
Databases: SQL overview.
[6] Ch. 2(1,2).
Week 8 04 Mar
NoSQL and cloud databases. Node.js integration.
[2] Ch. 8, [6] Ch. 4(1), 6(1), 8(1).
HW 6 due
HW 7 assigned.
Week 9 11 Mar
Cloud computing architectures: serverless (AWS Lambda), microser- vices.
[1] Ch. 5, 7. [2] Ch. 4.
HW 8 assigned.
(17 Mar)
No class, Spring Break.
Week 10 25 Mar
Cloud computing mechanisms: mes- saging, storage, and deployment.
[1] Ch. 6. [2] Ch. 6–8.
HW 8 due.
HW 9 assigned.
Draft project proposal due (28 Mar).
Week 11 01 Apr
Project meetings.
HW 9 due.
Week 12 08 Apr
Exam.
Revised project proposal due (11 Apr).
Week 13 15 Apr
Frontend frameworks: React, Com- ponents, and State.
[7].
Week 14 22 Apr
Advanced cloud deployment. CI/CD.
[3] Pt. 2.
Status report due (25 Apr).
Week 15 29 Apr
Project Wrap-up. Project meetings.
Thursday 08 May
Technical review and demos, 14:00 - 17:00.
Monday 12 May
Project deliverables, due 12:00.
Grading Procedure
Homework (55%). Assignments include a mix of applied and programmatic problems. Your total homework score sums your best homework scores (as a percentage) after removing the one lowest score
(of minimum 50%). You may discuss homework problems with classmates but each student must submit their own original work. Cheating warrants an “F” on the assignment. Turning in substantively identical homework solutions counts as cheating.
Late homework is accepted with a 0.5% deduction per hour, up to 48-hours – no exceptions. Technical issues while submitting are not grounds for extension. No submissions will be accepted 48-hours after the due date. Graders score what is submitted and will not follow up if the file is incorrect, incomplete, or corrupt. It is your responsibility to ensure you submit the correct files and that they are accessible.
Exam (15%). The exam tests your ability to apply major principles, demonstrate conceptual under- standing, and requires writing code. It occurs during week 12 (tentative). You are expected to bring a scientific (non-graphing) calculator. You may use a single 8.5”x11” reference sheet (front and back OK). You may not use any additional resources.
The exam includes multiple-choice and short answer questions. It also include free-response or open- ended questions to demonstrate conceptual understanding. You are expected to write reasonably correct code as well as determine expected behavior of novel computer code. Grading primarily follows correct reasoning but may include deductions for major syntax errors, algorithmic inefficiency, or poor imple- mentation.
Final project (30%). This course culminates with a final project in lieu of a final exam. Teams of three students (in rare cases, teams of two with instructor approval) design and implement a complete software product that connects two or more independent asynchronous components (often frontend and backend). The instructor will guide teams having difficulty identifying a suitable application. Teams are encouraged to devise solutions to novel problems of personal interest to their background or research. But teams may build an application similar to existing services or tools provided their efforts demonstrate understanding of the development stack and the product lifecycle — from idea to deployment to maintenance. All projects must obtain the instructor’s written approval. Teams will prepare and present/demo their approved project and show how it applies course material, concepts, and best-practices.
Course Grade
A if 90 - 100 points, B if 80 - 89 points, C if 70 - 79 points, D if 60 - 69 points, F if 0 - 59 points. (“+” and “–” at ≈ 1.5% of grade boundary).
Cheating
Cheating is not tolerated on homework or exams. Penalty ranges from F on exam to F in course to recommended expulsion.
Grading and Milestones
Topic proposal (initial and revised)
Status report - Design, components, integration Technical review and demo
Project report
Design and source code
Video
week 10 & 12
week 14 7% final 25%
20% 35% 3%
Final Project
Project Requirements
Project topics must include sufficient scope and apply course knowledge to a useful end. The project must compose at least two distinct units that operate and act independently but provide greater function when acting together. The project must demonstrate comprehensive understanding of the entire development stack and the product lifecycle from idea to deployment to maintenance. Additional requirements and guidelines will be discussed closer to the commencement of the project.
All projects must use Node.JS as the primary language unless approved explicitly in writing by the instructor. But projects may use additional languages for tooling and support. Projects must implement and expose some API or service to consumers. The instructor may provide additional requirements when introducing the final project assignment.
Deliverables
Topic proposal: describe the problem, proposed technical approach, and expected outcomes. It should
communicate that your topic is adequately prepared and it should outline immediate next steps. But the proposal is merely a guidepost and reasonable deviations in method, approach, and scope are expected.
Written report: summarize the topic, provide relevant background (theoretical or applied), timeline and contributions, and document challenges and extensions. It should provide discussion suffi- cient that an uninformed expert can understand the models, analytic decisions, outcomes, and implementation. Teams should provide quantifiable metrics to justify engineering tradeoffs.
Technical review and demo: Approximately 15 minutes (depends on class size) to describe the topic problem and solution. It should provide only what is necessary to understand the what and why and include minimal theoretical background. The instructor will provide a technical reference slide-deck template that must be completed in advance of the demo session.
Source code: submitted as a GitHub repository archive file (zip). It must include README file(s) that describe the repository structure, execution instructions, and special technical requirements.
Video: a 4-minute video that describes the topic, your implementation, and your results. You may choose to upload this to a video sharing site such as YouTube but that is not required.
3% + 7%
Academic Accommodations
Any student requesting academic accommodations based on a disability is required to register with Disability Services and Programs (DSP) each semester. A letter of verification for approved accommo- dations can be obtained from DSP. Please be sure the letter is delivered to me as early in the semester as possible. DSP is located in STU 301 and is open 08:30 - 17:00, Monday through Friday. The phone number for DSP is (213) 740-0776.
Support Systems
A number of USC’s schools provide support for students who need help with scholarly writing. Check with your advisor or program staff to find out more. Students whose primary language is not English should check with the American Language Institute http://dornsife.usc.edu/ali, which sponsors courses and workshops specifically for international graduate students. The Office of Disability Services and Programs http://sait.usc.edu/academicsupport/centerprograms/dsp/home index.html provides certifi- cation for students with disabilities and helps arrange the relevant accommodations. If an officially declared emergency makes travel to campus infeasible, USC Emergency Information http://emergency. usc.edu will provide safety and other updates, including ways in which instruction will be continued by means of brightspace, teleconferencing, and other technology.
Discrimination, sexual assault, and harassment are not tolerated by the university. You are encouraged to report any incidents to the Office of Equity and Diversity http://equity.usc.edu or to the Department of Public Safety http://capsnet.usc.edu/department/department-public-safety/online-forms/contactus. This is important for the safety of the whole USC community. Another member of the university community - such as a friend, classmate, advisor, or faculty member - can help initiate the report, or can initiate the report on behalf of another person. The Center for Women and Men http://www.usc.edu/ studentaffairs/cwm/ provides 24/7 confidential support, and the sexual assault resource center webpage http://sarc.usc.edu describes reporting options and other resources.
Academic Conduct
The University of Southern California is foremost a learning community committed to fostering successful scholars and researchers dedicated to the pursuit of knowledge and the transmission of ideas. Academic misconduct is in contrast to the university’s mission to educate students through a broad array of first- rank academic, professional, and extracurricular programs and includes any act of dishonesty in the submission of academic work (either in draft or final form).
This course will follow the expectations for academic integrity as stated in the USC Student Handbook. All students are expected to submit assignments that are original work and prepared specifically for the course/section in this academic term. You may not submit work written by others or “recycle” work prepared for other courses without obtaining written permission from the instructor(s). Students suspected of engaging in academic misconduct will be reported to the Office of Academic Integrity.
Other violations of academic misconduct include, but are not limited to, cheating, plagiarism, fabrication (e.g., falsifying data), knowingly assisting others in acts of academic dishonesty, and any act that gains or is intended to gain an unfair academic advantage.
Academic dishonesty has a far-reaching impact and is considered a serious offense against the university. Violations will result in a grade penalty, such as a failing grade on the assignment or in the course, and disciplinary action from the university itself, such as suspension or even expulsion.
For more information about academic integrity see the student handbook
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