Week 9

 Week 9 (3/5-3/11)

This is the first week of Software Design CST 338, and I got to work in CodingBat. I used this site before in community college for Java 1, which is a good refresher for this class. 

Discuss the process of solving the Coding Bat challenges.  A major part of software design is thinking about approaching a problem with the tools we have at our disposal.  What were the steps you took to solve some of these challenges? 

I follow a structure that involves reading the problem, understanding it, breaking it down or visually writing pieces down to help me understand it. Finally, I focus on what's needed. Then I put chunks of code in my head, write it down, and then organize and fix syntax.

Did you plan it out or throw code at it? 

I plan it out, and I need to understand it first to write code. Especially the conditions and what's being asked.

What worked? This approach works for me. Sometimes, I write it down visually or do extra steps to help me grasp the process. 

What DID NOT work? Sometimes, putting the code together in my head gets a bit overwhelming, so I try to visually write it down and write some pieces of code and then, lastly, put it together,

How many tries did it take? How many tries it takes depends on the subject. Map and String take me longer to write down, so more chances to get the syntax wrong. So, it took me more time to fix my process and syntax in those problems that involved more critical thinking. As usual, practice helps us master a subject.

Week 8

 Week 8 (2/26-3/1)

It is the end of CST 300 Writing Class, and I got to watch other teammates' videos below:

Lutra:

https://www.youtube.com/watch?v=IHjqfArZh9c

https://www.youtube.com/watch?v=ZF5O0Sj7gLI

1. is the topic well covered? 

Yes, they talk about BCI (brain computer interface) and Neuralink it is very well covered in many areas, such as healthcare.

2. is the presentation clear?

It is clear, and everyone used a decent mic to be able to understand them.

3. how is the quality of the research?

It is of good quality; they did a lot of research to present information about many areas in which BCI could help humanity. References were also provided in their videos.

4. how is the quality of the video production?

It is good quality for video production.

5. is the video engaging and interesting?

I would say yes and no. Some parts were a bit repetitive, and one of the team members talked with a flat tone that made me disengage a bit.

6. is the team work evident?

For the shorter video, teamwork is not evident because they used an automated voiceover, so I can't tell the team work. But for the long video, team work seems evident. 

7. is the video appropriate to the audience (either general public or technology professionals)

It is appropriate to both the general public and tech professionals.

Globe Tr'Otters:

https://www.youtube.com/watch?v=T9j7lscWYRo

https://www.youtube.com/watch?v=PjplkIYTEsg

1. is the topic well covered? 

Deepfakes was well covered. They even give real-life examples

2. is the presentation clear?

It is very clear; every member uses a clear voice and tone.

3. how is the quality of the research?

It seems like they researched, even on the news, and presented recent examples from the media and academic references.

4. how is the quality of the video production?

It has high quality audio and video. The only thing I want to mention is that at some points of the videos, the background music is a bit louder and overpowers the voiceover.

5. is the video engaging and interesting?

The visuals are very engaging; they used animation from pexels.com, and it engaged me.

6. is the team work evident?

Seems like everyone has a voice-over in the long video.

7. is the video appropriate to the audience (either general public or technology professionals)

It is for both general and professional audiences. The examples they give from real life make it really informative for both audiences. 

Code Busters

https://www.youtube.com/watch?v=3i3bgh1ClTs

https://www.youtube.com/watch?v=k4WZz3PkMGQ

1. is the topic well covered? 

The topic preventing cyber attacks with the use of AI is very well covered.

2. is the presentation clear?

It is clear because they also provide the script visually.

3. how is the quality of the research?

It seems like good quality because they were able to come with a lot of examples and ethical sides to it. And they provided a good amount of references at the end.

4. how is the quality of the video production?

The video is good quality, the audio is clear, and the slides are straightforward.

5. is the video engaging and interesting?

I would say yes and no because they read their slides, which made me disengage. They did not provide any visuals or animations to engage their audience.

6. is the team work evident?

It seems like everyone is talking equally in the videos, so teamwork is evident.

7. is the video appropriate to the audience (either general public or technology professionals)

It seems like it is appropriate. However, I would say that it could be more interactive for the general audience to keep them engaged. 

Week 7

 Week 7 (2/19-2/25)

1. Reflect on your team's Final Research Video Project Planning.  How did you collaborate?  What tools did you use to communicate and produce? Is the process smooth, what will you do differently next time in large collaborative projects?

Our team's collaboration for the Final Research Video Project was both productive and insightful. I played an active role in proposing the structure of the video, suggesting that we divide it into three main components to effectively cover the AI race between China and the U.S. This structure included an introduction, a detailed analysis of each country's advancements in the political, technological and economic component (with at least two minutes dedicated to each team member's contribution), and a conclusion to tie everything together. Splitting the video into distinct sections minimized the risk of overlapping content and ensured that each team member could focus on their assigned part without redundancy. This approach also helped us meet the project guidelines efficiently.

To facilitate communication and planning, we used Discord for team meetings, where we discussed and shared bullet points outlining each side of the AI race. I took the initiative to conduct extensive research on the topic, which allowed me to contribute well-informed ideas during our discussions. After finalizing the structure, we moved forward with scripting and are now in the process of recording the shorter video, for which we already have a completed script.

Overall, this experience has been a valuable lesson in teamwork and project management, and I look forward to applying these insights to future collaborations. The only thing I would change is to know the guidelines of this video in advance so that we can plan and come up with more solid ideas. 

2. Please reflect on the Lecture readings in this section and what you have learned from this week's activities.

After watching the video Life After Death by Powerpoint, I want to highlight how important it is to keep the audience engaged, and creating presentations that are long and overwhelming is the best scenario to disengage people.

I chose the video on TED talk: the wonderful and terrifying implications of computers that can learn.

https://www.ted.com/talks/jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn

It discusses the incredible advancements in machine learning and deep learning, highlighting both the opportunities and challenges they present. Computers, which once required detailed programming for every task, can now learn from data and perform complex tasks like playing games, recognizing images, translating languages, and even driving cars. For example, machine learning powers Google’s search algorithms, Netflix’s recommendations, and self-driving cars. Deep learning, inspired by the human brain, has enabled computers to surpass human performance in tasks like image recognition and medical diagnostics, even discovering new scientific insights in fields like cancer research. However, these advancements also raise concerns, as many jobs in service industries, which make up a large portion of employment, are now at risk of being automated. The rapid, exponential growth of machine learning capabilities means society must rethink economic and social structures to adapt to this new reality. While the potential for innovation is vast, the impact on employment and human roles in the workforce is a pressing issue that needs immediate attention.

Week 6

 Week 6 (2/12-2/18)

1. At this week's meeting, our team discussed focusing the capstone project on developing an App. We are unsure yet what kind of App, but we agreed on not making a video game for a few reasons. After taking upcoming classes and interning in some companies, we will be able to decide what type of app to build.

2. This week, I worked on the Portfolio; I decided to create it on Webflow to give it a visual and more friendly interface and develop some UI/UX design skills. Sadly, if I include more pages, I will get charged a yearly fee, so I will try to work with what I have. I am working on a cover letter, looking for one I recently sent to a company when applying for internships.

Also, our team decided to make the video next week. We will gather bullet points for ideas on the current AI race between China and the USA. We are motivated because it is a very controversial topic that happened a few weeks ago. Making many economic, political, and technological changes to the country. We want to follow a structured introduction for the professional video, including the Chinese and U.S. sides, the ethical impacts, and the conclusion. Next Wednesday, we will meet to put all the information together and work on the recording and visual components.

Week 5

 Week 5 (February 5- 11):

1. Support and Comment on Teammates' Goals:

https://wootarkkim.blogspot.com/2025/02/csumb-week-4-29-jan-2025-4-feb-2025.html?sc=1739076624125#c2859478532175007968

https://michaelsorensen.dev/posts/csumb-week-4

2. Possible Capstone Ideas

Some ideas I have in mind include developing an App that could improve people's lives for a community in my home country, Colombia, like a bike-sharing and tracking app that connects cyclists, provides safe biking routes, and offers accident alerts.

Another idea for automation systems in Colombia is to develop a platform that automates bill payments (utilities, fines, monthly payments) through a single app integrated with local banks.

Another idea could be a system that automates route planning for public transport in Medellin.

Lastly, I would like to develop something specific in the company while interning.

3. Keep Up With Your Learning Journal

This week, I've got to refresh my knowledge of how to write a persuasive/argumentative essay. The last time I did that was in an English class. I followed the outline for the ethical paper, so I got to use some of the skills I've used before. The most valuable thing I've learned this week was the Executive Interview because I got to interview an alumni from CSUMB and heard some of his advice and the approaches he took to be where he is today. This allowed me to see things more broadly and decide how to focus my career from now on. 

I applied for a good number of internships recently. There is a program for colleges in the San Diego area where recent grads or undergrad students apply for an internship with a local company, and the state of California pays the students, not the companies. This program was designed to help California's economy recover from COVID-19, so I hope that, through this program, I get to intern at a local company.

For a graduate program, after looking at the master's focus and curriculum, I am leaning toward an MS in Computer Engineering at SDSU or an MS in Analytics at Georgia Tech. We'll see if I change my mind by the time I graduate.

Industry Expert / Executive Interview Exploring Career Paths and Industry Trends

 Interviewing Daniel Howe:

Introduction

I interviewed Daniel Howe, a CSUMB alumni from cohort 7 (Spring 2018). He graduated in 2020 and is now the president of NeatMon, an agricultural tech company that provides monitoring tools for farmers. After reading an article from CSUMB about how he turned his capstone project into a real business, I chose to interview him. I found his journey impressive and wanted to learn more about how he did it. I was able to video call him for over 30 minutes.

Summary

Daniel worked in agricultural technology for nearly ten years as a product manager before deciding to pursue a more stable career for his family. While he was already working in tech, he lacked a deep understanding of programming concepts like data types, Big O notation, and AI. At CSUMB, he learned technical skills and how to think critically and problem-solve, which are essential.

His capstone project involved building a data visualization platform and a smart trash can device that alerted facilities when a bin was full. This project motivated him to work with the Institute for Innovation and Economic Development, where he participated in Startup Monterey Bay—a program that helps people turn ideas into real businesses based on market needs. However, launching a startup during COVID-19 was difficult because his potential customers were not operating normally.

Daniel highlighted that business, customer needs, and technology are the biggest challenges in his role. While using the latest tech is tempting, sometimes simpler solutions work better. He mentioned that many companies chase new technologies just to stay ahead, but most are not actually implementing AI—true AI requires a strong mathematical background and often a master’s degree in data science.

He also gave an interesting example about job security: in California, older programming languages like Pascal are still used in places like the DMV. Since these systems have not been updated, companies need engineers who know these older languages to maintain them, and this can be a stable and well-paying career path.

He emphasized the importance of learning to learn for success in the industry—picking up new skills quickly, building small projects, debugging efficiently, and taking breaks when stuck. He also stressed that writing efficient code and optimizing memory usage is crucial, especially in data-heavy applications like NeatMon, where clicking a button could return 300MB of data and cause an app to crash if not handled properly.

Reflection

One of the most interesting things Daniel said was his first question to me: Do you prefer working on long or short projects? I never thought about this before, but it made me realize that my preference could change my career path. Short-term projects fit web development and front-end work, while long-term projects align with application development or systems engineering. At the same time, being open to both short- and long-term projects could increase my chances of being hired in many industries.

His insights also made me reflect on the reality of the current industry. Many companies go for the latest trends, but only a few truly implement AI. Instead, it is essential to maintain existing systems, even old ones like those at the DMV, because they can be just as valuable. This showed me that being practical with technology, even sometimes working on the simplest thing, but getting it working well is more important than always trying to use the newest or most complex tool.

Future Steps

This interview made me realize the importance of learning efficiently, testing, and quickly implementing knowledge. I want to strengthen my skills in back-end technologies like TypeScript, React, and MongoDB while improving my ability to write optimized code for handling large data loads.

I also plan to explore long-term vs. short-term projects to see which fits better with me. I will focus on where I want to be in five years, whether in project management or application development. I will take Daniel’s advice to build small apps, test my knowledge, and challenge myself with different projects to find what fits me best.

Week 4

 Week 4 (January 29th - February 4th):

1. Set Educational Goals: When I set my educational goals, I picture myself focusing on the latest programming languages and frameworks to build great web projects. Mastering a front-end tool like React, a backend framework like Django, or both if I want to grow as a full-stack developer. To make my goal specific, I decided on something clear and measurable, such as creating an app that solves a problem for humanity while mastering many programming tools and beyond. I also ensure the goal is exciting enough to motivate me to practice and learn daily. Lastly, I want to enter more into data science in the upcoming months.

2. Set Career Goals: My career goal is to become a well-rounded engineer who masters front-end, back-end, full-stack, and data science skills. I see myself creating user-friendly interfaces, building strong server systems, and analyzing data to uncover hidden insights. I’m driven by the idea of solving real-world problems from start to finish and inspiring others along the way.

3. Take a wild guess of your percentile of the ETS Computer Science test: Based on the sample test, I see that the ETS Computer Science Major Field Test requires strong problem-solving skills in algorithms, data structures, programming, logic, and computational theory. If I want to score in a high percentile (let’s say 75% or above), I will need to work hard over the next 18 months to master every level of computer science. Hopefully, the content of the courses help me get there. 

4. Keep Up With Your Learning Journal: This week had a good amount of content; the AI's impact on my future was interesting because I learned about other students' views and thoughts on the subject. The outline for the ethical paper (I learned many things about it when researching information) and the executive interview, which I'll discuss in the next journal.