A Gen Z software engineer studied AI in college. He says you shouldn’t major in it if you fall into one of these 3 categories.

  • Sajjaad Khader studied intelligence in undergraduate and graduate school at Georgia Tech.
  • He said you may want to rethink majoring in AI if you struggle with attention, math, and commitment.
  • If you don’t major in AI, you can still get a job in tech or take courses on it later on.

22-year-old Sajjaad Khader knew he wanted to go into software engineering when he started college — but he has some advice for people considering studying AI at university.

In three years, he received his Bachelor’s and Master’s degrees in computer science from Georgia Tech and finished both programs by 2022.

In his undergrad degree, he concentrated on intelligence and modeling simulations. In grad school, he specialized in interactive intelligence. Now, he works as a software engineer at a tech company on an intelligence-based team.

With the AI race in full fledge, schools like the University of Pennsylvania are starting to announce new curriculums dedicated to AI. Other universities, like MIT, offer online AI certificates. Although the name of the degree may be changing, schools have been offering courses and concentrations in AI for several years.

Khader said he thinks computer science, especially with a concentration in artificial intelligence is one of the best and most valuable degrees at the moment.

But that doesn’t mean it’s for everyone. Khader posted a video on TikTok to tell college students about some of the not-so-glamorous aspects of the field.

Khader outlined who might not be well-suited to studying AI at college.

1. You have a low attention span

If you don’t like boredom, Khader said majoring in AI may not be for you.

Khader said when he was getting his undergrad degree, he worked on an AI research project that entailed trying to develop a genetic algorithm that could save lives in a disaster-struck third-world country. Khader said the project sounded cool at first, but most of the four months were spent developing the simulation, which had nothing to do with AI. It wasn’t until the last month that he dealt with genetic algorithms.

“It was kind of like irking me through it,” Khader said. “Like I kept asking my research mentor like, when do we get to it.”

Once he started working on the algorithm, he had to hyper tune it by tweaking certain variables to improve it. A large part of the simulation part and afterward was making slight enhancements and improvements.

“The flair, flashy things is very small,” Khader said.

2. Math isn’t your thing

It turns out that AI isn’t just about coding. Khader said many courses labeled as computer science were actually focused on math. Khader said in his TikTok video that his first assignment in an undergrad machine learning course had zero code and was “six pages of pure math.”

“It’s kind of deceptive in that regard,” Khader said. “So the formal number might be five or six but the actual number might be closer to 15.”

One of the AI math courses he had to take was “automata complexity,” and as he describes it, “a lot of letters and barely any numbers” mixed in with graphs and charts. Even if you are good at analytical math or problem-solving, Khader said it takes to get used to this form.

“Theoretical math, I feel like, is a different beast in a sense,” Khader said. “A lot of people aren’t familiar with it until you get to college.”

3. You struggle with commitment issues

AI is all about playing the long game, according to Khader.

In his video, he said that to become successful at a top tech company, you may have to get more than one degree. You also have to be committed to the long-term vision of the project because it can take time to get the results you want, he told BI.

This can be the case in many evolving tech sectors. Meta’s CTO Andrew Bosworth said in an interview on Lenny’s Podcast in March that when he worked as an engineer in the early days of Facebook, he had to wake up every four hours to check an anti-spam device that he was developing.

Khader said you also have to commit to the mindset of being in a constant state of not knowing what’s next and still being willing to learn until you get the right result.

“It’s that commitment,” Khader said. “Physically in terms of the work you’re doing, but also mentally.”

Remember, you don’t need to study AI to work in tech

If he hadn’t chosen computer science as his major, Khader said he would have chosen industrial engineering with a minor in computer science or artificial intelligence.

“I think this degree gives you an excellent opportunity to get into tech, while also learning logistical operations of a business,” he told BI.

Even if AI is the hottest field in the tech industry right now, there is still a need for tech jobs that don’t apply directly to AI.

Allen Tran graduated from San Jose State University with a degree in computer science in 2023. While he took an AI elective, he decided to stick with web application development over AI because he enjoyed seeing tangible progress in his work.

Now, he works at Amazon and he said he doesn’t feel concerned about job security just because he’s not in a role that focuses on AI.

“In very AI-centric companies, they still need someone to build a website. They still need someone to build tools,” Tran said. “They still need someone to support services and metrics and other things that are not related to AI.”

Even if you may eventually want to work in AI, you don’t necessarily need to pick it as a major.

Harper Carroll is a former Meta employee who received her Master’s at Stanford in computer science in 2022 and specialized in AI. She said getting a degree in AI gives you a solid foundation that may help you be more effective at your job.

But there are coding bootcamps and online courses available now if you want to learn the skills, she said.

“But as AI becomes more ubiquitous it makes sense that for many roles,” Carroll said. “A boot camp or similar experience should suffice.”

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