- Sajjad Kadar studied Intelligence at Georgia Institute of Technology as an undergraduate and graduate student.
- If you struggle with attention, math and commitment, you might want to reconsider majoring in AI, he said.
- If you don't major in AI, you can still get a job in tech or take courses related to AI later on.
Sajjaad Khader, 22, knew he wanted to go into software engineering when he started university, but he has some advice for those considering studying AI at university.
He spent three years earning his bachelor's and master's degrees in computer science from Georgia Tech, completing both programs by 2022.
I studied Intelligence and Modeling Simulation as an undergraduate and Interactive Intelligence as a graduate student, and I currently work as a software engineer in an intelligence-based team at a technology company.
With the AI race in full swing, universities like the University of Pennsylvania have begun announcing new AI-focused curricula, while others like MIT are offering online AI certifications. While the names of the degrees may change, universities have been offering AI-related courses and majors for years.
Kader said he believes computer science, especially with an emphasis on artificial intelligence, is one of the best and most valuable degrees out there right now.
But that doesn't mean it's for everyone: Kader has posted videos on TikTok educating college students about the less glamorous side of the field.
Speaking with Business Insider, Kader explained who might not be suited to studying AI at university.
1. Poor concentration
If you hate boredom, Kader says majoring in AI might not be for you.
Kader said that during his undergraduate studies, he worked on an AI research project to develop a genetic algorithm that could save lives in disaster-hit third-world countries. Kader said that while the project seemed interesting at first, he spent most of his four months developing simulations that had nothing to do with AI. It wasn't until his final month that he worked with genetic algorithms.
“It was kind of frustrating for me,” Kader said. “I kept asking my research mentor when he was going to start.”
Once we started developing the algorithm, we had to fine-tune certain variables to really tune the algorithm and improve it. The majority of the simulation part and afterwards, we just did small enhancements and improvements.
“There's very little flashiness or anything showy,” Kadar said.
2. I'm not good at math
AI, it turns out, isn't just about coding. Kader said that many courses labeled as computer science are actually heavy on math. In a TikTok video, Kader said the first assignment in his undergraduate machine learning course didn't have any code whatsoever, it was “six pages of pure math.”
“It's a little misleading in that respect,” Kader said. “The official number may be five or six, but the actual number may be closer to 15.”
One of the AI math courses he had to take was “Automata Complexity,” which he described as graphs and charts with “a lot of text and very few numbers.” Even for people who are good at analytical math and problem solving, Kader said the format takes some time to get used to.
“I think theoretical math is a whole other world in some ways,” Kader said. “A lot of people aren't familiar with it until they get to college.”
3. You have commitment issues
According to Kader, AI is meant to play the long game.
In the video, he said that to succeed at a top tech company, you may need to earn multiple degrees, and you also need to commit to a long-term vision for the project, as it may take time to get the results you want, he told BI.
This is something that could happen in many evolving technology sectors: Meta CTO Andrew Bosworth said in a March interview on Lenny's Podcast that when he worked as an early engineer at Facebook, he had to wake up every four hours to check on an anti-spam device they were developing.
Kader also said you need to be prepared to not always know what's going to happen next and remain willing to learn until you get it right.
“It's about dedication,” Kader said. “Not just physical dedication to the job, but mental dedication.”
Remember, you don't need to learn AI to work in tech
Kader said if he hadn't chosen computer science as his major, he would have chosen industrial engineering with a minor in computer science or artificial intelligence.
“I think this degree gives me a great opportunity to enter the technology industry whilst learning about corporate logistics operations,” he told BI.
Although AI is currently the hottest area in the tech industry, there is still demand for technical roles that aren't directly related to AI.
Allen Tran graduated from San Jose State University in 2023 with a degree in Computer Science. He took an elective in AI, but decided to continue with web application development over AI because he enjoyed seeing tangible progress in his work.
He currently works at Amazon and said he isn't worried about job security just because he's not in an AI-focused role.
“For AI-centric companies, you still need people to build websites. You still need people to build tools,” Tran said. “You still need people to support services and metrics and things that aren't related to AI.”
Even if you want to work in AI in the future, you don't necessarily have to choose it as your major.
Harper Carroll is a former Meta employee who will graduate with a master's in computer science from Stanford University in 2022 and specialize in AI. He said earning an AI degree will give him a solid foundation that will help him be more effective at work.
But if you want to learn the skills, she says there are coding bootcamps and online courses available now.
“But as AI becomes more prevalent, it will make sense for many roles,” Carroll said. “A boot camp or similar experience should be sufficient.”
Are you studying AI at university? Let us know what you think. Email the author at aaltchek@insider.com.
