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What are some potential career pathways or jobs I can go into when wanting to pursue a major in Artificial Intelligence and Machine Learning in college?

I am a current high school senior who will be attending college next year! I am really interested in different fields such as AI, Machine Learning, Cybersecurity, Psych, and Computer Science.

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Thank you comment icon Hi Ivy, This sounds exciting! I am currently working for HP and we're huge on AI. We have "HP Life"- where you can get free courses to expand your skills. I recommend you to check it out https://www.life-global.org/ Elainie Nguyen
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Teklemuz Ayenew’s Answer

Choosing to major in Artificial Intelligence (AI) and Machine Learning (ML) is an exciting journey with lots of career possibilities in different fields. To do well, start by learning programming languages like Python and get familiar with tools like TensorFlow and PyTorch. Understanding math topics such as linear algebra, statistics, and calculus is also important. Getting hands-on experience is crucial, so try working on personal projects, joining Kaggle competitions, and contributing to open-source projects on GitHub.

Online courses from places like Coursera, edX, and Udacity can boost your learning, while virtual internships with big tech companies like Microsoft, Google, IBM, and NVIDIA offer great experience. Stay connected with AI communities on platforms like Reddit’s r/MachineLearning and Stack Overflow, and attend conferences like NeurIPS to keep up with the latest trends.

While a graduate degree is helpful for research roles, having practical experience is often more valuable for industry jobs. Combining AI with areas like business, healthcare, or finance can lead to unique career paths, and participating in competitions can improve your problem-solving skills. Building an online portfolio, finding mentors, and exploring new areas like AI explainability and ethics will help you stand out and succeed in the AI/ML field.
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Matthew’s Answer

If you’re thinking about majoring in Artificial Intelligence and Machine Learning, you’re stepping into one of the most exciting and in-demand fields out there. There are a bunch of directions you could go, depending on what you enjoy most.

If you're more into the academic or theoretical side, you might love being a machine learning researcher or AI scientist. These roles are all about pushing the boundaries of what AI can do—designing new algorithms, diving deep into neural networks, or improving things like computer vision or natural language understanding. A lot of those positions are at places like Google DeepMind, OpenAI, or research universities, and they usually involve graduate-level work.

But if you’re more hands-on and love building stuff, then becoming a machine learning engineer or AI developer might be more your thing. These roles are all about taking models and actually deploying them in real-world applications—like making recommendation systems for streaming platforms, or designing smart features in mobile apps.

Then there’s the data side of things. You’ve got data scientists and analysts who use machine learning to find insights in massive datasets—super useful in business, healthcare, sports, finance—you name it. It’s a great blend of stats, coding, and storytelling.

If you’re drawn to specialized areas, you could dig into things like robotics, self-driving cars, or natural language processing (like building chatbots or voice assistants). There are even roles focused on the ethics of AI, which are becoming more important as this technology keeps evolving. You could end up shaping AI policy or making sure algorithms are fair and transparent.

And if you’ve got some entrepreneurial spirit, you could even start your own thing. There’s so much room to innovate—AI is being used in education, entertainment, fitness, mental health, and even fly fishing tech (you’d be surprised). You could absolutely build your own product or business around it.

Matthew recommends the following next steps:

First off, if you’re not already doing it, get solid in math and programming. Math—especially linear algebra, calculus, and probability—will be your best friend in AI. And programming? Python is the go-to language in the AI world, so getting comfortable with that early is a game-changer. If you already know some, great—level it up with libraries like NumPy, pandas, scikit-learn, and TensorFlow or PyTorch.
From there, take your learning into the real world. Build stuff. Start small. Maybe it’s a simple machine learning project like predicting house prices or building a chatbot. There are tons of beginner-friendly tutorials and datasets out there. The more you apply what you learn, the more it’ll stick—and you’ll also have something cool to show on your resume or portfolio.
Next, plug into a community. Join an AI or coding club at your school, participate in online forums (like Reddit’s r/MachineLearning or Kaggle), or get involved in hackathons. Being around other people with the same passion will keep you motivated—and you'll learn faster just by talking with others.
If your school offers electives or AP courses in computer science or data science, definitely take them. And if they don’t, that’s okay—online platforms like Coursera, Udacity, and Khan Academy offer some stellar (and often free) courses.
And finally, start thinking about internships or summer programs. Even if you can’t get into a big tech company right away, look for local startups, university research labs, or even volunteer projects where you can practice your skills in the wild.
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