You want to get your first AI job but have no experience. What’s the best way to get started?
Learn the basics
Forget toy data; dive into reality: If you want to land your first AI job, you need to start working with real-world data. No more sanitized examples; it's time to face the thrilling complexities you'll encounter in the trenches. Kaggle competitions & government databases are full of potential - each record is a puzzle piece to solve.
Think beyond memorizing algorithms; master the fundamentals like linear algebra, calculus, and probability, the true building blocks of AI magic. Don't just learn, do. Tackle challenges, join hackathons, and build practical tools like a sentiment analysis app for your favorite restaurant. This is where the rubber meets the road, where you transform from student to practitioner, ready to tackle the world of AI.
Build a portfolio
Albert Einstein said, "The important thing is not to stop questioning." Don't just build another faceless chatbot. Infuse your projects with purpose, with a story that reflects your passion. Predict traffic congestion in your city and analyze music genres for emotional resonance – these projects showcase your problem-solving prowess and resonate with real-world issues.
But don't go it alone! Join the vibrant open-source AI community. Contribute to existing projects, fix bugs, and add new features. Showcase your coding chops, sure, but more importantly, demonstrate your ability to collaborate, learn from others, & contribute to the collective advancement of AI. Let your contributions speak volumes about your potential as an AI professional!
Network and connect
How does AI impact fields beyond just algorithms and code? The answer lies in building a diverse network beyond just fellow AI nerds! When you attend a meetup on responsible AI development, you rub shoulders with data scientists who understand the business side, entrepreneurs who see the bigger picture, and even ethicists who ensure AI stays on the right track.
It's not just about showcasing your expertise by answering questions on forums; it's about learning from diverse perspectives and building a reputation as someone who thinks beyond the code. And the cherry on top? Finding a mentor, an experienced AI researcher who can guide you, review your projects, and help you navigate the exciting yet complex world of AI.
Research and apply
Follow these tips:
Tip #1: Speak their language. Research each role and highlight projects that address their needs. For example, when applying for self-driving car jobs, showcase your computer vision and sensor fusion skills instead of sending out generic resumes.
Tip #2: Think outside the "AI Job" box. Internships and entry-level roles, even if not labeled "AI," can be your golden ticket. Many companies hide AI projects within these positions, offering a valuable stepping stone.
Tip #3: Use LinkedIn and events to connect with company insiders and talk to the people who do the work!
Tip #4: Highlight your problem-solving and communication skills, along with finance data analysis experience, when applying for an AI startup role.
Prepare and practice
Imagine acing your AI interview, confidently discussing image recognition algorithms and ethical dilemmas. That's the power of preparation! Platforms like LeetCode and HackerRank become your coding dojo, where you master AI-specific challenges relevant to your desired role. But remember, AI isn't just about code. Practice answering behavioral questions – how would you handle an ethical AI dilemma? Explain your teamwork approach to a panel of engineers. And don't forget the soft skills: clear communication is key to explaining complex ideas to non-technical folks. Hone these skills through coding competitions or hackathons. Stay ahead of the curve – follow AI blogs, research papers, and online discussions.
