A Personal Guide to AI Engineering: From Beginner to Pro

Hey there, welcome back! If you’re exploring ai jobs without degree and are anything like me when I started in the tech world, it probably felt like navigating through a maze with blindfolds on. I’m Jean, and I’ve been working in tech for over 15 years.

When I first began my career at IBM in 2007, I had no idea what I was getting into. Luckily, I’ve had the chance to be part of amazing opportunities, like being the 19th engineer at WhatsApp, which was acquired by Facebook for $19 billion. Since then, I’ve become a software engineering manager, and now I’m here to share my insights and advice with you, especially for those interested in ai jobs without degree.

In this guide, I want to provide a roadmap or a blueprint for those getting into software engineering, especially in AI or machine learning engineering, as that’s what everyone’s been asking me about. But these three simple steps are applicable to any field in software engineering, whether you want to apply it to AI or machine learning.

Think of it like a ladder that we can all climb, with lessons and choices at each level. I’ll call these levels – Level One: Start, Level Two: Level Up, and Level Three: Strategize. We’ll dive into each level, dissect the choices you can make, and how to navigate them, even if you’re aiming for ai jobs without degree.

We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.

Level One: Start

At this stage, the main goal is to get moving towards ai jobs without degree. Many folks find themselves stuck here, like playing Monopoly but never leaving the start box. This is where you break through your own barriers. Get out of your own way and start coding. Dive into building projects and get coding, even if the first few lines aren’t great. You’ll probably feel like banging your head against the keyboard at some point, but that’s normal and okay. It doesn’t mean you’re dumb or that others are smarter than you; it’s just part of the process.

At Level One, you won’t know how to be a good AI engineer yet, and that comes at Level Two, but starting is key here. There’s no way around this; you’ve just got to start coding. The Activation Energy Theory compares this to giving a little push to start a chemical reaction, and the Momentum principle says it’s like a snowball effect, making it easier to keep going once you are in motion.

So, for all beginner AI engineers, career switchers, or CS students aiming for ai jobs without degree, my advice is to overcome the fear of a blank screen and start coding. Start with baby steps. Build your first mini project. It doesn’t have to be grand, and no one has to see it for the first time.

If you’re not sure where to start or how to start, check out my other guide, “Learn AI Engineering Fast with ChatGPT.” I share tips on finding the perfect projects and how to get the ideas where to start, all using ChatGPT, guiding you step by step. You can also download the exact prompts you need to get going. So, I’m not going to focus on the step-by-step in this guide, but the point here is to stop watching tutorials and start building towards ai jobs without degree. Things will start making more sense when you start being really hands-on, and trust me, the more you do, the better you’ll be.

And the reason why I say to stop watching tutorial videos is because when someone’s just talking, and you’re listening, everything seems to make a lot of sense. But once you start coding on hands-on projects, things start to maybe click, or you might have better questions, and it’s just a whole other beast when you start going.

Once you decide to get started on your first project, the next question is often: What do I make next? What language do I need to learn? You’re going to have all these questions, and at this point, it doesn’t really matter. Just pick something that seems easiest for you. Stop getting caught up in all these questions about language and tech stacks and all the debate around it for beginners.

You know, it really doesn’t matter for ai jobs without degree. Python is often recommended, especially for AI and machine learning, and Python is great. Just use Python unless you have a strong reason why you should not be learning Python. Just pick Python and just pick any ML algorithm. They’re all great to learn. And just start building a project around it. Your first project might be just really simple and not very exciting, and that’s perfectly fine because the goal here at Level One is just to get started.

Now, at the end of Level One, you’re going to face an important choice to make, and this is Choice Number One. You have three options here. Choice number one: Give up. The question here is if you’ve tried coding and maybe you feel like it’s a bit much for you; you don’t really feel passionate about it.

It’s okay to acknowledge that, and engineering may just not be the thing for you. The important thing is that you gave it a shot. You tried it out. You were hands-on. You built some things. Now you won’t have regrets thinking maybe I should have tried it when I was younger or whatever. Now you can say that you’ve tried it and move on.

Choice number two is to switch tracks. Maybe this particular thing that you tried is not really your thing, and you want to explore a different type of software engineering, which is completely fine as well. There are so many types of software engineering and coding and languages that you can choose from. You don’t have to stick with AI, and that’s okay. If you choose number two, you just go back to the starting point. Go back to Level One and get started with something else. You can pick web development, app development, or whatever you feel interested in. Honestly, they’re all great options for ai jobs without degree.

Choice number three is to keep going. Are you ready to commit to AI engineering and take it really seriously? If not, that’s really okay. But if that is something that you are going to be committing to or you are interested in moving forward to Level Two, now it is time to level up for ai jobs without degree.

Level Two: Level Up

So, Level Two is all about becoming a better AI engineer for ai jobs without degree. The goal here is to dive deep because becoming a really good AI engineer is not going to happen overnight, especially if you don’t have a Ph.D. or extensive years of experience working in the tech industry.

You have a lot to catch up on here. At this level, you’re probably going to have to figure things out on your own, and it’s not going to be easy. Malcolm Gladwell talks about the 10,000-hour rule popular from the book, “Outliers.” It talks about the importance of prolonged and focused practice to excel in any field. It emphasizes the need for continuous hard work and practice to become an expert.

If you can manage to get a job at this stage, good for you, but chances are that it’s going to be really hard to get a job because you’re not quite there yet. Most companies are going to want to hire you once you’re really good. So, Level Two is all about leveling up for ai jobs without degree. You’ll continue to build interesting projects but using different types of algorithms. Maybe you tried a few different things in Level One. Now it’s time to dig deeper into the same ones or add to your portfolio different types of algorithms.

Your goal here is to build up your skill set, and each project that you work on will contribute incrementally, pushing you forward by 1% over time. As you build more projects, you’re going to gradually move toward creating more quality programs and projects that other people care about for ai jobs without degree. The path to leveling up may be different for every person, so keep trying different things to know what works for you. Keep iterating. Keep improving.

You might be asking at one point, what makes a good engineer? And I’m sorry to tell you, there’s no consensus on this. Some people spend a good chunk of their lives chasing degrees and Ph.Ds. And while that’s a fine route to pursue, if that’s not what you want to go for, that doesn’t have to be the only path. And if the idea of diving into a decade-long higher education program doesn’t really get you excited, that’s okay.

But here’s the deal. You’ve got to make up for that time. Having a bunch of projects on your GitHub is really not going to be enticing enough for employers to want to hire you, especially if those GitHub projects don’t even work in production. If you compare someone who’s been grinding away in a Ph.D. program for 10 years with you, who would you hire? And again, it’s not about the credentials or degrees or the papers or whatever you get, but it’s more about your skills.

And there are many ways to level up. You can launch your own business. You can launch your own website or an app. You can volunteer for local charities or businesses to create something really interesting for them. You can take on contracting gigs and build projects for your clients and get paid. There are many ways to gain hands-on real-life experience.

To recap, Level One was to start; Level Two was to level up; and now, just before getting into Level Three, Strategize, we have to make another choice. Each option comes with different sets of challenges and opportunities, and which route you want to go depends on your goals and where you see yourself in the world of AI and Engineering.

So now, you have leveled up on your skills, so you have some options to consider. Choice number one, Be Your Own Boss. If you go with option one, you get to be your own boss, working on the projects that you find interesting. You may have the freedom to explore different areas of engineering, but there’s really no guarantee that you’ll ever land a full-time job. And your income may be good, but it might be unpredictable. It also demands a high level of self-discipline and motivation to stay focused and productive on your own.

Option two is to switch tracks. If you go with option two, there may be more opportunities in different areas of software engineering, potentially. You might have a higher chance of landing your first role way more quickly than AI engineering. And transitioning into a different role might provide a more immediate source of income. You could learn new things, and maybe you might find those new things even more interesting, but depending on the role, it might mean you have to go back to step one and learn a few more skills, and it might even take you further away from AI engineering. And you might end up hating it anyway again.

Now, option three is to keep going. You can keep trying to become an AI engineer and keep looking for that AI engineering job. The competition is going to be really tough, and there aren’t a lot of entry-level positions in AI engineering, but if you’re really, really interested and passionate about becoming an AI engineer, this could be the right path for you. It is definitely going to be an uphill battle, but if you’re determined, you can probably do it.

So, as you think about these options, consider your career goals and aspirations, but also your skill set and the current job market demands. But no matter which route you go, the skills that you learn in Level One and Level Two will still help you become more successful in the long term in your software engineering or AI career.

Level Three: Strategize

This is where we’re going to talk more specifically about your job search strategy for ai jobs without degree and how to increase your chances of landing that perfect dream job. Let’s take a look at where you are in your job search. Let’s say you started job searching for ai jobs without degree, and if you’re not getting any calls from recruiters, there might be a problem with your resume.

And here’s a little stat for you: If you apply to about 100 jobs, you should be hearing back from the recruiters about 10 to 20 times. That is just the average statistics. And if you’re hearing back less than 10 to 20 times, that means something is off with your resume.

And if you’re in that situation, I encourage you to check out the Ultimate Resume Handbook. I made it for you to help you find the red flags in your own resumes. Studies show that recruiters only spend about 6 to 8 seconds looking at each resume. What they’re doing mainly is just to spot these potential red flags because they don’t have a lot of time to just really comb through every single resume because they get so much volume.

Go to our website, and the book is $20. You can download the Ultimate Resume Handbook and try to spot the red flags in your own resumes. And if that’s too much for you, you can’t spare $20, you can try talking to your school. Most schools have career counseling services included in your tuition. If you’re at a boot camp, you can try talking to the boot camp.

Step two is, let’s say you did fix all your red flags, and now you’re getting those interviews, but you’re not getting the job offers. This means you need to practice your interview skills for ai jobs without degree. How do you talk during your interviews? Can you do the coding challenges? We just need to practice answering these common questions. They tend to ask the same questions over and over.

Do the mock interviews and try to get more feedback to improve your interview skills. Again, there are programs that you can enroll in to get help on interview prep, but if you can’t afford one of those, do it with your friends. A lot of people are studying for interviews, so you can do it together and find some buddies that you can have some accountability with. And if you’re going solo, you can also try recording yourself just on your phone. It doesn’t have to be anything fancy.

Just make a video of yourself doing a mock interview or doing a coding challenge. See if you make any funny faces. Listen to your voice. How do you sound? Do you sound confident in the camera? And you can probably just learn a lot by watching yourself in the video. I’m also going to share some interview prep tips on my website for ai jobs without degree. It’s going to be all for free. Go check that out if you’re not sure where to start.

Step three: If you’re getting job offers but not the type of ones that you like, maybe you want to learn negotiation skills. I wrote an article with my friend who’s in the recruiting business. It’s called something like “Startup Equity Negotiation for Software Engineers,” so go check that out. It’s all free. You can also research industry standards. There are also websites like levels.fyi to help you know what your value should be.

I have a video about which software engineering jobs pay the most. You can check that out to see what the different levels are supposed to pay. But if you’ve made it to this stage, I’m pretty sure you’re going to be okay. So, big congratulations.

And that’s pretty much it. If you want general advice on software engineering career, I wrote an article about “Getting Ahead of 99% of Software Engineers in Your 20s.” So go read that, and good luck!

AI Jobs Without Degree: Best Tips

Breaking into the field of AI without a traditional degree can be challenging, but it’s not impossible. Here are some tips to help you navigate this path and increase your chances of landing AI jobs without a degree:

1. Build a Strong Portfolio: Your portfolio is your best tool to showcase your skills. Work on diverse projects that demonstrate your proficiency in AI and machine learning. Make sure to include detailed explanations and results to impress potential employers.
2. Gain Practical Experience: Practical experience is crucial in the AI field. Participate in internships, volunteer for projects, or contribute to open-source projects. Real-world experience will not only enhance your skills but also make your resume stand out.
3. Stay Updated with Latest Trends: AI is a rapidly evolving field. Keep yourself updated with the latest technologies, algorithms, and industry trends. Follow relevant blogs, attend webinars, and join online forums to stay informed.
4. Network: Networking is key in any job search, especially in a specialized field like AI. Connect with professionals in the industry through LinkedIn, attend industry conferences, and join AI-related groups to expand your network.
5. Leverage Online Courses and Certifications: There are numerous online courses and certifications available that can help you gain the necessary knowledge and skills in AI. Platforms like Coursera, Udacity, and edX offer courses designed by top universities and companies.
6. Showcase Your Problem-Solving Skills: Employers look for candidates who can solve complex problems. Participate in AI competitions and hackathons to showcase your problem-solving abilities and creativity.
7. Focus on Specialization: AI is a vast field. Specializing in a specific area, such as natural language processing, computer vision, or robotics, can make you more attractive to employers looking for experts in that niche.
8. Demonstrate Soft Skills: Apart from technical skills, soft skills like communication, teamwork, and adaptability are also important. Highlight these skills in your resume and during interviews.
9. Prepare for Interviews: AI job interviews often involve technical questions and problem-solving tasks. Practice coding and algorithm questions, and be prepared to explain your projects and thought processes in detail.
10. Be Persistent: The journey to landing an AI job without a degree may be long and challenging. Stay persistent, keep learning, and continuously improve your skills. Your dedication and passion for AI will eventually pay off.

By following these tips and continuously honing your skills, you can increase your chances of securing AI jobs without a degree and succeed in this exciting and dynamic field.

We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.