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How To Get Into Software Engineering In 2024 | How To Start Without Any Experience?

3.7K views· 140 likes· 10:55· Dec 9, 2023

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Is almost 2024. Will software engineering continue to be an important field in 2024? What can you do to increase your chance of finding a job? 💻 Google Coding Certificate: https://imp.i384100.net/zNjB4r 📌 Software Engineer Tech Essentials: https://tinyurl.com/bdhywpj4 🔖 Stay Safe Online with Aura: https://aura.com/sandra 🔒 Get 3-months free with ExpressVPN: https://expressvpn.com/withsandra My Camera Gear: https://amzn.to/3zJqFIA Follow me on IG: @techwithluca Brand/Collab Email: techwithluca@gmail.com Tech & Boba Podcast: https://tinyurl.com/4ehpxakc tags: learn programming,how to learn how to code,get a job in tech,tech jobs with no experience,coding job,learn javascript,how to get into software engineering,how to get into software engineering with,how to get into software engineering without a degree,how to get into software engineering without experience,how to become a software developer,how to become a software engineer without a degree,How to become a software engineer,how to learn programming effectively Disclaimer: This video is not officially endorsed by the employer. The views, opinions, and experiences expressed herein solely belong to the subject and do not represent those of the employer. 00:00 My experience as a software engineer 02:37 The most popular programming language 03:47 High demand roles but not enough people 06:25 Study the next big stack 07:03 Degree & Bootcamp 08:09 How to stay relevant as a software engineer 10:25 Conclusion

About This Video

In this video, I break down how to become a software engineer in 2024, especially if you’re starting with zero experience. 2023 was a wild year—layoffs, over-hiring correction, and nonstop generative AI breakthroughs—so it’s normal to ask if SWE is still “worth it.” From my own experience going through multiple rounds of layoffs, I’ll be honest: the anxiety is real. But I’ve also seen companies spin up brand-new generative AI initiatives and hire engineers to build productivity tooling (code completion, code review helpers, internal AI tools). Overall, I still think the direction is positive, and new opportunities will keep showing up. Then I get practical about what to learn. I explain two ways to choose a path: (1) go with the most popular/in-demand route like full-stack JavaScript (tons of roles, tons of competition, but also tons of openings), or (2) pick “high demand but not enough engineers” niches where replacements are harder—like Android (Kotlin) and backend/infrastructure with Go. I also mention Julia as a “watch this space” language in ML/scientific computing. Finally, I talk about degree vs bootcamp vs self-learning, and why continuous learning matters even more now: AI tools can be helpful, but they lack depth unless you already know what “good” looks like.

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