Hi everyone! I'm an early-career developer with a ...
# ai-news-and-resources
c
Hi everyone! I'm an early-career developer with a strong interest in AI and Machine Learning. I'm looking to upskill and eventually transition into AI Engineer roles. Could you recommend the best courses or certifications that are both valuable for learning and help strengthen my resume? I’d love to hear what worked for you or what’s currently in demand in the industry. Thanks in advance!
s
Depends how serious you are and what's your budget. There's a lot of free online resources on LLMs/ML through MOOCs like edx.org and coursera.com (these tend to be more highlevel, although some of the edx courses offered by big Universities tend to be more in-depth). If you want the classroom experience for free, pretty much all courses anything ML/AI related are available for free through MIT opencourseware. Stanford also has ML/AI courses online for a price (not as extensive as MIT opencourseware, but for less than $500, you get 1 CEU validating you took the course) If you're more serious, you can do Stanfords SCPD program and take individual graduate level courses in ML and AI (which can count towards a degree, so they are heavyweight Resume accolades) with no commitment to actually complete a graduate degree. These are pricy though (roughly $4k to $6.5k per course) and are the real deal, so expect the pace and challenge to be top tier. Also, they offer AI graduate certificate (which is the next best thing to a Graduate degree from Stanford) by just meeting the required courses (complete 4 courses in their list and just apply to get the certificate). Getting into SCPD program is a lot easier than applying to graduate school, you just have to be committed once you start. The better option if you're really serious is Georgia Techs and UT Austin's online Masters in Computer Science (UT also has a Master in AI if you prefer). 10 courses and $10K, and you get the same degree as the one student's get by attending physically, and you can take a quality AI courses from world renowned top-tired universities (or you can take 4-5 graduate courses in AI then dropout and do something similar to Stanford's SCPD program for $4k-$5k instead of $20-$25k)
structuring your resume so that it shows you're serious about AI is the most importing thing, having courses, degrees or certifications from grad schools are the lowest hanging fruits (not necessarily easy to do, but easy paths to follow). You can also just do free-path and do work in open-source comunities to build your resume up from an experience perspective. In tech, an applicant with serious experience and achievements under his belt will usually get a chance to interview, which is where you can seal the deal even if you don't have a lot of formal classroom experience. If you have both classroom and practical experience, even better
Also, AI as we know it right now (former buzzword being deep learning), has matured quite a bit since the 2010s, but is still mostly in research realm, so if you want to get into the model architecting, training, tuning aspect of it, this is what you're getting into. There will be a lot of demand for AI engineering though, since now we're in a phase where models and datalakes are so large, that just supporting the infrastructure to train these experimental models is a hard engineering problem, and this requires a lot of engineers who can manage large clusters using systems like kubernetes, and can implement custom code to manage resource usage and communication from these large distributed systems. The Masters in CS degree can more easily enable you to follow both paths, albeit at a cost and commitment (not the only path though and just my opinion)
c
Thank you so much for taking the time to share your insights I really appreciate it! Your suggestions are super helpful as I map out my learning path into AI/ML. It means a lot, especially as someone early in the field. Thanks again!
s
Not a problem : )
p
Really great advice above! 🙌 I'll just add in some more for the resources. • Hugging face has some great free courses that you can follow at your own pace, they're releasing new parts of the agents one: https://huggingface.co/learnDeeplearning.ai (on coursera too) has longer specializations like CM mentioned, but they also have a lot of new short courses for free that are new and have cutting edge content usually from AI tool companies. • datacamp has a lot of good looking newer AI content if you like their platform/teaching style. • Udacity has a lot of AI/ML content as well. Some of it used to be free, but you can also pay and get code reviews (and maybe mentorship still?) • I've read a lot of books recently as part of #C06AAG8LU9M and they have been great! If you're looking for LLM content I really like Building LLMs for production as a practical start, Build a Large Language Model (From Scratch) for a deeper dive on how LLMs actually work, and AI Engineering for going deeper into the theory of practices around AI engineering. I used to work at programming bootcamp and when people asked what we taught that they couldn't learn for free online, I would say "nothing" 😂. Sometimes paying for the structure, accountability and access to mentors can really help accelerate your learning. I usually recommend starting with free materials around the subjects you're interested in and feeling out if having more structure from one of the paid MOOCs is something you'd benefit from! Also most companies building tools in the AI space do free events which are usually very educational even if you don't end using the exact product.