This section shares my thoughts after participating in the First Cloud AI Journey program. The program is still ongoing, so this isn’t a final summary — just a mid-term perspective.
Overall: 8/10 – Satisfied
The program provides a structured hands-on learning roadmap that closely mirrors real-world cloud work environments. The standout points are the mentor’s approach and the thoroughly prepared lab materials.
1. Working Environment
Overall, it’s quite comfortable. I can ask anything without anyone making me feel bad or pressuring me with “how can you not know this?” Documents and announcements are well-organized and easy to find. One thing I feel is lacking is that since it’s remote work, there aren’t many opportunities for in-person interaction. If there were occasional meetups or coffee chats, I think everyone would get closer.
2. Support from Mentor / Team Admin
This part is very good — probably what impresses me the most. The mentor never gives the answer outright; instead, they often ask me back like “have you checked this?” or suggest reading more about a certain topic. At first, I found it slow because I had to figure things out on my own, but looking back, that approach helped me remember things much longer. As for the admin team, they’re also quick — things like account creation, credit allocation, or access permissions are handled early, so my learning is never interrupted.
3. Relevance of Work to Academic Major
It’s quite relevant. What I learned at school about networking and systems connects directly when doing AWS labs. The great thing is that the program doesn’t just teach theory but gets you hands-on right away, so I can see more clearly how classroom knowledge applies in practice.
4. Learning & Skill Development Opportunities
I’ve learned quite a lot — not just technical skills but many other things too. For example, writing documentation in Markdown, using Hugo, translating English blogs, or even paying attention to cloud billing. I didn’t think these were important before, but after doing them, I realize they are. The “learn by doing” approach through hands-on labs is much more effective than just reading theory.
5. Company Culture & Team Spirit
I really like this. Everyone shares knowledge freely without distinguishing between newcomers and veterans. Even as an intern, I feel my opinions are heard. The general atmosphere is that everyone wants to learn more, so I get drawn into it too.
6. Internship Policies
The program has a clear 12-week roadmap and provides AWS credits for labs, so I don’t have to worry about costs. The schedule is flexible, allowing me to balance it with my university classes. Lab materials are well-prepared — not too hand-holding but not too vague either. I find them at just the right level to require some self-study.
What I’m most satisfied with during the internship? It’s that “aha” feeling when I finish a lab and look back. Before, I only knew the names of AWS services and had a vague understanding from reading descriptions. But after actually configuring things myself and seeing them work, I truly understood what each component does and why it needs to be where it is.
What I think the program should improve for future interns? I think there should be a small group exercise (2-3 people) after completing the foundational phase. In reality, no one works alone, so practicing collaboration early would be beneficial. Also, I’ve noticed many common errors that everyone encounters during labs — like missing IAM permissions, incorrect routes, or insufficient policies. Having an FAQ page summarizing these issues would save a lot of time for future interns.
If recommending to friends, would I suggest they intern here? Why? Yes, but I’d be honest that it’s not easy. If someone wants to pursue cloud and is willing to invest time in real learning, it’s very worthwhile. But if they just want an internship for the sake of having one, they’ll probably find it tough. The program requires a lot of initiative.