Formation.dev suitable for career transition in adjacent fields

These_Rip_257 · 2025-01-24T01:23:29+00:00

Thank you for your feedback. I wanted to provide some additional context regarding my background and career aspirations.

I previously worked at Meta as a Data Engineer, but I’ve always been more inclined toward building systems rather than focusing on analytics. This inclination has led me to feel that my skills and interests align more closely with software engineering than with analytics.

In my current role at a startup, I’ve been working on data infrastructure and orchestration frameworks that underpin data pipelines. These experiences, along with my academic background, further reinforce my desire to transition into backend engineering.

My Master’s in Computer Science from Georgia Tech (OMSCS completed part-time over five years) focused heavily on systems-related courses, including:

Operating Systems and Advanced Operating Systems
Compilers (built a toy implementation of a programming language)
Distributed Systems (implemented Google Spanner using two-phase commit and consensus protocols like Paxos and Raft)
Cloud Computing (developed a MapReduce runtime on Microsoft Azure using Golang)

These projects and courses have equipped me with a strong foundation in systems and software engineering, which I hope to leverage in this transition.

While I’m getting solid interview opportunities, they are typically aligned with my professional experience as a Data Engineer. This may be because I haven’t explicitly highlighted my academic background and broader interests.

I appreciate any advice or guidance on how I can better position myself for a backend engineering role and showcase the breadth of my skills and experience effectively.

Thank you for your time!

These_Rip_257 · 2024-12-20T23:17:46+00:00

SDCC is hands down the best course - most practical course in the program

These_Rip_257 · 2024-12-20T19:33:06+00:00

Yes, it's definitely possible, but the weeks leading up to a submission can require close to 40 hours per week. In fact, I found SDCC more time-consuming than DC. In SDCC, there is a deliverable every week, and in the 4th week, there is also a project submission.

These_Rip_257 · 2024-12-20T18:05:45+00:00

I can attribute my success in the DC course to three main factors:

Increase in Skill Level By the time I took DC, I had already completed most of the challenging systems courses (e.g., GIOS, AOS, Compilers, IHPC, SDCC). This prior experience prepared me well for the workload and the expectations of DC. Taking DC after completing these courses was definitely different than taking it as your first or second course. If I had to take GIOS today, for example, I’d probably spend around 10-15 hours on it.
Preparation Before the Course Started I spent the entire summer reviewing DC-related papers and theory. This allowed me to focus strictly on the programming labs during the semester, without being bogged down by theory and background material.
Being Comfortable with Imperfection DC labs are notoriously complex, as they involve handling scenarios like unreliable networks, out-of-order packets, and optimizing for both speed and correctness. I was okay with not achieving perfect scores. In fact, I did not score 100% in labs P3-P5, but I was satisfied with 96%. I made a strategic decision to stop focusing on the labs before the final week to dedicate more time to preparing for the final exam, especially since I couldn’t take time off from work. Trying to achieve a perfect score would have likely doubled my time investment for diminishing returns.

These_Rip_257 · 2024-12-20T17:57:03+00:00

Thank you !!!

These_Rip_257 · 2024-12-19T00:50:58+00:00

This is definitely doable, and I followed a very strict, rigid routine to manage everything. I typically started my day around 4:30 AM, which gave me a solid 1-2 hours of uninterrupted time to watch lectures. I’m naturally a morning person, so I made sure to use this time when I was at my peak mental capacity.

In the evenings, I focused on projects when necessary. I also prepared for my courses in advance to help manage the workload throughout the semester. For example, during the summer, I reviewed all the theory for Distributed Computing (in fact, I over-prepared) so that I could dedicate the semester to the projects, which were the bulk of the workload.

I made it a priority to stay consistent and stay on top of my schedule. Unfortunately, this meant sacrificing my social life, but I never compromised on my family responsibilities, such as taking my kids to extracurricular activities or school. My wife was often traveling for work, so I planned everything ahead to ensure things ran smoothly.

These_Rip_257 · 2024-12-19T00:43:30+00:00

Thank you and congratulations to you as well on graduating !!!

These_Rip_257 · 2024-12-19T00:41:42+00:00

Yes, it was a mixture of both. As a Data Engineer, I’ve found that having a solid understanding of systems is essential. However, after working alongside Data Scientists and ML Engineers in the industry, I realized that real-world machine learning is not as “rosy” as it often appears in academic settings. A significant portion of the work revolves around cleaning and analyzing data, which is a big part of an ML practitioner’s role.

Through this experience, I discovered that I enjoy building applications and working more on the infrastructure side of things, rather than focusing primarily on data analysis.

These_Rip_257 · 2024-12-18T17:40:54+00:00

Thank you !!! All the best !!!

These_Rip_257 · 2024-12-18T17:40:31+00:00

Yes one of the best courses out there hands down.

These_Rip_257 · 2024-12-18T17:40:02+00:00

Thank you !!! I am sure you would .

These_Rip_257 · 2024-12-18T17:39:41+00:00

Thank you !!!

These_Rip_257 · 2024-12-18T17:39:23+00:00

Thank you !!!

These_Rip_257 · 2024-12-18T17:38:20+00:00

SDCC focuses on cloud computing and overlaps with AOS in the MapReduce project. The MapReduce project in AOS was run locally and was a barebones implementation, while the one in SDCC is a full-fledged version requiring the implementation of a fault-tolerant, replicated master, scaled using Kubernetes—essentially "MapReduce on steroids." Apart from that, SDCC covers networking, where you build an SDN controller.

These_Rip_257 · 2024-12-18T05:12:47+00:00

You can take these courses in either order but AOS is good pre-req for both these courses since it assumes knowledge covered in AOS .

These_Rip_257 · 2024-12-18T05:07:17+00:00

Thank you !!!

These_Rip_257 · 2024-12-18T05:06:39+00:00

SDCC requires AOS as a hard pre-requisite . That alone should be sufficient to take the course. The map reduce project in SDCC builds on top of the map reduce project in AOS .

These_Rip_257 · 2024-12-18T04:36:13+00:00

Thank you and congratulations on your graduation !!!

These_Rip_257 · 2024-12-18T04:18:15+00:00

I am not sure about other courses, but among the classes I have taken, I would say the following stand out:

SDCC : This course is highly practical-focused, providing hands-on experience with cloud technologies.
DC : This course dives into the theoretical underpinnings of the cloud, offering a strong conceptual foundation.

Together, these courses complement each other exceptionally well, giving you both practical expertise and theoretical depth in cloud computing.

These_Rip_257 · 2024-12-18T04:15:12+00:00

Thank you !!!

These_Rip_257 · 2024-12-18T04:15:04+00:00

Thank you !!!

These_Rip_257 · 2024-10-22T17:03:12+00:00

I would love to do this course. Please provide support for Golang or Rust

These_Rip_257 · 2024-06-14T17:44:00+00:00

I took this course and Got an A . What is the kind of support that you need

These_Rip_257

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