Welcome back to “From Linux to Lambda,” a series of blog posts where I take a look at current day cloud services and technologies and where they came from. As a DevOps engineer who started coding after AWS was launched and Cloud already dominated the industry, it’s been interesting connecting the dots for myself on…
At the recent AWS Global Summit in NYC, the mention of a course which was a collaboration between AWS and Deeplearning.AI called Generative AI with Large Language Models which seemed like a good way to learn more about the workings of LLMs. I recognized Andrew Ng from his hit AI for Everyone course when I
I recently attended AWS’s Global Summit in New York City and don’t remember an AWS event with such a clear theme. As with the world in general, Generative AI was the focus everywhere from talks on prompt engineering, many existing vendors advertising their app’s new AI functionality and the keynote itself. Many new products and
What is this site? Who is Nick? Are these the questions we ask ourselves? What is this site? The current purpose of this website is for Nick to convey his learnings and insights from working as a Software Developer / Cloud Engineer for the last five years. He will attempt to cement his understanding of
As someone who got into programming through a non-traditional method I’ve always wondered what I would have learned with a traditional computer science degree that I didn’t get exposed to on my path. If I got confused on something or stuck on a bug, I’d assume that it was something I would have learned in
I’ve reached the final course in my list and one that I’ve been pretty excited for. While I haven’t been the most consistent blogger, the first time I realized the blog could be useful for sticking to projects was with my series of posts going through Kaggle competitions. Before that, I’d started watching through machine
While Computer Systems Engineering should be a course I’m excited for, this has been a course I’ve been somewhat dreading as it seems to have the least straightforward way of approaching it on MIT OpenCourseWare. Searching for it normally shows a version from 2018, however this only contains lecture slides and very scarce notes from
Throughout my time coding, it often occurred to me that I had little knowledge about how computers work. I had a base level knowledge of bit calculations and knew compilers and interpreters were used to translate the high level Python code to instructions the computer could understand. This course goes into a lot more details
The ninth course in this series goes back to physics specifically looking at electricity and magnetism, where the first physics course looked at classical mechanics. A lot of the course feels like the full course follow up to Intro to EECS’s section on circuits and it probably makes the most use of calculus a course
I’m still working on the project going through MIT’s Open CourseWare to figure out what I missed by not doing a Computer Science degree. Software Construction is course number eight and mostly focuses around programming using Java. Of all the courses so far, this one is the most related to actually writing software. Unfortunately, there
The seventh course in my series going through MIT Open CourseWare courses looks at Design and Analysis of Algorithms, an undergraduate course on algorithms that seems to be a natural follow up to Introduction to Algorithms. This course goes further with showing techniques for solving NP-complete problems such as incorporating randomness and other tricks with
