CST 499 Week 11

 This week I got through the first four lessons of the fast.ai Practical Deep Learning course, which has been pretty challenging but really interesting and already has me thinking of some cool project ideas. I also went ahead and scheduled my AWS Cloud Practitioner exam for Monday 3/30 and have been working through practice tests to get ready. Next week I want to keep pushing forward with fast.ai, but I also want to start working back toward Azure Fundamentals so I stay somewhat aligned with my original proposal. The main challenge right now is just balancing everything and keeping up with the pace, but nothing I need help with at the moment.

Comments

Post a Comment

Popular posts from this blog

CST 489 Week 4

I am beginning a Scrum certification, which I chose because Agile and Scrum practices are used across many roles and industries, making them valuable regardless of specific technology or position. This week I reviewed the core ideas behind Scrum, including its principles, roles, and processes. While I have worked within Scrum teams before from a contributor perspective, this material helped me better understand the bigger picture of how everything fits together.
Read more

CST370 Week 3

 This week we went over BFS and DFS algorithms. We covered how BFS uses a FIFO queue, while DFS uses LIFO stacks. The first homework focused on DFS and used recursion to take advantage of the implicit stack. Our second assignment was on the Traveling Salesman Problem, using brute force to try all possible paths. Since the input could have up to 15 cities, the program had to generate and check every permutation, which really showed how quickly brute force becomes inefficient.
Read more

CST370 Week 5

     This week we went over Kahn’s algorithm, Quick Sort, and how to traverse a BST. I struggled a bit on my first read-through, but going step by step and writing things out helped a lot. Following the pointers in Quick Sort and tracking each step made it easier to understand. For Kahn’s algorithm, building the in degree table and manually popping nodes off my paper queue helped me visualize the process and work through it more clearly. Breaking things into smaller chunks made the material feel a lot more manageable.
Read more