CSUMB CS Online Learning Journal - Ryan

  What went well? What would you improve? What was the most impactful part? What challenges did you face? What advice do you have for future SL students?     For this class I think what really went well was working with my team assigned to the InnSure service work. I enjoyed working with my team and attempting to solve the issues faced by InnSure when dealing with wildfire insurance coverage. I think the most impactful part was working on a real world problem and finding a solution that can have a positive influence in solving that problem. There were many challenges along the way, like learning how to use the Mission Model Canvas (MMC) and developing out Value Proposition Canvas (VPC), Our team was able to work through these challenges and achieve some real results.      For future students I would encourage them to have an open mind, and just try your best. This course is very much about brainstorming solutions and so alot of the learning will be done whi...

 This week we learned about two additional algorithms: Counting Sort and Radix Sort. Counting sort involved finding the frequency of a given value in an input array and then generating output based on that frequency. Radix Sort takes an set of input numbers and looks at the least significant digit in each entry and creates an output order based on that digit. The algorithm continues with each least significant digit and will order all the numbers once it is complete. One other topic I found this week to be interesting was the idea of dynamic programming where we keep an array of solutions to sub problems to help with future calculations.  Overall I felt this week provided great information on additional sorting algorithms and the concept of dynamic programming.

 This week we learned a great deal of new concepts. The first was how to utilize the quick sort algorithm and how it is based on the divide and conquer technique. This technique aims to break a problem into smaller and smaller parts until the problem is easily solvable, and then the solution is applied to essential conquer a big problem by breaking it apart. We also learned more about binary tree traversal and the different methods for moving through binary trees. We also learned about the concept of tree height calculation which is a good indicator of the worst case scenario in tree traversal. One of the big take aways from this week was learning about Kahn's algorithm and how it is useful for topologically sorting data. A lot of great concepts this week that I will have to revisit before the final.

 This week primarily consisted of the Mid term which encompassed the first three weeks of learning. So far, this class has been challenging, but I am beginning to grasp some of the main concepts. I find that doing a daily review of the materials I have learned helps me to feel a little more confident that I understand. I feel that the main ideas have been computing the time complexity of the algorithm and getting familiar with some established algorithms for solving common problems. I will continue to study the new material and review previous materials to continue to improve.

 This week explored algorithms including the brute force method by performing an exhaustive search. We also learned about two primary strategies to transverse a graph. These two methods were depth first search and breadth first search. Of the two I am more comfortable with the depth first search. I find it somewhat more simple to code an algorithm that performs a depth first search. When coding for the breadth first search I found I had to keep track of the queue and in the homework I had to keep track of what permutation produced the optimal path. I also learned about the divide and conquer strategy and how to use the master theorem to calculate time complexity. We will also have our midterm this week so I will need to review and solidify my understanding of the concepts presented in these first three weeks.

This week I learned more about asymptotic notations. I had previously only heard of Big Oh notation, and it was interesting to know that there were two other notations, namely Big Theta and Big Omega. I feel like I have some understanding of how these notations are used to describe an algorithm's efficiency, but I know I will need to review and use these concepts to really cement them into memory.  I also learned how to analyze an algorithm's efficiency for recursive and non-recursive algorithms. For the non-recursive algorithms the process is relatively straightforward. For recursive algorithms, I learned about a process called the "backward substitution" method. I did struggle with this concept and feel that I need to review it in the coming weeks to ensure I understand the material. Overall, I would say this week introduced several challenging topics that I will need to study and review.