Search Results for: --------

The AWS Academy Cloud Foundations course has been a great experience for me. It enriched my understanding of cloud computing including the basic principles and how they work in AWS. This training covers everything from what makes up a cloud infrastructure to hands-on practice with some of the most important Amazon Web Services like EC2, S3 or VPCs. There is no doubt that each of these modules gave me invaluable knowledge about technology that is all around us – the Cloud. They showed me practical exercises and explained real-life situations where we need to use these services in order to make our cloud infrastructures scalable, resilient and secure. Besides security this program also focused on cost optimization so now I know what are good ways not only to save money but also design efficient solutions which meet technical requirements within given budgetary constraints.

For this project, I chose a dataset from OpenDataPhilly focusing on the food landscape in Philadelphia neighborhoods. The dataset ‘Neighborhood Food Retail’ examines the availability of stores that offer healthy food options such as supermarkets and farmers’ markets, versus those offering fewer healthy options, like dollar stores and convenience stores. The outcome variable, “ACCESS,” aims to predict whether an area has access to healthy food options. Initially, the “ACCESS” column held three categories: being “Low Access,” “High or Moderate Access,” or “No Access” to healthy food options. To make it compatible with the decision tree model, I changed cells holding “Low” or “No access” to 0 and “High” or “Moderate” to 1. Utilizing Python and the CSV file, I was able to create a decision tree to determine the traits that determine the likelihood of a neighborhood having low quality options. Analyzing this dataset provides valuable insights into the food landscape and access to healthy food options in Philadelphia neighborhoods

 

The data suggests that supermarkets may not see value in opening locations in these neighborhoods, possibly due to the residents’ limited ability to afford fresh produce and higher quality products. This information can be useful for charities, funding organizations, and initiatives like the Cherry Pantry, as it highlights the specific areas that need help.

NeighborhoodFoodCSV

Decision Tree Results and Code

(Jung) – MIS2502-Extra_Points_Assignment

healthcare-dataset-stroke-data

After completing this optional assignment for MIS 2502, I chose a random dataset online and used that to manipulate the output of my decision tree. Attached are the answers to the questions included in the assignment as well as the dataset I chose. I experimented with different minimumsplits and maximum depths to generate the decision tree displayed here:

The task was to watch the videos and take the quizzes for all 10 modules for the Cloud Foundations course on AWS Academy. From the videos, I learned about a variety of topics. Like VPC’s, IAM roles, AWS support plans, and edge locations. I think I learned a great deal about AWS and thought it was very helpful throughout MIS 3406.

AWS_Academy_Graduate___AWS_Academy_Cloud_Foundations_Badge20240502-8-xeufvu

Completed 10 modules of videos with a knowledge check at the end of each module, for a cumulative of 20 hours of work. Then completed the certification exam to earn the certificate. The course went along with our class so it helped me to better understand key concepts that were applied in class. The course taught me about development using cloud technologies such as AWS’s IAM, S3, Lambda, EC2, VPCs, DynamoDB, and API Gateways to name a few.

 

During this project, I was able to use my skills from class and practice applying them to real world JSON files. Using what I know, I was able to create hypotheses based on real world data.

For this project, I practices using get JSON and using loops to find statistics on an array of data.

In the MIS2402 course we have learned javascript, jQuery, CSS and HTML. This project allowed me to display my understanding of all those skills while using a web API. The data set I accessed was about daily traffic counts on various streets in Chicago, Illinois.  I first created a web page that displayed a paragraph about a hypothesis that would be useful to test which would use the data I picked and a button. After clicking the button the code iterates through all the streets where traffic was counted and averages the daily traffic count. It also finds the street with the highest traffic counted and displays both answers in a sentence.

link to webpage: https://misdemo.temple.edu/tuk75720/ProPointProject/DailyTrafficChicago.html

 

Project description: Include the goals, results, project URL (if applicable), and what you learned in a brief paragraph.

My first function calculates how many how many Tesla’s are located in the Washington state. And my second function shows how what the average range of Tesla’s in Washington State are. My hypothesis is relevant as Tesla is more of the known brand when it comes to electric vehicles and with there being so many Tesla’s out in Washington alone, there could be many more in other states in getting 

In my research, I’ve noticed how electric vehicles are becoming more common in Washington state and with the company well known for their electric vehicles, Tesla has around 80,000 vehicles in the Washington state alone. This will benefit businesses and society as they see how well the electric vehicles are expanding and potentially could join in on the expansion of electric vehicles in some way. I learned with this coding project, I could learn much information from public data and that it can be very helpful in research and drawing up conclusions.

The PRO Points Project allow me to use programming to learn about the big data sets. I use programming to solve some questions from  this project. In this project I build a simple webpage to post some information and a button with some functions. I studyed “Drug overdose death rates, by drug type, sex, age, race, and Hispanic origin: United States” JSON data set, and find gender has big influence on the death rate.

From this project, I fully understand the convinience of the programming when we are trying to perform some tasks from a big data set. I also learn what should I include if I want to make a webpage.