Semester-Long Projects (SLP) is a great program to enrich coding skills in a group setting. Participants are formed into groups of similar interests. Each group is led by a mentor to build a unique coding project. SLP includes workshops like git, inclusive design, and other topics to aid the project's completion. At the end of the semester, the groups come together for sheCode's SLP Demo Day to showcase their project!

We congratulate every member and team lead on finishing SLP of 2022!

Thank you for your 10 weeks of teamwork and dedication! You have accomplished these past 10 weeks and should be proud of all the work you have done. We hope that SLP has encouraged you to explore more about Computer Science and inspires you to continue pursuing projects outside of class. We hope you had fun and learned a lot! sheCodes and sheBoard are so proud of you and we can’t wait to see where you will go from here.
-Laura Siu (she/her) sheCodes Internal Vice President 2022-2023

Judges for SLP 2022

• Daisy Tang

• Markus Eger

• Mohammad Husain

• Lan Yang

• Yu Sun

We would like to thank you judges for being a SLP Demo Day Judge! We appreciate you sharing your expertise and guidance with our members. On behalf of sheCodes, we sincerely thank you for taking the time to help create a meaningful experience for our SLP participants.

Team Introduction

• Tam Dinh

• Allison Ly

• Youstina Gerges
• Joanna Cornejo
• Francisco Ramirez
• Shavleen Singh

About the Project

We are a team of upperclassmen that wanted to try something new and gain some more experience. Since we all have some coding experience, we split the project into two parts: Intro to Coding + Interview Preparation. For our interview prep, we focused on behavioral questions and helped each other practice for technical interviews. Our project is a to-do list that allows users to assign their tak in specific categories: urgent, important, medium, and low.

Co-Leads
Tam: buttons to submit and remove task(s)
Allison: facilitated coding interview prep.
Both: organized meetings, sent announcements, assisted members

Members:
Joanna: design of the website
Youstina: text box that takes user input
Shavleen: displays user inputted task(s)
Francisco: notification of upcoming task(s)

Tools

• HTML 5
• CSS 3
• Javascript
• Git/GitHub
• Visual Studio Code
• CodingBat (With Java)
• Discord and Zoom
• Google Docs

Challenges

• Scheduling and time management
• Trouble with tool installation
• Technical issues with pushing/pulling to github
• New languages to learn
• Virtual meetings

Given More Time...

• Creating a more user interactive website
• Add in more UI and UX details

Team Introduction

• Allison Fung

• Raymar Lagos
• Julia Alfaro
• Evelyn Vu

About the Project

Change of Scenery Website
Link to Figma


The team created a study helper website inspired by imissmycafe.com. The user can choose from a selection of scenery images includes: environment sounds, work/break timer, Spotify playlist, and “Trip Summary” that lists which scenery the user has visited. The work and break timer is an adjustable feature with two choices, a pomodoro and custom timer.

Team Lead:
Alison: work on Figma design, Category pages layout, Scenery audio settings organized meetings, delegated parts of the project, etc.

Members:
Julia: created Figma design, Category pages layout, Scenery page background
Raymar: worked on Welcome page, header, icon bar, Spotify API
Evelyn: worked on Timer functionality and implementation

Tools

• HTML 5
• CSS 3
• JavaScript
• Git/GitHub
• Figma

Challenges

• Becoming team lead
• Making a project timeline
• Getting the hang of Figma and GitHub
• New languages to learn
• Working in a team enviornment
• Time management

What Was Learned

• Coding in a team project
• HTML/CSS/JavaScript
• Using Figma
• Navigating through GitHub
• Design vs Realistic Implications

Given More Time...

• Implement different background images onto the website
• Add in a variety of music genres onto the website

Team Introduction

• Ceiara Madrigal

• Anna Hock

About the Project

Studio Notes is a note-taking application that enables user to store their notes on their device. Users can organize notes which are stored on a database for each unique user. They can also create as many notes as they want. There is no specific order when notes are created. It will order out in a straight layout.

Team Lead:
Ceiara: set deadlines, provided resources, project management, problem solving, coding back-end & fron-end

Member:
Anna: coding back-end, working with in a team setting to come up with ideas for the application

Tools

• Flutter IDE - Dart
• Firebase - Firestore database and Authentication
• GitHub

Challenges

• Ceiara: Group orginally had a total of 5 members
• Anna: First time working on back-end and Android Studio/Flutter

What Was Learned

• How to use authentication sytem
• Leadership and communication skills
• Valueable knowledge about back-end
• Learning a new language/environment

Given More Time...

• See how our app can expand when multiple notes are added
• Create different authentication methods

Cover image by Studiogstock on Freepik

Team Introduction

• Brittany Flores

• Julia Chaidez
• Alison Ching
• Aisling Gonzalez

About the Project

sheCooks is an app that helps the user return n amount of recipes when user picks n amount of ingredients. We wanted to create a flexible search function and have detailed description of each recipe with main ingredients, steps, and time to cook.

Check out our Figma Design!
Figma Prototype

Team Lead:
Brittany: splash screen and full stack

Members:
Julia: homescreen
Alison: homescreen
Aisling: recipe list and view screen
All members worked on API caller and the recipe view screen

Tools

• Swift
• Xcode
• Figma
• GitHub
• Rapid API – Spoonacular
• Google Docs
• Discord

Challenges

• Understanding a new language
• Time management

What Was Learned

• Helpful Youtube tutorials for Swift
• Coding in Swift
• Team collaboration
• Navigating through GitHub
• Design vs Realistic Implications

Given More Time...

• Add other features
• Allow more customization

Cover image by Rawpixel.com on Freepik

Team Introduction

• Sneha Vivek

• Vanessa Cano
• Paige Moore
• Canh Trinh
• Mia Felipe

About the Project

Our team wanted to research and understand implementation of Artificial Intelligence via Neural Networks. Modeled loosely after the human brain in structure and algorithm, designed to recognize patterns, and comprised of node layers. Our team craeted 3 Multi Layer Perceptions (MLP) which printed the results for the training and test scores.

Tools

• Python
• VS Code

Challenges

• Scheduling meetings
• Meeting everyone's knowledge level
• Compiling our research in a succinct way
• Understanding coding Artificial Intelligence in Python
• The training data which was one letter by letter

What Was Learned

• Intro to neural networks
• Math behind neural networks
• Multilayer perception
• Creating MLPs

Given More Time...

• Implement a scanning tool to help upload notes or text files

Team Introduction

• Tiffany Truong

• Lindsay Kislingbury
• Mohraiel Matta
• Andrew Perez
• Katelyn Mijares

About the Project

Cinema is a website that provides the user a list of movies based on their chosen genre(s)/keyword. The user will get a list of options along with the release date, original language, run time, and overview.

Team Lead:
Tiffany: Assisted members with any problems that occured

Members:
Lindsey: Backend
Mohraiel: Frontend, Assisted with Backend & logo
Andrew: Frontend, Logo Design
Katelyn: Frontend

Tools

• Server - Node.js
• Framework - Express JS
• CSV- Parser Multer
• Search - Fuse.js
• HTML/CSS

Challenges

• Datasets we found were too big to work with
• Unfamiliar with new technologies such as EJS & Flexboxes
• User Inclusiveness: Colors/Fonts
• Frontend Design/Layout
• Getting data into a usable Javascript format, performing the search → sending that data to the next HTTP route
• New to the concept of Data Science

What Was Learned

• Better understanding of data science & how it works
• How to make documentation to share information with the rest of the team
• Gained insight in new technologies (EJS & Flexboxes)
• Collaboration & Teamwork

Given More Time...

• Advanced search for list of movies
• More genres - Not limited to the ones we have
• More detailed search

Team Introduction

• Bryan Gonzalez

• Erika Ledesma

• Meghan Nguyen

About the Project

Conceptually, DevOps was used in project through scrum project management and task delegations. Many are unaware of how much money can be saved instead of spent. WalletBuddy helps users keep tabs on their expenses, helping them stay on track with financial goals.

Co-Leads:
Bryan: managing meeting objectives and being resourceful
Erika: backend/frontend developer
Members:
Meghan: frontend framework, slides, and logo

Tools

• Node.js
• Kanban Boards - GitHub
• Spring Boot
• Bootstrap
• VSCode
• IntelliJ IDEA
• HTML/CSS
• JavaScript
• React
• MongoDB

Challenges

• Unfamiliarity with certain tools
• Unfamiliar with languages
• Changes in team size
• Limited knowledge of DevOps
• Time management
• Time-restrain
• Knowledge/skills gaps

What Was Learned

• Implementation through guidance from a tutorial and researching on Google
• Set goals and objective since early stages and learn more about project management
• Every challenge leadsto growth, so view issues as a way to learn more about DevOps
• Be more aware of time-restraints and try to address knowledge/skills gaps early on.

Given More Time...

• User authorization (log-in) feature
• Customization
• Payment method (for users who want to subscribe)
• Using cloud-based platforms (AWS)
• AWS and Docker

Cover image by storyset on Freepik

Team Introduction

• Alejandro Hernandez

• Min Jung
• Vivian Hoang
• Stella Sinlao

About the Project

Our goal was to learn about machine learning, particularly a method to solve simple regression problems. For this project, we created a linear regression model and train it with gradient descent to get the best possible prediction line.

We gathered a collection from 24 students of hours studied for an exam and their exam score. We suspect a linear relationship between these two variables.

Tools

• Python
• Pandas
• NumPy
• MatPlotLib
• Discord
• Zoom

Challenges

• Understanding concepts of the methods
• Connectivity issues on Zoom
• Limited meeting windows

What Was Learned

• Better understanding of Machine Learning
• Learned how to get gradient descent
• Understanding how models are used for predictions

Given More Time...

• Explore functions that automatically implement linear regression from Python libraries like Scikit Learn
• Study methods to optimize gradient descent
• Study and implement multiple linear regression models