Hackbright Alumnae Showcase: Fina Silva-Santisteban, Jenica Huang, and Jennifer Kim
Fina Silva-Santisteban
Fina is a Data Analyst, Computer Science undergrad from Germany, and a new mom. In previous roles, she has worked on providing data insights for different stakeholders and used SQL and Python to slice and dice existing datasets. Building web applications was always a passion of hers, she taught herself how to use Node.js, Express.js, and D3.js to build web apps for data visualization. She applied that knowledge in multiple side projects at work to present the insights that she had discovered in an engaging way. During her extended maternity leave, Fina had the opportunity to reevaluate her career and she realized that in all of her previous roles it was coding that she enjoyed the most. She's looking forward to growing as an engineer.
LinkedIn: https://www.linkedin.com/in/fina-silva-santisteban/
Hackbright Project: Knit It
‘Knit It’ is a single-page web app that allows a user to search and browse knitting patterns available on ravelry.com. Users can register and log in, and if a user is logged in they can add, remove and browse patterns from their favorites list. The app is organized following an MVC pattern. To get knitting patterns, React components use real-time ajax calls to my server which calls the Ravelry API. Controller classes extract the information needed from the API response and compose a meaningful result object which will then get returned to the frontend. The only information stored in my DB is related to the user and their favorites list. This way I can ensure that my app always serves the most up-to-date knitting pattern information.
Technology Stack:
Python, Flask, JavaScript, React.js, jQuery, Bootstrap, PostgreSQL, HTML, CSS
APIs Used:
Ravelry API
https://github.com/finasilvasantiste/hackbright__knit_it
About Fina Silva-Santisteban
C.S. or Related Experience Prior to Hackbright:
Fina studied Computer Science in Germany, where she learned Java, relational databases, object-oriented programming back in 2008. In previous roles as a Data Analyst, she used SQL and Python extensively for analytics reports. She picked up Node.js, Express.js, and D3.js on her own to build web apps for data visualization.
Jenica Huang
Jenica first picked up coding as a hobby when she took 6 months off to travel the world on an extended honeymoon. After taking her first intro to CS course, she decided to pursue this hobby full-time and chose to attend Hackbright Academy after returning from her travels. Before discovering her love for computer science, she was a CPA with five years of combined experience in assurance, internal controls, technical accounting, and SEC reporting. She is originally from Toronto and holds a Bachelor in Commerce from McGill University in Montreal, Canada. Jenica is passionate about learning and finding creative solutions to solve interesting problems. She is currently looking for a developer role and excited to continue growing her skillset.
LinkedIn: https://www.linkedin.com/in/jenica-huang/
Hackbright Project: PinTrip
PinTrip is a mashup of Pinterest and Flickr to help users find photos of interesting places to see on their next trip. Users can create or remove their own personalized 'trip board' for each city they are interested in visiting. After a board has been created, users can search for photos with geotags in their chosen city and add or remove photos to and from the trip board. Once photos have been added, users can view a map of their trip which pins all of the saved photo locations.
Technology Stack:
Python, JavaScript, HTML, CSS, SQL, Flask, jQuery, AJAX, Jinja, Bootstrap
APIs Used:
Flickr API, Mapbox API
https://github.com/jenihuang/HB_Project_PinTrip
http://52.12.167.44/
About Jenica Huang
Jennifer Kim
Jen graduated from Amherst College in 2017 with a B.A. in sociology and a passion for education. After graduation, she completed a fellowship program for Reader to Reader, Inc. There, she recruited, interviewed, trained and mentored 200+ college students. Her interest in programming peaked when she felt the urge to change the layout of Reader to Reader’s website to improve the site's user experience. She realized that she needed to learn the foundations of computer science to successfully reconfigure the website. Shortly after, she committed to a career change and enrolled at Hackbright Academy. Now, Jen aspires to become a full-stack web developer at a company where she can pursue her passion for programming and possibly, education.
LinkedIn: https://www.linkedin.com/in/jennifer-yeon-kim/
Hackbright Project: Vibez
Vibez is a web application that utilizes Spotify's API to generate playlists based on a user's choice of genre and minimum and maximum range of danceability levels (0 - 1). Once a playlist has been generated, Vibez gathers and stores the playlist's history in a PostgreSQL database along with information for the three audio features. Once a Spotify API request is made, Vibez integrates the JSON into the frontend using the Amplitude.js library to showcase its lists of songs and its accompanying shuffle, skip, adjustable volume, scroll, and other convenient functions. In order to display a page of stored playlists, Vibez assimilates interactive, complex visuals rendered by code that is extracted and refactored from the D3.js library.
Technology Stack:
Javascript (AJAX, JSON), jQuery, D3.js, Amplitude.js, Python, Flask, Jinja, SQLAlchemy, PostgreSQL, HTML, CSS, Bootstrap
APIs Used:
Spotify
https://github.com/surferJen/vibez
About Jennifer Kim
C.S. or Related Experience Prior to Hackbright:
Before Hackbright, Jen worked for Uber as an EATS Enterprise specialist and was later promoted to a special projects analyst role. At Uber, she acquired knowledge in advanced Excel, Salesforce software, Data Loader, Jarvis, and Uber internal systems. In order to develop her programming skills, she started to practice coding on Code Academy, learn the fundamentals of Javascript on Plural Sights and complete bootcamp preparatory courses through Fullstack Academy and Ada Developers Academy.
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