CodeDay Labs is the 100% online tech internship for everyone.
VolunteerStudents from partner colleges:
Dates may vary. Use your invitation link to apply.
Dates may vary. Use your invitation link to apply.
Dream of working at a top tech company? Join us!
Work with your mentor & other students.
Tell us what you love in technology, and where you want your career to take you. We'll match you with the perfect industry mentor and up to three other students.
Create or contribute to real-world, open-source projects.
Learn to ship real software that helps real people using the latest industry tools. (Ever wondered what “Kubernetes” is? Or how to set up a GraphQL backend in Typescript?)
Daily tech talks, career panels, and more.
What do recruiters look for when you meet them? How does Microsoft deploy machine learning modules? How do real engineers make progress on a difficult problem?
CodeDay Labs has daily opportunities to learn from leaders and build a professional network.
Get ready to land your dream job or internship next year.
Learn the skills you need to succeed in technical interviews and strengthen your resume by shipping code in the OSS projects tech companies really use.
Contribute to open-source software used by millions of people.
Multiple tracks. What's your experience level?
Init
A great first-step for students who have not coded beyond college assignments.
This is the right track for you if you're a college student who has completed some CS classes but hasn't built anything independently and without step-by-step guidance.
You'll be matched with a mentor from the technology industry, like at most traditional internships, and will make a tiny first contribution to OSS.
(By invitation only.)
Intermediate Track
More guided projects for college freshmen/sophomores/juniors to help develop engineering mindset.
This is the right track for you if you're a college student who has completed 101/102-level CS classes but not much more (or a high school student who's participated in hackathons).
You'll be matched with a mentor from the technology industry, like at most traditional internships, and will build a polished app/feature.
(No fee. Not a paid internship.)
Advanced Track
For college juniors/seniors with more CS knowledge, but without the time for a full-time internship.
This is the right track for you if you're a college student with experience beyond the 101/102-level CS classes, or a student who has built projects on your own time (e.g. hackathons).
You'll be matched with a mentor from the technology industry, like at most traditional internships, and will build a polished app/feature.
(No fee. Not a paid internship.)
If you get stuck, our TAs are always available to help!
Lola Egherman
Ludo
Lynne
Faisal
We've helped thousands of students get their start in technology since 2009.
As an international student in a programming major, you guys totally helped me to start my wonderful career path! In a three years degree, I had you guys as my first experience, Meta as my second, and Microsoft as my third, and this last one gave me a full time return offer.
Luiza Cartaxo, Labs Advanced-TrackI loved being able to work as a team and gain real world experience about coding but at the same time also having the opportunity to learn something new.
Kelly Dong, Labs Advanced-TrackBeing a Venezuelan immigrant, Labs was the first time that I got true exposure to a community of tech people that I could rely on. Fast forward a couple of years and now I'm three and a half months away from graduating college and have a job as a SWE at the Microsoft HQ right after I graduate.
Daniel Lobaton, Labs Beginner-TrackI began my CodeDay Labs internship with no background in using React Native, but came out of this internship knowing the ins and outs of React Native thanks to my team and my mentor, Eric. I highly recommend CodeDay Labs as a chance to apply your knowledge to real-world applications
Vivian Wang, Labs Beginner-TrackI really enjoyed learning how to use new technology such as Angular, Node, Sequelize, and Joi. Working with my teammates and interacting with each other was one of my favorite parts of this internship. Just helping each other out, working, learning, and growing together as developers was really great. Also the mentor was very helpful.
Alain Nshimirimana, Labs Advanced-TrackMy experience as a CodeDay Labs intern certainly exceeded my expectations. My favorite part about being an intern was getting to learn and work with Python Django. I found working with Django to be difficult yet also fun. At the beginning of the internship, because I only had experience with ReactJS, I thought I would only be working on the frontend component of the app which we built. However, I ended up only working with ReactJS (i.e. the frontend) for about a week before I became responsible for the backend. I'm really glad I got this exposure because I found that I enjoy working with backend-related stuff.
Amy Ghotra, Labs Advanced-TrackShowcase your talent for potential employers.
LiDAR Data VisualizationAdvanced Track
Mentor: Omar Shehata, Graphics engineer at Cesium
Create a web app to visualize LiDAR data from self driving cars.
LiDAR is a way of obtaining an accurate 3D representation of a scene, often used in self driving cars to detect their surroundings. Lyft recently released a large dataset of sensor readings from their self driving car work: https://level5.lyft.com/dataset/
Most analysis done on data like this is done without visualizing all the data together, because it's in different formats/too large to efficiently visualize in real time. This project would involve taking this data, converting it to a standard format that Cesium's pipeline can ingest (likely using Python since it has many of the helper libraries you'll need), and then building an application to visualize it in 3D using Cesium's JavaScript library.
This would not only help people get more insight out of this particular dataset, but would provide a framework for anyone doing self driving car analysis to see their result and share their research. For inspiration you can see how people are analyzing this data in this Kaggle competition:
https://www.kaggle.com/c/3d-object-detection-for-autonomous-vehicles/discussion/109415
LiDAR is a way of obtaining an accurate 3D representation of a scene, often used in self driving cars to detect their surroundings. Lyft recently released a large dataset of sensor readings from their self driving car work: https://level5.lyft.com/dataset/
Most analysis done on data like this is done without visualizing all the data together, because it's in different formats/too large to efficiently visualize in real time. This project would involve taking this data, converting it to a standard format that Cesium's pipeline can ingest (likely using Python since it has many of the helper libraries you'll need), and then building an application to visualize it in 3D using Cesium's JavaScript library.
This would not only help people get more insight out of this particular dataset, but would provide a framework for anyone doing self driving car analysis to see their result and share their research. For inspiration you can see how people are analyzing this data in this Kaggle competition:
https://www.kaggle.com/c/3d-object-detection-for-autonomous-vehicles/discussion/109415
AmbientflixAdvanced Track
Mentor: Ed Bukoski, Engineer at Netflix
Create movie and TV show recommendations based on signals from your ambient environment. Imagine visiting Netflix and seeing a recommendation row based on your local weather, current geographical location, local news, or the past hour of your personal Twitter feed!
We will divide up into two teams. One team will source data from weather services, Twitter API, news feeds, or any other source that has data from the local environment. The second team will use these as input to query movie data from themoviedb.org and form a list of movie and TV show recommendations (bonus for links to streaming services where this content is hosted). We will figure out the final presentation format as we go, it could be a command line, REST (JSON) API, or a web site.
We will divide up into two teams. One team will source data from weather services, Twitter API, news feeds, or any other source that has data from the local environment. The second team will use these as input to query movie data from themoviedb.org and form a list of movie and TV show recommendations (bonus for links to streaming services where this content is hosted). We will figure out the final presentation format as we go, it could be a command line, REST (JSON) API, or a web site.
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