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 two other students at your skill level.
(Beginner-track attendees: we'll match you with a former intern from a tech company who has time to provide you with more support.)
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?)
It's like a real-world internship at a leading tech company, but 100% online.
What do recruiters look for when you meet them? How does Microsoft deploy machine learning modules? What does a day-in-the-life look like for a technical artist?
CodeDay Labs has daily opportunities to learn from leaders and build a professional network.
Our students have daily opportunities to do practice interviews and get resume feedback from tech hiring managers and recruiters.
A guided experience which is best for people with some CS knowledge, but who don't have prior experience working on complex projects.
This is probably the right track for you if you're a high school student who's taken AP CS A or equivalent course, or a college student with 101-level experience in CS or Engineering.
You'll work with an older student, a current/former tech intern, who will guide you through your first experience building something with real-world implications.
($250 fee if accepted; many scholarships available.)Apply
This track is the most similar to a traditional in-person internship, for those students who have higher-level CS knowledge or significant experience building projects.
This is the right track for you if you're a college student with experience beyond the 101/102-level CS or Engineering classes, or a student who has built projects on your own time.
You'll be matched with a mentor from the technology industry, like at most traditional in-person internships, and will build a polished app/feature.
(No fee; not a paid internship.)Apply
I 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-Track
Being 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-Track
I 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-Track
I 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-Track
My 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-Track
Mentor: Saharsh Yeruva, RM at CodeDay
A chrome extension that looks at all the images on a webpage. If there is an image that does not have an alt tag, use ml to generate one so that screen-readers can actually recognize it.
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.
Mentor: Yang Xu, Engineer at LexisNexis Risk Solution
We will design a system to fetch data from REST api and store data in a database. The system is comprehensive with various functionalities such as input/output, caching, logging, etc. The system has to be highly scalable so that it could handle big amount of data.
This year's talk schedule hasn't been released yet, so have a look at last year's lineup:
Jul 8, 2020, 8:00 PM
Building a NLP/machine learning model in 5 steps
Jul 8, 2020, 9:30 PM
One Approach To Prototype Software Ideas
Jul 9, 2020, 6:00 PM
IT Careers in Public Sector Higher Education
Jul 9, 2020, 8:00 PM
Colin Vandervort - Indie Game Technical Audio Designer
Jul 10, 2020, 9:00 PM
My experience with interviewing as an enterprise software engineer
Jul 10, 2020, 11:00 PM
College Admissions, College Life, and First Jobs
Jul 13, 2020, 8:00 PM
College New Grad Hiring Demystified - Tips From a Recruiter (Erwin Chan)
Jul 13, 2020, 11:00 PM
Using AI to Craft Conversational Experiences
Jul 14, 2020, 6:00 PM
17 Tips for Working in Tech
Jul 14, 2020, 7:00 PM
Steven Stadnicki - 20 Years of Game Dev Revealed!
Jul 15, 2020, 5:00 PM
Big Data Journey and solving real word problems
Jul 15, 2020, 7:00 PM
Machine Learning and Algorithm vs Data
Jul 16, 2020, 6:30 PM
Careers in Product, Dev, and QA Panel
Jul 17, 2020, 3:00 PM
Career Progression for New Grads with Zero Experience
Jul 20, 2020, 7:30 PM
College New Grad Hiring Demystified - Part II, Your Questions Answered
Jul 20, 2020, 9:00 PM
The Road of Robotics Research
Jul 21, 2020, 8:00 PM
Prehistoric computing 1960s-1970s
Jul 22, 2020, 4:00 PM
Venture Financing in a COVID World
Jul 22, 2020, 10:00 PM
Trust through Verification
Jul 23, 2020, 7:00 PM
Professor Blake Hannaford - Robotics Expert from UW Electrical and Computer Engineering
Jul 23, 2020, 8:30 PM
Docker and container based solutions
Jul 27, 2020, 3:30 PM
The Invisible Code - Data Engineering in 2020
Jul 27, 2020, 6:00 PM
Web Scraping using C# and Python on ScrapingHub
Jul 27, 2020, 9:00 PM
How We Matched You to Your CodeLabs Team (A Journey From From Elastic Search to Marriage Algorithms)
Jul 28, 2020, 7:00 PM
You Should Make Things
Jul 28, 2020, 9:30 PM
The day to day life of a Data Scientist
Jul 29, 2020, 7:00 PM
Find your cardboard box.
Jul 29, 2020, 9:30 PM
Jul 30, 2020, 9:00 PM
Game Engine Architecture
Jul 31, 2020, 4:30 PM
Continous Integration and Continous Delivery for Machine Learning Models
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