The class is provided at no cost for students. We work closely with a number of industry partners who help us cover the costs of the program.

Depending on the course you are enrolled in, our instructors include engineering professionals from major technology companies, start-ups, and academia, such as Google, Meta, or Stanford University. We also carefully select and mentor a group of high-performing student leaders (Tech Fellows) who help facilitate each class of students at partner universities. We have created and tested extensive learning materials including pre-recorded video lectures and online documentation to help with the homework. In addition, professional experts are available to answer student questions online about lecture materials as well as the homework.

Regardless of which class you take or which university you attend, CodePath provides the same high quality curriculum and course experience to arm you with industry knowledge, technical excellence, and a portfolio to demonstrate your work.

CodePath is committed to teaching foundational CS principles like problem decomposition, critical thinking, and systemic design. However, we’re also evolved our curriculum to include AI-assisted coding, responsible AI use, and multidisciplinary applications to better prepare students for an AI-powered future.

No. We emphasize learning how AI works and how to use it effectively, not just relying on AI-generated code. Students will still gain strong CS fundamentals, but they’ll also learn how to integrate AI into real-world engineering workflows.

AI is automating routine coding tasks, but it won’t replace engineers—it will change the expectations of engineers. Those who learn to leverage AI will be more valuable, while those who ignore it risk falling behind. Our goal is to ensure CodePath graduates are on the leading edge.

Employers are increasingly looking for engineers who can think critically about AI, not just use it. Our AI-Native approach prepares students to be adaptable, making them more competitive and valuable in an AI-driven workforce.

You should set aside 2-10 hours per week for each CodePath class. This includes 1 session per week (2 hours) and homework (depending on the course track). Classes last for 10 weeks. For colleges offering for-credit courses, it can last up to 14 weeks.

Yes, we typically offer multiple remote courses each year:

• Applied AI Engineering: Master software engineering in an AI-native world. Rather than treating AI as a separate topic, the program embeds it directly into programming practice. Students strengthen their understanding of data structures, algorithms, and object-oriented programming while learning to use AI tools as collaborators for debugging, scaffolding, and refinement, always with human oversight and critical evaluation.
• Web Development: Dive into full-stack development with the Web Development pathway. Learn to design and create your own sites inspired by popular websites you already know and love. You will build fast, responsive websites with a personalized user experience from account signup to profile customization to content creation.
• Cybersecurity: Originally designed in partnership with Meta, this course teaches students how to think like a hacker and exploit vulnerabilities, while also exploring how to build offensive capabilities into applications.
• Technical Interview Prep: Ace technical interviewing and get a preview of real-world software topics in the industry.
• Tech Fellow Training: Train to be an instructor of one of our CodePath courses at your campus.

We're always adding new courses and updating our curriculum based on student demand! You can sign up for our mailing list to stay up to date on our new offerings.

Yes. You will need a GitHub account to have access to the CodePath courses, and submit the assignments and labs throughout the course. If you don't have one yet, you can create an account here.

Please see a brief description of the application process. During the process, you will receive detailed emails to help you with each step:

Start application form - Start an application by logging into GitHub and selecting a particular cohort. For Connected Classroom (non-credit remote) courses, you may start your application here by logging through your email.

Complete application form - Fill out and complete the application. Once the application is submitted, you will receive a confirmation email with next steps (configured per cohort).

Submit pre-work - You will automatically receive a customized email outlining the next steps for pre-work, including key dates and deadlines. Only applications submitted with pre-work will be reviewed and scored for admissions.

Confirm spot and agree to terms to get admitted - Our team will finalize admissions by reviewing each application. If selected, you will receive an email requesting to confirm admission. Please note that if the admission is not confirmed, you can potentially lose your spot and be switched to rejected or waitlist status, especially if the class is full due to a large number of applicants.

It is very important that you add CodePath to your email address contact list, and check your spam folder so that you do not miss any emails from us.

Our courses are generally designed for students in computing-related majors who are 18 or older and attending a US college or university. Some of our courses will also have prerequisites, such as familiarity with object-oriented programming or data structures and algorithms. You'll find the requirements for each course detailed when you begin your application in our application portal

All CodePath courses are designed to quickly give you technical skills that will enhance your college education, build a portfolio to show future employers, and add valuable skills to your resume. When you successfully complete our courses, you will receive a certificate from CodePath, and you also gain access to CodePath’s career services, 1,100+ industry mentors, and our 10,000 students and alumni network. CodePath's courses and services are here to help you bridge the gap between your computer science education, getting a job in the tech industry, or forming your own tech start-up.