Break Through Tech AI
Here’s how it works:
Inside the Program
MACHINE LEARNING FOUNDATIONS
Are you interested in building machine learning workflows to solve real-world problems? In this 8-week, skills-based summer course, you’ll work with industry-relevant tools to analyze real-world data sets, identifying patterns and relationships as you create robust data science projects. Once you master the data science basics, you’ll move on to using several common machine learning tools to approach real-world business problems, build your own ML models, train, and implement these in the most effective way.
During this part of the program (June-August 2023), you can expect to spend about 10 hours per week on asynchronous, online classes and 3 hours per week on synchronous lab sessions with other students.
What you’ll do:
- Articulate the complete data science life cycle end-to-end
- Build a dataset that is suitable for ML applications and understanding your data through exploratory analysis
- Learn how to use industry-relevant ML tools and libraries
- Learn core ML algorithms and develop intuition on trade-offs between different algorithmic choices
- Select ML model evaluation metrics, hyper-parameters for testing, and run model selection to choose the best model amongst candidates
- Learn more advanced ML models and navigate design decisions and constraints to perform agile model development
- Investigate how deep learning can be used in ML and train and adapt neural networks to take advantage of different types of data
- Understand the responsibility of ML engineers to improve the fairness and accountability of ML models
AI STUDIO AND PORTFOLIO DEVELOPMENT
Throughout the academic year, you’ll be invited to join the AI Studio where you’ll work in teams to tackle business challenges from leading companies. Our industry partners include a mix of leading companies and organizations working in different industries at the forefront of ML and AI, including American Express, Capital One, Google, JP Morgan Chase, Pfizer, and more.
Based on your unique skills and interests, we’ll match you with a relevant project where you will work with large-scale, real-world datasets to train, test, and evaluate machine learning models to make predictions. Guided by academic and industry advisors, you’ll present your solutions to people experts in the field. All projects will result in technical artifacts that you can add to your portfolio that will serve as a “credential” to show future employers what you can do.
During this part of the program (August 2023-April 2024), you can expect to spend about 5 hours per week developing your project. The majority of the work can be completed virtually, with the exception of Maker Days, which occur in person and on-campus at Cornell Tech.
What you’ll do:
- Apply the ML skills that you learned in your summer ML Engineering course
- Identify and dissect real-world business problems with real-world data and evaluate the ways that they can be addressed using ML and AI
- Collaborate in small teams to develop, test, and iterate on solutions to business problems using ML and AI
- Synthesize and convincingly present your solutions to industry experts
- Add artifacts to your portfolio demonstrating your capabilities and experience
MENTORSHIP AND CAREER COACHING
Getting your first job in AI and machine learning takes more than raw technical capability. To support your professional goals, you will work closely with a professional mentor in a small-group and over 18 months to engage in skill-building simulations, practice, and receive personalized feedback. Your mentor will be by your side as you cultivate your authentic leadership and social capital and ensure that you are on track to land a summer internship and full-time employment.
Additionally, you will receive career coaching and placement support from Break Through Tech to prepare your portfolio, apply for internships, and practice for your interviews.
During this part of the program (August 2023-December 2024), you can expect to spend about 1 hour per week completing online skill-building workshops or synchronous small-group meetings with your mentor each month.
What you’ll do:
- Learn about technical roles within data science, ML, and AI domains and their requirements
- Develop job search methodologies to identify, evaluate, and apply for summer internships or full-time roles
- Create and revise your professional portfolio, including your resume, LinkedIn profile, GitHub profile, and more
- Prepare and practice for coding and ML interviews
- Grow your professional network within the AI/ML field
- Prepare to get the most out of your internship experience
Who Should Apply
- In addition to all female-identifying and non-binary students, students in other underrepresented groups (Black, African American, Hispanic/Latinx, Indigenous, low-income, non-traditional, and first-generation college students) are welcome to apply.
- Applicants should be planning to major in CS, mathematics, engineering, or a related STEM discipline.
- Applicants should have an interest in learning about artificial intelligence, machine learning, or data analytics
- Applicants should have some programming experience, including familiarity with introductory Python
The application will open in early January. This page will be updated with key dates and links as information is available.
Artificial intelligence and machine learning are already changing our world. It’s up to us to make sure that change is for the better.”
Help train tomorrow’s engineers
We’re actively looking for corporate, public-sector, and nonprofit partners to provide our students with real-world challenges that they can work on in our Studio. If you have a business challenge that can be solved with AI that you’d like fresh ideas on, we’d love to hear about it. We’re committed to building a better, safer, and more inclusive future of tech, and we believe that starts by having more women coders on the frontlines. We’d love your support in making that happen.
Break Through Tech’s AI Program is funded by Melinda French Gates’ company Pivotal Ventures, Ken Griffin, Citadel and Citadel Securities, the Hopper-Dean Foundation and New Venture Fund.