'I was taking graduate level machine learning and reinforcement learning as a junior in college, and Sam saved me! He was able to teach me a semester's worth of material in under a week, and help me really understand it, way better than my professor. We went over the different learning algorithms at a theoretical level, and then he guided me on implementing them from scratch, and gave me a crash course in Pytorch too, because debugging code was part of my exam. He used a lot of different graphing techniques too, to really get into the small details of all models. Couldn't recommend him highly enough!' -Solly
As the landscape of computer science education continues to evolve, many find themselves in need of learning something about the field. Our tutors have designed three specialized courses that have benefited both those interested in exploring computer science with no background and those who want to brush up on their skillset and further develop an area of expertise.
Check out our specialized courses, unique to Priority-Q, that have helped many secure internships, software engineering jobs, and research positions.
This course is designed to introduce those without a technical background to the realm of AI and machine learning (ML).
Suitable for high school students who want to build a portfolio of research and development for college admissions!
A supervised project can be included at the request of the student.
This course is geared at students seeking to advance their algorithmic programming skills prior to job interviews.
This course covers the advanced mathematics and programming techniques of algorithmic feature engineering needed for internships and jobs.
Focuses on applications in computer vision, natural language processing, machine learning and reinforcement learning.
We also offer this as an intensive preparatory course at an introductory level for those who currently hold a non-CS degree and are wishing to complete a CS masters degree.
This is a comprehensive course starts off by covering the Python, Linear Algebra and Multivariable pre reqs needed to succeed in Comp Neuro.
Content focuses on Modelling, Machine Learning, Dynamical Systems, Stochastic Processing.
Course concludes with a supervised project by a doctoral candidate.