Engineering track

AI Engineering & Data Science.

Three intensive months. Real projects from week one. A capstone judged by people who hire in the field. Free.

The 3-month journey

Foundations to capstone.

Month1

Foundations of AI & Machine Learning

  • Intermediate Python
  • Probability & statistics
  • Algorithms
  • Data analysis & time series
  • Machine learning
Month2

Deep Learning & Applied AI

  • Deep learning & neural network architectures
  • NLP & large language models
  • Computer vision
  • AI as a Service
Month3

Practical AI + Capstone

  • Advanced Python & numerical optimization
  • Big data — Hadoop & Spark
  • An AI project of your own, built end to end
  • Presentation and evaluation by industry experts

How the cohort runs

Weekly rhythm.

Lectures and labs

Taught by industry practitioners — the people building with these tools in production.

One project thread

A project that runs the length of the cohort, so every week's material lands on something you're actually building.

Weekly reviews

Progress reviewed every week. Feedback early, when it's cheap.

Completion

Documented completion and a skills assessment.

Full-time attendance, project milestones met, capstone presented and evaluated by industry experts, and a skills assessment — that's what completion means here.

Prerequisites

Before you apply.

Educational background

Degree: Bachelor's in Computer Science, Computer Engineering, or a related field.

Status: recent graduates (within two years) or final-year students completing before the program starts.

Foundational knowledge

Programming: one language common in AI — Python, Java, C++, or R.

Mathematics: calculus, linear algebra, probability, statistics.

Data structures & algorithms: arrays, lists, trees, graphs; sorting, searching, dynamic programming.

Technical skills

Basic machine learning: regression, classification, clustering, neural networks.

Software development: Git and modern IDEs.

And the rest

Analytical problem-solving. English proficiency. A genuine interest in AI and the willingness to study full-time for three months.

Recommended: prior AI projects, internships, research, or certifications.

Where our graduates go

Three paths out of the Institute

01

Global employment

Graduates join global companies through our employer network and university career centers, with the portfolio and references to land the role.

02

Advanced research

A path into research with our university partners and industry labs, for graduates who want to push the field forward.

03

Your own startup

Founders plug into the Openner ecosystem — and the strongest ideas find their way to Openner's investors.