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Artificial Intelligence and Data Science

Combined AI + data curriculum — hireability still depends on SQL, software, and evaluation discipline.

Where this leads

The confusion, addressed honestly

AIDS branding makes students think the hybrid title itself is differentiation. Hiring still asks: can you write SQL, ship a small service or notebook pipeline, and evaluate a model or analysis without fooling yourself? "Built an AI project" without data quality notes, baselines, or failure cases is noise. Lean into either analytics engineering or applied ML with one sharp artifact — not five shallow demos. The degree opens the conversation; evidence finishes it.

Role paths

AI Engineer

Builds AI features — prompts, retrieval, evaluation, and safe product integration.

Analyst Consultant

Structured problem-solving for clients — research, models, and recommendations.

Analytics Engineer

Builds trusted analytics tables and metrics layers for the business.

Associate Sales Engineer

Bridges product and buyers — demos, technical Q&A, and solution mapping.

Associate Scrum Master

Supports agile ceremonies, blockers, and delivery rhythm for engineering teams.

Computer Vision Engineer

Builds systems that understand images/video for products or industrial use.

Content Engineer

Builds structured learning or knowledge content for technical audiences.

Data Analyst

Turns raw data into dashboards, insights, and decisions stakeholders can use.

Data Engineer

Builds reliable pipelines that move and transform data for analytics and ML.

Data Scientist

Frames problems, builds models, and communicates uncertainty to stakeholders.

Graduate Engineer Trainee

Campus-hire rotational or team-assigned role for fresh graduates learning production systems.

Growth Engineer

Ships product experiments and instrumentation that move growth metrics.

Junior Database Administrator

Helps keep databases available, backed up, and reasonably performant.

Machine Learning Engineer

Productionizes models — training pipelines, evaluation, and serving.

NLP Engineer

Works on text/speech understanding and generation systems.

Product Analyst

Measures product funnels, experiments, and feature impact with data.

Project Coordinator

Tracks timelines, risks, and dependencies so engineering delivery stays visible.

Prompt Engineer

Designs prompts, evals, and workflows that make LLM features reliable.

Research Intern

Supports experiments, literature, and prototypes in academic or industry labs.

Robotics Engineer

Builds robots spanning mechanics, electronics, and autonomy software.

Technical Recruiter Associate

Sources and screens engineering talent using technical judgment and outreach.

Map your own path

We'll pre-fill your starting point as a Artificial Intelligence and Data Science student.