Applied AI & Data Science — A.E.C. Program Guide
Collège Unica's 5-session, 28-course attestation (A.E.C.). 530 hands-on classes, 1620 hours of training — from Python foundations to a defended production capstone.
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At a glance
5
Sessions
28
Courses
530
Classes
1620
Total hours
Credential
Attestation d'études collégiales (A.E.C.) in Applied Artificial Intelligence & Data Science — an online learning path offered by Collège Unica, distinct from the on-site LEA.ED program. Fully self-paced with a guided AI tutor; you can start anytime. See https://unica.college for program details.
The five sessions
Each session builds on the last, moving from foundations to a defended capstone.
Foundations of AI & Data Science
Programming, mathematics, algorithms, statistics, and ethics — the fundamentals every applied AI practitioner needs before touching a model.
5
Courses
100
Classes
300h
Total hours
- 1.1Mathematics applied to computing I — 75h · 25 classes
- 1.2Computer French — 45h · 15 classes
- 1.3Introduction to the job function — 45h · 15 classes
- 1.4Algorithms and programming — 90h · 30 classes
- 1.5Setting up an AI ecosystem — 45h · 15 classes
Data Engineering & Machine Learning
Build the data engineering and programming foundation for machine learning: applied mathematics, structured Python, and exploratory data analysis — alongside the professional French communication skills you'll use across every later session.
6
Courses
110
Classes
330h
Total hours
- 2.1Mathematics applied to computing II — 75h · 25 classes
- 2.2Advanced computer French — 45h · 15 classes
- 2.3French for the office and entrepreneurship — 45h · 15 classes
- 2.4Exploratory data analysis — 60h · 20 classes
- 2.5Structured programming (Python) — 75h · 25 classes
- 2.6Technical and intercultural communication — 30h · 10 classes
Deep Learning & Applied Machine Learning
Master the core supervised and reinforcement learning algorithms, then go deeper into neural networks and deep learning — the model-building toolkit that every modern AI system builds on.
6
Courses
115
Classes
345h
Total hours
- 3.2Programming with R for data analysis and visualization — 60h · 20 classes
- 3.3Data transformation and manipulation — 60h · 20 classes
- 3.4Supervised learning algorithms — 60h · 20 classes
- 3.5Reinforcement learning algorithms — 45h · 15 classes
- 4.4Deep learning algorithms — 90h · 30 classes
- 3.6Design thinking and entrepreneurship — 30h · 10 classes
Applied AI Systems & MLOps
Take models from notebook to production: cloud infrastructure, MLOps lifecycles, edge deployment, security, and AI product thinking.
6
Courses
95
Classes
285h
Total hours
- 4.1Script programming and task automation — 60h · 20 classes
- 4.2Unsupervised learning algorithms — 60h · 20 classes
- 4.3Cloud computing — 45h · 15 classes
- 3.1Data collection and storage — 60h · 20 classes
- 4.5Develop your leadership skills — 30h · 10 classes
- 4.6Entrepreneurship and innovation — 30h · 10 classes
Capstone Studio & Industry Deployment
A two-part capstone, an industry practicum, and a public demo day. Graduate with a defended portfolio and real production experience.
5
Courses
110
Classes
330h
Total hours
- 5.1Preparing the AI solution for production launch — 45h · 15 classes
- 5.2Web analytics and marketing database analysis — 45h · 15 classes
- 5.3Data mining techniques and analysis of textual and social network data — 45h · 15 classes
- 5.4Search engines and recommendation systems — 45h · 15 classes
- 5.5Supervised project/internship — 150h · 50 classes
Where this leads
Roles grounded in the program's actual curriculum — drawn from National Association of Career Colleges program data for related applied-AI career tracks.
Data/Business Analyst
Translate datasets into decisions — exploring, cleaning and visualizing evidence that drives business choices.
Built from: 2.4, 3.3, 3.2
Web Analytics/Marketing Specialist
Measure what audiences do online and tie behavior to campaigns using analytics and marketing-database tooling.
Built from: 5.2, 3.2
SEO Consultant
Improve search visibility by combining textual analysis, ranking logic and recommendation-system fundamentals.
Built from: 5.4, 5.3
Web Strategist
Architect the web presence — recommendation systems, analytics and production-grade data pipelines working together.
Built from: 5.4, 5.2, 4.3
AI Integration Manager
Stand up the AI ecosystem, automate the plumbing, and ship models to production on cloud infrastructure.
Built from: 1.5, 4.3, 5.1
Digital Marketing Strategist
Plan and run digital campaigns powered by analytics, social-data mining and recommendation logic.
Built from: 5.2, 5.3, 3.6
Marketing Consultant
Advise clients on data-informed marketing — from analytics to design-thinking-led venture framing.
Built from: 5.2, 5.3, 3.6
Project Manager
Coordinate AI projects end to end — scope, lead and deliver a supervised capstone or internship engagement.
Built from: 1.3, 4.5, 5.5
E-commerce Director
Lead online commerce ventures using recommendation systems, analytics and innovation strategy.
Built from: 5.4, 4.6, 5.2
Sales and Marketing Manager
Direct sales and marketing teams with data-driven campaigns, leadership practice and entrepreneurial framing.
Built from: 4.6, 4.5, 5.2
How the program works
Self-paced, start anytime
No fixed cohort calendar. Every course pairs a guided AI tutor with hands-on classes — learn on your schedule.
Learn by doing
Each class is time-boxed into Theory, Practical, and Personal Work with concrete tools and take-home micro-tasks.
Agentic AI & GenAI for business
The curriculum is oriented around LLM/GenAI APIs, tool-calling, multi-step agents, RAG, and real business problem solving.
Defended capstone
Session 5 is a full agentic-AI business-solution build-and-defend project arc — scope, build, harden, and present to a panel.
Try before you enroll
The first class of every course is free, including its AI tutor and quiz. Redeem a referral code to unlock the first two.
Ready to start?
Begin your application, or explore the full curriculum course by course.