Teaching & Academic Team
Meet the AI2 team and explore the subject areas behind our programmes.
Teaching & academic team
Practitioners who teach what they build
AI2’s teaching team brings together engineers, data scientists and researchers who work on real industrial and research problems. Courses are built around projects, case studies and jury defences, so that students learn the methods and tools actually used in companies: machine learning, generative AI, data engineering, cloud, cybersecurity and connected systems.
- Practitioner-led: instructors active in industry or applied research.
- Small cohorts and individual academic guidance for each student.
- Applied assessment: competency-block defences, professional projects and company placements.
- Academic direction by Yacine Aslimi, founder and president, keynote speaker on Industry 5.0 skills.
Teach at AI2
AI2 regularly recruits instructors for its Bachelor and Master programmes in data science and AI. Send your CV and areas of expertise to the academic team.
Meet the teaching team
Professor
Abdelhak Touiti, PhD
Engineer in embedded and computational systems, IoT specialist. Teaches connected systems, edge computing and the hands-on IoT modules of the MSc Applied AI & IoT.
Professor
Manel Boumaiza
Data engineering, natural language processing and deep learning. Teaches data pipelines, NLP and neural networks in the MSc Applied AI & Data Science.
Assistant teacher
Ammar Djebabla
Cloud computing and distributed systems. Supports the cloud, DevOps and deployment modules across the MSc foundation year.
Academic team and teaching areas
| Name | Role | Teaching areas |
|---|---|---|
| Yacine Aslimi | Founder, president and academic director | Data science, applied AI strategy, Industry 5.0 skills; keynote speaker and conference lecturer |
| Abdelhak Touiti, PhD | Professor | Embedded and computational systems, IoT, edge AI |
| Manel Boumaiza | Professor | Data engineering, NLP, deep learning |
| Nedia Aouani | Professor | Data science and applied AI |
| Nouha Othman | Professor | Data science and applied AI |
| Djihane Houfani | Professor | Data science and applied AI |
| Ammar Djebabla | Assistant teacher | Cloud computing, distributed systems, DevOps |
Instructors assigned to a specific intake or module are confirmed by the academic team. Guest lecturers from industry and partner universities complete the team each year.
How we teach
01
Project-based learning
Each semester ends with a project defended before a jury: data pipeline, model, dashboard or connected prototype, built on an industrial case.
02
Industry inside the classroom
Case studies, hackathons such as the CND and GAIA challenges, and company placements connect the curriculum with real constraints.
03
Research and conferences
Faculty publish and present their work, from IEEE conferences to keynotes at partner universities, and bring it back to the programmes.
Explore the curriculum of each programme and the events and student challenges of the year.
Faculty interview · English, subtitled
Abdelhak Touiti, PhD: teaching applied AI and IoT
Engineer in embedded and computational systems and IoT specialist, Abdelhak Touiti teaches the connected-systems, data-engineering and edge-AI modules of the MSc Applied AI & IoT. In this interview he explains how AI2 connects theory with hands-on projects:
- understanding the business impact of every technical choice;
- a mathematical background to design efficient data-engineering pipelines;
- cloud, ETL and data-engineering technologies applied inside real projects;
- concrete, industry-oriented projects drawn from experience with companies such as Safran and Capgemini.