Renaissance: the Data & AI curriculum to Airbus Skywise

My public curriculum to become a complete data engineer, data analyst and data scientist for aerospace, with Palantir Foundry (the platform behind Airbus Skywise) at its centre. Every module is applied in Aerolisa, my flagship project. Independent learning project, not affiliated with, or connected to Airbus, Skywise or Palantir.

North star

1. Next: a data apprenticeship (alternance) at Airbus, Skywise ecosystem, Toulouse, starting September 2027.
2. Then: a data & AI specialist in the aerospace, space & defence (ASD) industry, in Europe or the USA.

Everything in this repository is ordered by how much it moves me toward step 1. Nothing is here "just because".

Two repositories, one system

Repository	Role	When
Renaissance	Learn: modules, exercises, notes, exit tests, career prep	Saturday
Aerolisa	Build: the flagship platform where every module is applied and shown to recruiters	Sunday

Each Renaissance module names the Aerolisa milestone it feeds. Learning without building is not allowed; building without the learning behind it is fragile.

How it works

• 16 modules, done in order (00 → 13). Two tracks run in parallel the whole time: 14 aerospace domain (mostly on the commute) and 15 interviews & applications.
• Two levels in every module. 🎯 Apprenticeship level is what an Airbus interviewer expects from an apprentice: it is mandatory. 🚀 Pro level is what makes me a strong junior: do it when ahead, or later. "100%" is reached through the Pro levels, over time, without blocking the critical path.
• Sizes, not dates. Each module is sized in weekends. The order never changes; the speed does.
• Three gates. Each gate is a state I must reach, checked honestly in PROGRESS.md:
  • Gate 1: Application-ready. Modules 00–07 at 🎯 level. Aerolisa live with a demo link and a Foundry build.
  • Gate 2: Interview-ready. Modules 08–10 at 🎯 level. Aerolisa engine health v2 and planner done.
  • Gate 3: Complete profile. Modules 11–13 at 🎯 level. Aerolisa analytics pack, industrialization, copilot.
• Exit tests close every module: closed-book, timed, no AI. Scores go in checkpoints/.

Full plan: PLAN.md · What Airbus asks for and where I learn it: SKILLS_MATRIX.md.

The weekly rhythm

Slot	What	Where
Saturday (1 session, 3–4 h)	Learn + exercises of the current module	Renaissance modules/NN/work/
Sunday (1 session, 3–4 h)	Next step of the paired Aerolisa milestone	Aerolisa
Commute / phone	Module 14 reading, Foundry docs, flashcards, interview answers out loud	Anki + notes
Sunday evening (15 min)	Weekly review	GitHub issue

If weekdays free up, add a third session. The order stays the same.

My rules

1. Ship every weekend. At least one pushed commit in Aerolisa or Renaissance.
2. Floor on bad weekends: one session and one commit. Never a zero week.
3. First attempt without AI. AI reviews my work; it never writes the first version.
4. Build beats reading. Every module ends with something in Aerolisa.
5. Cut the 🚀 Pro level, never the build. When behind, drop Pro items, keep the milestone.
6. Apply before feeling ready. A posting that matches 60–70% gets an application.
7. Protect rest. One free half-day every weekend, one full weekend off every six.

Modules

#	Module	Roles	Size	Feeds Aerolisa
00	Launch	all	1 wk	M0
01	Python for data	DE · DA · DS	1 wk	M1
02	SQL	DE · DA · DS	3 wk	M2
03	Data modeling & architecture	DE · DA	1 wk	M2 · M3
04	PySpark	DE · DS	2 wk	M2
05	Pipelines & data quality	DE	1 wk	M2
06	Foundry I: data engineering	DE	3 wk	M4
07	Foundry II: ontology, apps & analytics	DE · DA · AI	3 wk	M3 · M4
08	Statistics & probability	DA · DS	2 wk	M5 · M6
09	Machine learning	DS · AI	3 wk	M6
10	Time series & predictive maintenance	DS · AI	3 wk	M6 · M7
11	Analytics, BI & storytelling	DA	2 wk	M8
12	Software engineering, MLOps & cloud	DE · DS	2 wk	M7 · M9
13	GenAI, LLMs, agents & AIP	AI · DS	3 wk	M10
14	Aerospace & ASD domain	all	parallel	M11
15	Interviews & applications	all	parallel + 2 wk	M11

wk = weekend (one Saturday session + one Sunday session). Total ≈ 32 weekends of focused work, plus the parallel tracks.

Repository structure

Renaissance/
├── modules/
│   └── NN_topic/
│       ├── README.md         # why, 🎯 and 🚀 levels, steps, exit test, resources
│       └── work/             # my notes, solutions, code and tests
├── career/                   # Airbus & ASD knowledge, CV, applications, pay, interviews
├── palantir/                 # Foundry & AIP skill map, certifications, glossary
├── checkpoints/README.md     # exit tests and score log
├── PLAN.md                   # the ordered path, gates, rhythm, what to do when behind
├── SKILLS_MATRIX.md          # job-posting requirement → module → proof
├── PROGRESS.md               # modules, gates, certifications, Aerolisa, career
├── RESOURCES.md              # curated, free first
├── WEEKLY_REVIEW_TEMPLATE.md
└── .github/                  # CI for exercise tests, issue templates

Getting started

git clone https://github.com/xdmanflow/Renaissance.git
cd Renaissance
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
pytest -q   # runs every test_*.py found under modules/*/work/

Author

Manil DOUDOU, engineering student in computer science (AI & Data Science), CESI Toulouse.

License

Code under the MIT License. Notes may be reused with attribution.