AI Pros Bootcamp
Week 1: Python & Tooling
1. Python & Tooling
2. Functions + Files + Better Profiling
3. Modules + OOP + Typer CLI
4. Streamlit GUI + (Optional) httpx
5. Git + GitHub + Ship Week 1
Week 2: Data Work (ETL + EDA)
1. Foundations for an Offline‑First Data Workflow
2. Verify + Clean + Join (first real EDA)
3. Transform → Feature Table → EDA Tables (Tidy data + time + outliers)
4. EDA with Plotly — Chart Choice + Uncertainty
5. Ship a trustworthy data product (rebuild + metadata + SQL lens)
Week 3: Machine Learning
1. ML in one picture + your dataset contract
2. Split + baseline + train
3. Evaluate + artifacts
4. Predict CLI + inference contracts
5. Write-up + submit
Week 4: Deep Learning
Modules
Week 6: Agentic AI
Week 7: Building AI Apps
A learning outcome is a concise description of what students will learn and how that learning will be assessed. Having clearly articulated learning outcomes can make designing a course, assessing student learning progress, and facilitating learning activities easier and more effective. Learning outcomes can also help students regulate their learning and develop effective study strategies.
Read Learning Outcomes for Week 7 Here.
Daily Sessions
- Day 1:
- [M1] Client-server Architecture
- Self-paced lab:
curl_lab.md(B5 repo) - [M2] FastAPI Introduction
- [M2] FastAPI Reading: Overview & Tooling (Session 1)
- Day 2:
- [M2] FastAPI Reading: Sessions (2 - 6)
- [M2] Becoming a 10x Developer
- Assignment: Build an API with FastAPI and Coding Agents (B5 repo)
- Day 3:
Week 8: Job Readiness
Read Learning Outcomes for Week 8 Here.
- Day 1:
- Week 7 Quiz (M1, M2 and M3)
- [M5] Deployment
- Capstone Progress Presentation
- Day 2:
- معرفة النفس
- Assingments to Submit:
- الاستفادة من شبكة العلاقات
- السيرة الذاتية
- Assingments to Submit: Resume (PDF)
- البحث عن الشركات
- معرفة النفس
- Day 3:
- Day 4:
- Final Capstone Presentation