Start with AITP
All members complete AITP before joining internal and client project teams. The program establishes the technical foundation and development workflow required to contribute to real machine learning systems.
Program overview
How to become a DAML engineer
DAML's AI Training Program (AITP) is the structured entry point for members to become engineers within the organization.
Join a project team
Members progress through training, evaluation, and a final project before transitioning into active engineering roles within DAML.
Curriculum
Syllabus
10 weeks, from probability and evaluation metrics through CNNs, transformers, diffusion models, and AI agents, with the project phase opening after Week 2. Every lesson is recorded on the AITP site.
Week 1
Intuition & ML landscape
Supervised vs unsupervised, different problem types, what ML can solve, cool applications, limitations (AGI, BCI, genetics)
Week 2
Math & metrics bootcamp
Probability, statistics, loss functions, evaluation metrics
After Week 2Project phase begins
Choose your final project track
Members select a real partner-aligned brief and form project teams with DAML mentors.
Milestones, tech stack guardrails, and accountability cadences are set before Week 3.
Week 3
Simple supervised classification
KNN, logistic regression, decision trees, Gini impurity
Week 4
Simple unsupervised + signal/time-series methods
K-means, PCA, NMF, FA, HMM, GFPA, Granger causality
Reinforcement learning
Q-learning, basic RL concepts
Week 5
Intro to deep learning + classical baselines
MLP, backprop, random forest, SVM
Week 6
Convolution & image recognition
Convolution, image recognition, YOLO
Week 7
Sequences & attention before transformers
Recurrent networks, simple attention, hard/soft attention, QKR, applications, LSTM
Week 8
Transformers & modern sequence models
Transformers, transformer internals, SSMs
Week 9
Generative modeling
AE, VAE, GAN, diffusion, flow matching
Week 10
Applications & agents
API, Token, MoE, SWARM, CLAW, MCP
Logistics
Schedule and requirements
What the semester asks of you, and what you get back for it.
01
Structure
- Weekly cadence
- Workshops run Saturdays 12:00–1:00 pm in Social Sciences 139.
- Project sessions
- Dedicated project work sessions follow immediately after from 1:00–2:00 pm with mentor check-ins.
- Mentorship
- Each project team is paired with experienced DAML engineers who guide scoping, execution, and delivery.
02
Requirements
- Prerequisites
- Comfort with Python from CS 101/201 or equivalent. Prior ML exposure is helpful but not required.
- Attendance
- More than two unexcused absences removes eligibility for certification. Recordings are provided for approved conflicts.
- Deliverables
- A final project showcase judged by our DS Directors. Weighted scores across presentation and exam inform whether members pass our program.