Recruitment
AI Training Program
The structured entry point into DAML engineering. Members who complete AITP transition directly into internal and client-facing project teams.
Program Overview
AITP: The pathway into DAML engineering
DAML's AI Training Program (AITP) is the structured entry point for members to become engineers within the organization.
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.
Members progress through training, evaluation, and a final project before transitioning into active engineering roles within DAML.
Explore our curriculumCurriculum
Syllabus
Gradient descent, loss functions, bias-variance tradeoff, and structural risk minimization.
Hyperparameter tuning, cross-validation, train-test splits, and model evaluation.
Hands-on with linear and logistic regression, k-nearest neighbors, and SVMs.
Cleaning with emphasis on missing data and encodings that fight the curse of dimensionality.
Text and image preprocessing plus exploratory data analysis methods like ROC analysis and Pearson correlations.
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.
Principal component analysis and manifold learning techniques like MDS, Isomap, spectral clustering, and t-SNE.
Clustering with k-means and expectation-maximization.
Decision trees, information theory, random forests, AdaBoost, XGBoost, and generalized additive models.
Architecture design, activation functions, universal approximation, and backpropagation.
Convolutional layers, kernels, pooling strategies, and computer vision applications.
Motivation, vanishing gradients, and LSTM gate mechanics for NLP workflows.
Transformer architecture, semi-supervised fine-tuning, and practical BERT + LLM deployments.
Logistics
Expectations & Information
Weekly cadence
Workshops run Saturdays 2:00–3:00 pm in Social Sciences 139.
Project sessions
Dedicated project work sessions follow immediately after from 3:00–4:00 pm with mentor check-ins.
Mentorship
Each project team is paired with experienced DAML engineers who guide scoping, execution, and delivery.
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.