Best AI & Data Science Training Curriculum for
Developed with Andrew Ng, deeplearning.ai, and delivered by Stanford educators. We train specialists in Computer Vision, Natural Language Processing, Data Engineering & Datascience.
Overview of Topics Covered
PROGRAMMING FOR AI
Focused Program For Quants and Scientists: In-depth programming review of Algorithms and Data Structures with Python. Best practices for data wrangling on real-world datasets
Based on your current on-going projects, engineers specialize in the most relevant field of AI relevant to your business (e.g: e-commerce recommender systems, fraud detection in Fintech)
MATH FOR AI
Focused Program For Software Engineers: Numerical Linear Algebra, Multivariate Calculus, Statistics & Optimization for Theoretical Aspects of Data Science
Engineers build from scratch, real-world projects co-developed with our industrial partners. They are guided by senior engineers with experience in full cycle machine learning.
Data-driven algorithms for unstructured datasets such as images, audio, video or temporal signals. Extensive practice in modern Deep Learning frameworks such as Tensorflow & Pytorch
ADVANCED STATISTICAL LEARNING & MACHINE LEARNING
Pattern recognition on structured datasets for classification, regression or unsupervised tasks. Engineers become familiar to the different APIs and libraries to speed up their developments
Featured Case Study:
HYPERBOLIC EMBEDDINGS FOR HIERARCHICAL DATASETS
Our partners took advantage of existing hierarchical relations on their SQL database by computing embeddings in a non-euclidean geometric space. This new structural insight allowed them to substantially improve their in-house recommender system
A quick prototype enabled our partners to translate their Spanish datasets into English to use the latest pre-trained models in sentiment analysis. As a result, automated customer feedback improved in Spanish speaking countries