This course provides you with the fundamental understandings of the latest language models built using deep learning architectures.
You will start with the traditional language models, learn about word embeddings, attention and then move on to transformer models. At the end of this course, you will be able to build efficient language models, and tell how well they are performing.
This course will prepare you for more advanced studies in deep learning and more intermediate positions in AI research and opportunities.
After successfully completing the program, you will be:
Learners and practitioners who have a fundamental understanding and practice of basic AI and ML concepts including Neural Networks are ideal for this course. You should have strong foundations in statistics, computer science & mathematics.
Knowledge of beginning and intermediate AI as exemplified by the topics in AI: Basics
Prior knowledge of high level machine learning libraries such as keras
Bi-weekly live, cohort-based lessons with labs and quizzes
Ten or more hours/week to interact with an experienced & accomplished mentor
Complex problems that challenge you to apply what you learn
10–12 week long Capstone Project with one of our partner companies or faculty