Hewlett Packard Enterprise Data Science Institute

101 Intro to HPC (offered every semester) is designed for students beginning their training and is a prerequisite for all other HPE DSI courses. After completing this, a student can choose one or more script programming courses like 211 R (offered every semester), 212 Python (offered every semester), and/or 221 Julia (offered only in the Spring semester). 201 C++ (offered only in the Spring semester) provides a scientific programming background for most users. Students interested in parallel programming, such as 303 GPU Programming (offered only in the Spring semester), should have knowledge of low-level programming languages such as C++ or Fortran. Upon completing 212 Python, 211 R, 271 Excel (offered only in the Fall and Spring semesters), and/or 221 Julia, students can take the 261 Principles of Data Management course (offered every semester), followed by 311 Machine Learning (offered every semester) and then 312 Deep Learning (offered in the Spring semester). 212 Python is a prerequisite for 261, 311, and 312. 311 Machine Learning is a prerequisite for 312 Deep Learning. 301 Parallel Programming with OpenMP and 302 Parallel Programming with MPI are offered only in the Fall semester. 313 Introduction to Natural Language Processing and Large Language Models (offered every semester) requires 311 Machine Learning. 400 Introduction to Bioinformatics and NGS Data Analysis (offered in Fall and Spring semesters) requires 212 Python and 261 Principles of Data Management. 411 Selected Topics in AI (offered in Fall and Spring semesters) requires 311 Machine Learning and 312 Deep Learning.

Attendance is mandatory. Grades (Pass/Fail), and badges, will not be assigned to students who fail to attend at least 12 hours of synchronous instruction.