HPCDS is a CCE-PROFICIENCE semester long course aimed at students, researchers, and professionals working on computational modeling or Data science applications who wish to upskill. This course will be organized during evening hours so that regular students from other institutes/colleges and working professionals can participate without affecting their normal schedule.
Admissions open for January – May 2021 Term. Apply online!
Syllabus of the course
Mathematics for Data Science: Introduction to Calculus, Linear algebra, Probability theory and Optimization. Introduction toComputing: Representation of numbers and arithmetic in the computer, Round-off errors, Basic data types, and Introduction toObject-Oriented Programming (OOP) for Data Science, Numba just-in-time (JIT) compiler for Python.
Parallel Architecture: Fundamentals of Parallel computer Memory Architectures; Multi-core computer, Parallel programming models, MPI, OpenMP,Distributed and GPU implementations for Data Science Applications, Numba GPU implementation, MapReduce frameworks.HPC for Modeling and Simulation: Developing a multi-node/multi-GPU solver for a system of algebraic equations and for thesolution of the Poisson problem. HPC for Data Science: Distributed training with TensorFlow, Taming Big Data with HadoopMapReduce and Spark.
Pre-requisites: Basic Mathematics, Basics of Computer Systems, Basic Data Structures and Programming, Basic Algorithms.Course
Course Timings: Tuesday & Thursday 6.00 pm to 7.30 pm (will be decided in the first class)
Course Brochure: Course No. 7, Page 16.