Data Science

Cloud Scale Machine Learning

GROUP TRAINING

Overview

Build machine learning models at any scale from in Cloud Scale Machine Learning, a comprehensive 2-day course designed for data and tech professionals. This course will provide participants with a comprehensive understanding of how to scale machine learning models and data analysis. In this course, you’ll learn the strategies and tools to determine the best fit for specific use cases and gain hands-on experience applying that knowledge with state-of-the-art tools. Participants will gain hands-on experience using technologies for scalable machine learning, such as Dask, Ray, Horovod, and DeepSpeed. Upon completion, participants be empowered to build machine learning models that only are only possible through cloud scale computing.

Duration

2 Days

Who Should Take This Course

Audience

Data Scientists, Data Engineers, Machine Learning Engineers, MLOps professionals.

Prerequisites

Participants should have intermediate programming skills (preferably in Python), an understanding of mathematics and statistics, basic familiarity with machine learning / neural networks, a grasp of computer science fundamentals, familiarity with common operating systems and basic command-line operations, and a willingness to review pre-course materials.

These prerequisites will help participants engage effectively with the course material and hands-on labs, making the learning experience more rewarding. Attendees will also need to be able to ssh into a supplied cloud instance during the course to complete the lab work.

Why You Should Take This Course

Upon completing this course, participants will:

Build an in-depth understanding of how to scale machine learning models and data analysis
Learn how to determine which scaling strategy and tools best fit your use case
Gain hands-on experience using state-of-the-art technologies for scalable machine learning, such as Dask, Ray, Hovorod and DeepSpeed
Develop the skills and expertise to build machine learning models with trillions of parameters, using petabytes of data

Course Outline

Cloud Scale Machine Learning

Day 1: Understanding Cloud Scale ML

1. Overview
2. Data Analytics with Dask SQL and VegaFusion
3. Model Parallelism and Data Parallelism
4. Model Considerations at Scale

Day 2: Tools for Scalable ML

1. Dask ML
2. Ray Train
3. Hovorod
4. DeepSpeed