Data Science Training

News
INTRODUCING SNOWFLAKE TRAINING FUNDS ➤  Learn more HERE. To purchase, contact us.  COVID-19 UPDATES ➤   Instructor-led classes will be delivered via virtual classroom only.

Data Science Training

Data Science Training

Summary

This 3-day class is ideal for Snowflake users who are interested in developing the skills and experience necessary to utilize Snowflake Data Cloud for Data Science workloads. This course will cover key concepts, features, considerations, and best practices for building out data science solutions within Snowflake.

Duration

3 Days

Objectives

By the end of this class you will be able to:

  • Collect and access data from Snowflake Data Marketplace and other sources
  • Manage and architect data lakes and real time streams
  • Employ Snowflake best practices for developing or querying semi-structured and other data types
  • Work with supervised and unsupervised machine learning models using some of the most relevant open source framework and libraries
  • Formulate data science and machine learning workflow and data pipelines
  • Manage and deploy machine learning models at scale with APIs
  • Visualize and collaborate on machine learning results

Audience

Who should attend this course?

  • Data scientists who build and train machine learning models
  • Data scientists and data analysts who use the machine learning models to conduct predictive and prescriptive analytics

Prerequisites

  • Basic knowledge of SQL is required
  • Foundational knowledge of databases
  • Python or some other object-oriented programming language

Setup Requirements

Snowflake Training students need...

  • to bring a laptop
  • a Snowflake compatible browser (see options HERE)

Outline

Upcoming Classes

Online

Instructor-led online training

Location Nov 2021 Dec 2021 Jan 2022 Feb 2022 Mar 2022 Apr 2022 May 2022 Jun 2022 Jul 2022 Aug 2022 Sep 2022 Oct 2022 Nov 2022
Virtual Classroom (AMER/CT) Nov 30 – Dec 2
Jan 25 – Jan 27
Feb 23 – Feb 25
Mar 22 – Mar 24
Apr 26 – Apr 28
Virtual Classroom (EMEA/GMT) Dec 13 – Dec 15
Mar 8 – Mar 10
Apr 26 – Apr 28

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