Cloudera Data Scientist Training

Data Scientist Training

Summary

This four-day workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges.

Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment.

Description

The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful.

Duration

4 Days

Objectives

The workshop includes brief lectures, interactive demonstrations, hands-on exercises, and discussions covering topics including:

• Overview of data science and machine learning at scale

• Overview of the Hadoop ecosystem

• Working with HDFS data and Hive tables using Hue

• Introduction to Cloudera Data Science Workbench

• Overview of Apache Spark 2

• Reading and writing data

• Inspecting data quality

• Cleansing and transforming data

• Summarizing and grouping data

• Combining, splitting, and reshaping data

• Exploring data

• Configuring, monitoring, and troubleshooting Spark applications

• Overview of machine learning in Spark MLlib

• Extracting, transforming, and selecting features

• Building and evaluating regression models

• Building and evaluating classification models

• Building and evaluating clustering models

• Cross-validating models and tuning hyperparameters

• Building machine learning pipelines

• Deploying machine learning models

Technologies

Participants gain practical skills and hands-on experience with data science tools including:

• Spark, Spark SQL, and Spark MLlib

• PySpark and sparklyr

• Cloudera Data Science Workbench (CDSW)

• Hue

Prerequisites

Workshop participants should have a basic understanding of Python or R and some experience exploring and analyzing data and developing statistical or machine learning models. Knowledge of Hadoop or Spark is not required.

Setup Requirements

Strong internet connection is required throughout the class.

For VIRTUAL deliveries of this course, please note:

The interactive demonstrations and exercises will be conducted using Cloudera Data Science Workbench (CDSW). The learning experience will be enhanced if the student has two monitors: one to display the instructor's CDSW environment and the other to display the student's CDSW environment.

Upcoming Classes

Online

Instructor-led online training

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
Virtual Classroom, Singapore (Cloudera) Sep 3 – Sep 6
Virtual Classroom, AMER (Cloudera) Oct 1 – Oct 4
Oct 29 – Nov 1
Virtual Classroom, EMEA (PUE) Oct 15 – Oct 18
Nov 5 – Nov 8
Virtual Classroom, EMEA (Cloudera) Nov 19 – Nov 22

Classes in bold are guaranteed to run!

Poland

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
Warsaw, Poland (Compendium) Sep 9 – Sep 12
Krakow, Poland (Compendium) Nov 18 – Nov 21

Classes in bold are guaranteed to run!

Hungary

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
Budapest, Hungary (Compendium) Sep 23 – Sep 26

Classes in bold are guaranteed to run!

United Kingdom

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
London, England (Training Room Hire) Sep 24 – Sep 27

Classes in bold are guaranteed to run!

Spain

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
Madrid, Spain (PUE) Oct 15 – Oct 18

Classes in bold are guaranteed to run!

Czech Republic

Location Aug 2019 Sep 2019 Oct 2019 Nov 2019
Prague, Czech Republic (Compendium) Nov 12 – Nov 15

Classes in bold are guaranteed to run!

Onsite Training

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Public Training

Virtual Classroom, Singapore (Cloudera)

Budapest

London

Virtual Classroom, AMER (Cloudera)

Virtual Classroom, EMEA (PUE)

Madrid, Madrid

Virtual Classroom, EMEA (Cloudera)

Kraków, Poland

Prague

Warsaw, Poland


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