Data Science Bootcamp

Learn via : Virtual Classroom / Online
Duration : 5 Days
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This five-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 workshop is designed for data scientists who currently use Python 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.



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


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

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