Data Science with Scala

Knowing a language is one thing, but being fluent and able to string together concepts in context is another. In this course, your Scala skills will be put in context allowing you to flex your skills in terms of data preparation, feature engineering, and creating data pipelines.

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About This Course

Put your Scala knowledge to good use by tackling Big Data analytics problems.

  • Learn to leverage the integration of Apache Spark™ and Scala.
  • Learn how use Spark’s machine learning pipelines to fit models and search for optimal hyperparameters using Scala in a Spark cluster.

Course Syllabus

  • Module 1 - Basic statistics and data types
  • Module 2 - Preparing data
  • Module 3 - Feature engineering
  • Module 4 -  Fitting a model
  • Module 5 - Pipelines and grid search

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

Recommended skills prior to taking this course

  • Experience with Java (preferred), Python, or another object­ oriented language.
  • General understanding of machine learning.


Course Staff

Scala Machine Learning instructor - Dr. Priya Dev

Dr Priya Dev

Dr Priya Dev is a lecturer of statistics at ANU and UNSW and also a founder of a mobile commerce startup, Qhopper. She completed a PhD in probability theory from ANU and Columbia University and has been a data analytics consultant to ASX listed companies and global banks. Qhopper is a massively scalable mobile commerce platform built on the Lightbend platform using Scala and Spark. It bridges the technology gap for hospitality businesses, helping them create better experiences and connect with new and existing customers through their own online ordering, CRM and business intelligence suite.