Data Science Master Class 1

Subject code: MA5851:03 

This subject will provide students with the foundations for cutting-edge tools and techniques for high-performance and large-scale computing, with focus on computer models and software designed to handle Big Data sets in a distributed and/or parallel fashion. Particular focus will be given to distributed and parallel computing using Map- Reduce and similar models for management and processing of Big Data sets. The integration of commercial SAS packages with the Hadoop ecosystem will be employed as the software platform of choice. Efficient and intelligent exploratory data analysis techniques using SAS will also be covered.

It is a two-part subject, you must complete Master Class 1 before enrolling into Data Science Master Class 2.

Software platform: SAS exclusively 


Learning outcomes

  • use SAS programming methods to read, write, query and manipulate Hadoop data, manage the Hadoop Distributed File System (HDFS), execute MapReduce and Pig code from SAS, and interface SAS with Hive.
  • apply DS2, a fourth-generation SAS proprietary language for advanced data manipulation, which enables parallel processing and storage of large data with reusable methods and packages.
  • use processing methods to prepare structured and unstructured big data for analysis, in particular, organize the data into structured tabular form using Apache Hive, Apache Pig, and their integration with SAS.
  • perform efficient and intelligent exploratory data analysis using SAS in-memory statistics and SAS enterprise miner.

Assessment

Assessment for this course will occur at various times across the seven-week study period. Tasks may include online quizzes, discussion board activity, portfolio development, case studies, reflection, literature reviews presentations and reports.Feedback will be provided to you throughout the study period as well as a final grade at the conclusion of the study period.

Please note, unit structure and content are subject to change. Contact your JCU Online student advisor on 1300 535 919 for more information based on your particular circumstances.

 

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