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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for Course EDA025F Programming Models and Practice for Big Data

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General
  • EDA025F
  • Temporary
Course Name
  • Programming Models and Practice for Big Data
Course Extent
  • 7.5
Type of Instruction
  • Third-cycle course
Administrative Information
  • 7121 (Computer Science (LTH))
  • 2015-09-08
  • FN1/Anders Gustafsson

Current Established Course Syllabus

General
  • English
  • If sufficient demand
Aim
  • This course will teach the doctoral students how to analyze and design programs for big data. It will provide knowledge on big data architectures, languages, and ecosystems with a focus on Spark. The techniques presented in the course are expected to have high impacts in a variety of fields such as data analysis, customer recommendation, trend prediction, pattern recognition, etc.
Contents
  • The course consists of four full-day sessions that will address:
    1/ Cloud architectures, Spark concepts, and Spark programming.
    2/ Intermediate and advanced Spark.
    3/ Supervised machine-learning with Spark: MLlib and MLlib programming.
    4/ Unsupervised machine learning.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • show a knowledge of the architectures for big data processing.
    show understanding of the structure of big data programming models and ecosystems
Competences and Skills
  • For a passing grade the doctoral student must
  • show her/his capability to operate big data architectures and design and write programs using Spark.
Judgement and Approach
  • For a passing grade the doctoral student must
  • show the ability to select and assess architectures and algorithms for big data problems.
Types of Instruction
  • Lectures
  • Laboratory exercises
  • Exercises
  • Project
Examination Formats
  • Written assignments
  • The assessment will consist of programs and reports to hand in
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • Good programming skills in Java, Scala, or Python. Knowledge of statistics
Selection Criteria
Literature
  • Karau, A., Wendell, P. & Zaharia, M.: Learning Spark. O'Reilly Media, Inc, 2015. ISBN 9781449358624.
    Karau, H., Konwinski, A., Wendell, P. & Zaharia, M.: Learning Spark. 2015. ISBN 9781449358624.
Further Information
Course code
  • EDA025F
Administrative Information
  • 2015-09-08
  • FN1/Anders Gustafsson

All Established Course Syllabi

1 course syllabus.

Valid from First hand in Second hand in Established
Autumn 2015 2015‑06‑03 16:54:15 2015‑08‑19 11:19:00 2015‑09‑08

Current or Upcoming Published Course Occasion

No matching course occasion was found.

All Published Course Occasions

1 course occasion.

Course syllabus valid from Start Date End Date Published
Autumn 2015 2015‑09‑07 (approximate) 2015‑10‑30

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