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bigdata17

BST 262: Computing for Big Data - 2017/2018

Week 1 - Basic tools

  • Lecture 1. Unix scripting, make
  • Lecture 2. Version control: Git and GitHub

Week 2 - Creating and maintaining R packages

  • Lecture 3. Rationale, package structure, available tools
  • Lecture 4. Basics of software engineering: unit testing, continuous integration, code coverage

Week 3 - Software optimization

  • Lecture 5. Measuring performance: profiling and benchmarking tools
  • Lecture 6. Improving performance: an introduction to C/C++, Rcpp

Week 4 – Databases

  • Lecture 7. Overview of SQL and noSQL databases
  • Lecture 8. R database interfaces

Week 5 - Analyzing data that does not fit in memory

  • Lecture 9. Pure R solutions, JVM solutions
  • Lecture 10. An introduction to parallel computing; clusters and cloud computing

Week 6 – Visualization

  • Lecture 11. Principles of visualization
  • Lecture 12. Javascript and d3, maps and GIS

Weeks 7 & 8 - Guest lectures (order and precise schedule TBD)

  • Lecture 13. Software project management
  • Lecture 14. R and Spark
  • Lecture 15. Advanced GIS and remote sensing
  • Lecture 16. Cluster architecture

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  • HTML 64.1%
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  • CSS 8.2%
  • JavaScript 4.6%
  • Shell 0.1%