BU CAS Computer Science 591 L1
Data Mechanics









2016-01-19lecture
  • lecture notes
  • introduction, background, and goals
  • organization and workflow
  • potential data sets and problems
2016-01-21lecture:
data and
transformations
  • lecture notes
  • formal definitions of data
    • relational model
    • MapReduce paradigm
    • other algebraic considerations
  • data provenance
2016-01-26lecture:
data and
transformations
  • data transformations
  • fine-grained data provenance
  • data flows in the relational model
  • k-means relational data flow
2016-01-27project
2016-01-28lecture:
data and
transformations
  • algorithms in the relational model
    • Floyd-Warshall shortest paths
    • shortest routes
    • k-means clustering
2016-02-02lecture:
data and
transformations
  • algorithms using the MapReduce paradigm
    • using MapReduce in MongoDB
    • k-means clustering
    • comparing data sets
2016-02-04lecture:
models &
algorithms
  • Cartesian products using MapReduce
  • spatial algorithms & data structures
    • minimum/maximum spanning tree
    • shortest/widest paths
    • quadtrees
2016-02-09lecture:
models &
algorithms
  • relational queries in MongoDB
  • repository/platform architecture
  • systems and models
    • representations for modeling
    • models used in algorithms
2016-02-11lecture:
models &
algorithms
  • more on provenance
  • PROV standard
2016-02-16
Monday sched.
    2016-02-18lecture:
    models &
    algorithms
    • JSON schemas
    • more on systems and models
    • tools for finding models
      • matrix equations
      • SMT solvers
      • linear programming
    2016-02-23lecture:
    optimization
    • optimization & decomposition
    2016-02-25lecture:
    optimization
    • review of calculus
    • basic gradient descent
    2016-03-01lecture:
    optimization
    2016-03-03lecture:
    optimization
      2016-03-08recess
        2016-03-10recess
          2016-03-15lecture
          • review for midterm
          2016-03-17
          Tuesday
          2:05-3:05 PM
          midterm
          exam
            2016-03-22lecture:
            statistics
            • review of midterm solutions
            • lecture notes
            • Cauchy-Schwarz inequality
            • means & standard deviations
            • covariance & correlation
            2016-03-24lecture:
            statistics
            • lecture notes
            • more on covariance & correlation
            • distributions
            • p-values & significance
            2016-03-29lecture:
            statistics
            2016-03-31lecture:
            visualization
            • SVG and D3.js
            • networks and graphs with D3
            2016-04-05lecture:
            visualization
            • plots & charts with D3
            2016-04-07lecture:
            visualization
            • web-based map APIs
            • visualization design topics
            • visual perception
            2016-04-12lecture:
            other topics
            • more on GeoJSON and mapping
            • comments on ZIP archives
            • crowdsourcing
            • incentive compatibility
            2016-04-13project
            2016-04-14lecture:
            other topics
            • web services & web applications
            • REST architectures
            • implementing a web service
            2016-04-19lecture:
            other topics
            • review for midterm
            2016-04-21
            Thursday
            2:05-3:05 PM
            midterm
            exam
              2016-04-26
              Tuesday
              2:00-5:00 PM
              poster
              session
                2016-04-28lecture