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      1. Column 1
        1. General neuroinformatics
          1. Digital brain atlasing
          2. Neuroimaging
          3. Neuromorphic engineering
          4. Ontologies
          5. Optogenetics
          6. Reproducibility
          7. Standards and best practices
          8. Tools
          9. Workflows
        2. Computational neuroscience
          1. Biochemical networks
          2. Dynamic systems
          3. Mathematics
          4. Neural coding
          5. Statistics
      2. Column 2
        1. Computer science
          1. Databases
          2. High performance computing
          3. Software engineering
        2. Clinical neuroscience
          1. Clinical neuroinformatics
            1. Cognitive neuroinformatics
          2. Pain
          3. Psychiatric disorders
          4. Schizophrenia
      3. Column 3
        1. General neuroscience
          1. Neuroscience
            1. Developmental neuroscience
          2. Cell signaling
          3. Connectomics
          4. Glia
          5. Electrophysiology
            1. EEG
            2. ERP
          6. Learning and memory
          7. Neuroanatomy
          8. Neurobiology
          9. Neurodegeneration
          10. Neuroimmunology
          11. Neurophysiology
          12. Neuropharmacology
          13. Synaptic plasticity
          14. Visual system
      4. Column 4
        1. Genomics
        2. Data science
          1. Data management
          2. Data analysis
          3. Data structures/models
        3. Open science
        4. Education
        5. Ethics

Foundations of Data Science

25 parts
Datalabcc: Foundations of Data Science. Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.

Statistics: Do it yourself!

Datalabcc
Sep, 2016
0 likes
You don't have to be a wizard to do statistics! Speaker: Barton Poulson.

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Topics

  • General neuroinformatics (55)
    • Digital brain atlasing (12)
    • Neuroimaging (22)
    • Neuromorphic engineering (10)
    • Ontologies (3)
    • Optogenetics (1)
    • Reproducibility (3)
    • Standards and best practices (2)
    • Tools (5)
    • Workflows (4)
  • Computational neuroscience (100)
    • Biochemical networks (1)
    • Dynamic systems (2)
    • Mathematics (8)
    • Neural coding (20)
    • (-) Statistics (2)
  • Computer science (37)
    • Databases (7)
    • High performance computing (19)
    • Software engineering (1)
  • Clinical neuroscience (20)
    • Clinical neuroinformatics (9)
      • Cognitive neuroinformatics (5)
    • Pain (2)
    • Psychiatric disorders (4)
    • Schizophrenia (2)
  • General neuroscience (82)
    • Neuroscience (11)
      • Developmental neuroscience (7)
    • Cell signaling (2)
    • Connectomics (1)
    • Glia (1)
    • Electrophysiology (12)
    • Learning and memory (4)
    • Neuroanatomy (24)
    • Neurobiology (8)
    • Neurodegeneration (4)
    • Neuroimmunology (2)
    • Neurophysiology (20)
    • Neuropharmacology (2)
    • Synaptic plasticity (2)
    • Visual system (12)
  • Genomics (5)
  • Data science (37)
    • Data management (15)
    • Data analysis (18)
    • Data structures/models (7)
  • Open science (20)
  • Education (3)

Difficulty levels

  • Beginner (1)

Types

  • Video (1)
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Providing informatics educational resources for the global neuroscience community

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