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• Python basics
• Branches
• Domains

Note: sections marked with * are in Draft version

Python basics | ^

• P0.0 Key ideas
  • What is Python
  • What to install
  • Language execution model
  • Namespaces and Modules
  • Variables and Dynamic typing
  • Where do types come from?

• P0.1 Basic Data Types and I/O
  • Data types
    • Numericals (Integer, Float, Complex)
    • Strings
    • random & math modules
    • Booleans
  • I/O commands
    • Print
    • Input

• P0.2 Flow control
  • 'while' loop
  • 'if' control
  • Break, continue, pass
  • 'for' loop
  • range

• P0.3 List
  • The 'list' object
  • Constructing lists
  • List slicing
  • List of lists
  • List functions & methods

• P0.4 Dictionary, Tuple & Set
  • The 'dictionary' object
  • Constructing dictionaries
  • Combining dictionary and list
  • Dictionary vs. List
  • Dictionary functions and methods
  • The 'tuple' object
  • The 'set' object *

• P0.5 Functions
  • Functions defined
  • Arguments
  • Variable Scope
  • Functions as first-class objects *
  • Generators *

• P0.6 File handling
  • 'open' a file *
  • Text files
    • Reading from and writing to a text file
    • tell() and seek()
  • Binary files
  • Pickling

Branches | ^

- B1: OOP and advanced Python | ^

• B1.0 Object-oriented programming
  • Introduction *

- B2: Numpy and Matplotlib | ^

• B2.0 Numpy and the 'array' object
  • What is 'numpy'?
  • Array construction
  • Array construction (cont'd)
  • Array indexing
  • Array slicing
  • Array operations
  • Array functions

• B2.1 Matplotlib: plotting in Python
  • What is 'matplotlib'?
  • Basic plotting with 'plot'
  • Customizing the plot
  • Common plots
  • Multiple plots *

- B3: Scipy | ^

• B3.0 Scipy: introduction to scientific computing
  • What is Scipy *

- B4: pandas | ^

• B4.0 pandas: Series and DataFrame objects
  • What is pandas?
  • The 'Series' object
  • Indexes and NaN values
  • The 'DataFrame' object
  • Data access in DataFrame
  • Modifying Columns in DataFrame
  • Modifying Rows in DataFrame *
  • Plotting a Series/DataFrame object
  • The power of 'GroupBy'

Domains | ^

- D1: Hypothesis testing | ^

• D1.0 Research design and Hypothesis testing
  • Research design
  • Experimental design
  • What is hypothesis testing

• D1.1 Distributions
  • Distributions
  • The normal distribution
  • The t distribution
  • The f distribution

• D1.2 Statistical controls
  • Descriptive statistics

Test for differences between 2 groups

• t-Test (independent samples)
• Paired t-test
• One sample t-test
• Chi Square test *
  

Test for differences between 3 or more groups

• One way ANOVA
• Write your own ANOVA function
• Repeated measures ANOVA
• Two way ANOVA
• Analysis of Covariance (ANCOVA) *

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