7/27/2019 Topics for examns.docx
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Topics
1 examen
Algorithms
Big O notation
Exhaustive enumerationGuess and check
Successive approximation
Divide and conquer algorithms
Binary search
Merge sort
Hashing
Orders of growth
Exponential
Polynomial
Linear
Log
Amortized analysis
Linguistic issuesValues, types, expressions variables
Builtin types: int, float, string, list, dictionary, tuple
Mutability and aliasing
Control flow and iteration
Functions and methods
Input/output
Recursion and call stacks
Software engineering
Debugging
Loop invariants
Specifications
Anything needed to successfully complete problem sets
Topics for Quiz 2
Material Through Lecture
17
(* indicates material covered since
Quiz 1)
Algorithms
Big O notation
Exhaustive enumeration
Guess and check
Successive approximation
Divide and conquer algorithms
Binary search
Merge sort *
Hashing *
Orders of growth
Exponential
Polynomial
Linear
Log
7/27/2019 Topics for examns.docx
http://slidepdf.com/reader/full/topics-for-examnsdocx 2/3
Amortized analysis
Linguistic issues
Values, types, expressions variables
Builtin types: int, float, string, list, dictionary, tuple
Mutability and aliasing
Control flow and iteration
Functions and methodsInput/output
Recursion and call stacks
Exceptions *
Polymorphism *
Classes, objects, inheritance *
Pylab *
Software engineering
Debugging
Loop invariants
Data abstraction and inheritance *
Specifications
Simulations *
Random walks
Monte Carlo methods
Understanding data *
Simple probability
Standard deviation, coefficient of variation
Confidence intervals and levels
Linear regression
Goodness of a fit
Plotting/Pylab
Distributions
Anything needed to successfully complete problem sets
Algorithms
Big O notation
Exhaustive enumeration
Guess and check
Successive approximation
Divide and conquer algorithms
Binary search
Merge sort
Hashing
Orders of growth
ExponentialPolynomial
Linear
Log
Amortized analysis
Depth first search and backtracking *
Breadth first search *
Linguistic issues
Values, types, expressions, variables
7/27/2019 Topics for examns.docx
http://slidepdf.com/reader/full/topics-for-examnsdocx 3/3
Builtin types: int, float, string, list, dictionary, tuple
Mutability and aliasing
Control flow and iteration
Functions and methods
Input/output
Recursion and call stacks
Exceptions
PolymorphismClasses, objects, inheritance
Pylab
Software engineering
Debugging
Loop invariants
Data abstraction and inheritance
Specifications
Simulations and modeling
Random walks
Monte Carlo methods
Graph-based models *
Understanding data
Simple probability
Standard deviation, coefficient of variation
Confidence intervals and levels
Linear regression
Goodness of a fit
Plotting/Pylab
Distributions
Building computational models *
Evaluating fits *
Overfitting *
Statistical sins *
GIGO *Texas sharpshooter *
Data enhancement *
Non-representative sample *
cum hoc ergo propter hoc *
Optimization Problems *
Knapsack *
Shortest path *
Dynamic programming/memoization *
Graph problems *
Depth first and breadth first search *
Shortest path in graphs *Implicit graph generators *
Max clique *
Anything needed to successfully complete problem sets
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