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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

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  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

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  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