Overview
Want to learn how to solve coding problems easily and efficiently?
Time to learn about the pillars of good code and programming: Data structures and algorithms. In the Data Structures Essentials: Pseudocode with Python Examples zyBook, you will learn and master these basics in pseudocode and Python.
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Course Details
The Data Structures Essentials: Pseudocode with Python Examples zyBook teaches essential data structures and algorithms with minimal text, maximum interactivity.

INTRODUCTIONIntroduction What is AI good for?

GRAPHSEARCH ALGORITHMSBreadthfirst search introduction Breadtfirst search implementation Depthfirst search introduction Depthfirst search implementation I  with stack Depthfirst search implementation II  with recursion Enhanced search algorithms introduction Iterative deepening depthfirst search (IDDFS) A* search introduction

BASIC SEARCH & OPTIMIZATION ALGORITHMSBruteforce search introduction Bruteforce search example Stochastic search introduction Stochastic search example Hill climbing introduction Hill climbing example

METAHEURISTIC OPTIMIZATION METHODSHeuristics VS metaheuristics Tabu search introduction Simulated annealing introduction Simulated annealing  function extremum I Simulated annealing  function extremum II Simulated annealing  function extremum III Travelling salesman problem I  city Travelling salesman problem II  tour Travelling salesman problem III  annealing algorithm Travelling salesman problem IV  testing Genetic algorithms introduction  basics Genetic algorithms introduction  chromosomes Genetic algorithms introduction  crossover Genetic algorithms introduction  mutation Genetic algorithms introduction  the algorithm Genetic algorithm implementation I  individual Genetic algorithm implementation II  population Genetic algorithm implementation III  the algorithm Genetic algorithm implementation IV  testing Genetic algorithm implementation V  function optimum Swarm intelligence intoduction Partical swarm optimization introduction I  basics Partical swarm optimization introduction II  the algorithm Particle swarm optimization implementation I  particle Particle swarm optimization implementation II  initialize Particle swarm optimization implementation III  the algorithm Particle swarm optimization implementation IV  testing

MINIMAX ALGORITHM  GAME ENGINESGame trees introduction Minimax algorithm introduction  basics Minimax algorithm introduction  the algorithm Minimax algorithm introduction  relation with tictactoe Alphabeta pruning introduction Alphabeta pruning example Chess problem

BUILDING TICTACTOEAbout the game Cell Constants and Player Game implementation I Game implementation II Board implementation I Board implementationj II  isWinning() Board implementation III Minimax algorithm Running tictactoe

INTERVIEW: SINGAPOREAN EXPERTBackground of Expert Information and Communication Technology in Singapore
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Our Other zyBooks & Courses
The Data Structures Essentials: Pseudocode with Python Examples zyBook will pair well with the following:

INTRODUCTIONIntroduction What is AI good for?

GRAPHSEARCH ALGORITHMSBreadthfirst search introduction Breadtfirst search implementation Depthfirst search introduction Depthfirst search implementation I  with stack Depthfirst search implementation II  with recursion Enhanced search algorithms introduction Iterative deepening depthfirst search (IDDFS) A* search introduction

BASIC SEARCH & OPTIMIZATION ALGORITHMSBruteforce search introduction Bruteforce search example Stochastic search introduction Stochastic search example Hill climbing introduction Hill climbing example

METAHEURISTIC OPTIMIZATION METHODSHeuristics VS metaheuristics Tabu search introduction Simulated annealing introduction Simulated annealing  function extremum I Simulated annealing  function extremum II Simulated annealing  function extremum III Travelling salesman problem I  city Travelling salesman problem II  tour Travelling salesman problem III  annealing algorithm Travelling salesman problem IV  testing Genetic algorithms introduction  basics Genetic algorithms introduction  chromosomes Genetic algorithms introduction  crossover Genetic algorithms introduction  mutation Genetic algorithms introduction  the algorithm Genetic algorithm implementation I  individual Genetic algorithm implementation II  population Genetic algorithm implementation III  the algorithm Genetic algorithm implementation IV  testing Genetic algorithm implementation V  function optimum Swarm intelligence intoduction Partical swarm optimization introduction I  basics Partical swarm optimization introduction II  the algorithm Particle swarm optimization implementation I  particle Particle swarm optimization implementation II  initialize Particle swarm optimization implementation III  the algorithm Particle swarm optimization implementation IV  testing

MINIMAX ALGORITHM  GAME ENGINESGame trees introduction Minimax algorithm introduction  basics Minimax algorithm introduction  the algorithm Minimax algorithm introduction  relation with tictactoe Alphabeta pruning introduction Alphabeta pruning example Chess problem

BUILDING TICTACTOEAbout the game Cell Constants and Player Game implementation I Game implementation II Board implementation I Board implementationj II  isWinning() Board implementation III Minimax algorithm Running tictactoe

INTERVIEW: SINGAPOREAN EXPERTBackground of Expert Information and Communication Technology in Singapore