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Building a Mobile App

by

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Why Build a Mobile App?

EXCLUSIVE

Be one of the first in the world to hold the exclusive dummies endorsed certificate.

FUN & ENRICHING

Learn how to make interactive Android apps in a fun, easy-to-understand way.

PROJECT-BASED

Create two functional apps for Android devices.

HIGH VALUE

Add mobile app development and an internationally recognised course to your portfolio with only one course.

First-of-its-kind Collaboration with

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FUN FACTS

There are more than 250 million For Dummies books in print.

Curriculum

Day 1

Start by learning the features of App Inventor, then use it to make a basic app with multiple screens.

Topics Covered:

  • Programme Introduction

  • Basic Mobile App Tools

  • Project: Make an App About You

Day 2

Use your new skills to create a more complex app that allows you to add, edit and draw on pictures.

Topics Covered:

  • Project: Make a Photo Editing App

Schedule

DECEMBER 2020

CLASS 1: 12 DEC & 13 DEC (FULL)

  • Sat & Sun, 10am - 5pm
    (Lunch break: 1pm - 2pm)
    @ Online

CLASS 2: 28 DEC & 29 DEC

  • Mon & Tue, 10am - 5pm
    (Lunch break: 1pm - 2pm)
    @ Online

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At Only $549, You Will Get:

1 year access to Building a Mobile App ebook

dummies endorsed certificate

Live instruction by expert instructors

Available via Zoom

(Physical classes coming in 2021)

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  • INTRODUCTION
    Introduction What is AI good for?
  • GRAPH-SEARCH ALGORITHMS
    Breadth-first search introduction Breadt-first search implementation Depth-first search introduction Depth-first search implementation I - with stack Depth-first search implementation II - with recursion Enhanced search algorithms introduction Iterative deepening depth-first search (IDDFS) A* search introduction
  • BASIC SEARCH & OPTIMIZATION ALGORITHMS
    Brute-force search introduction Brute-force search example Stochastic search introduction Stochastic search example Hill climbing introduction Hill climbing example
  • META-HEURISTIC OPTIMIZATION METHODS
    Heuristics VS meta-heuristics 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 ENGINES
    Game trees introduction Minimax algorithm introduction - basics Minimax algorithm introduction - the algorithm Minimax algorithm introduction - relation with tic-tac-toe Alpha-beta pruning introduction Alpha-beta pruning example Chess problem
  • BUILDING TIC-TAC-TOE
    About 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 tic-tac-toe
  • INTERVIEW: SINGAPOREAN EXPERT
    Background of Expert Information and Communication Technology in Singapore
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