simulation, ai, data science

What can relate simulation, artificial intelligence, and data science

intro

Simulation (S) is the art and science of mimicking the operation of a real-world system on computer, which is aimed at capturing complex, dynamic, and stochastic characteristics of the real-world process, where other types of models fall ¹. The model itself is is a simplified representation or description of a complex entity, which applies to human models (they are supposed to be ‘idealised humans’, at least in appearance!), to wooden models of mosquitoes, and to mathematical models of mosquito populations ². And modeling is the creation of model, so that modeling can be described as a static process, while simulation is described as dynamic process ³. It migh be summerized that modeling is the process of creating the model representing a system, while simulation of is the process of using the model by changing inputs and observing the outputs.

Artificial intelligence (AI) is so difficult to define, where one of the reason because there is not any a set definition or one solid concept for intelligence in general, since intelligence is often dependent on context ⁴. One of definition found is that artificial intelligence is the ability of machines to perform certain tasks, which need the intelligence showcased by humans and animals and it allows machines to understand and achieve specific goals, where it includes machine learning via deep learning ⁵. There is also the other definition, which is narrowing AI to software used by computers to mimic aspects of human intelligence ⁶.

There is a multidisciplinary field that combines mathematics, statistics, artificial intelligence, machine learning algorithms, computer engineering, and more to extract meaningful insights for people and their businesses, where these insights help companies understand why or how something is happening and what is likely to happen in the future, allowing companies to prepare for and create hot trends in the market, whose field is known as data science (DS) ⁷. There at least about nine steps in data science process from problem definition, through modeling, until reporting ⁸.

Here S, AI, and DS are segreted contents that are forced to be put in a post.

s

There is course named Simulation and Modelling of Physical System, Undergraduate Program in Physics, Institut Teknologi Bandung, as part of 2019 curriculum with 3 credit hours.

1. Exlain the difference between modeling and simulation.
2. Make flowcharts explaining how the bubble sort algorithm work for
   a. sorting integer numbers in ascending order, and
   b. soriting integer numbers in descending order.
   Both flowcharts should contain shapes representing start (1), input (1), initialization (2+), process (3+), condition (2), flow of process (12+), output (1), and end (1). Connector (1+) can also be used if necessary in making the flowchart easy to understand.
3. Riemann sum or partition-based numerical integration rules for calculating definite integral covers left hand rule, right hand rule, mid point rule, trapezoidal rule, and Simpson rule.
   a. For all rules, draw two partitions as the approximation in calculating area below a cuve.
   b. Write a general formula for all rules, so that their differendes are only in the coefficients.
4. a. What is random numbers and how they can be produced using Python?
   b. What is Monte Carlo integration?
   c. Explain how Monte Carlo method can be used to find value of π.
5. Explain and relate the terms artificial intelligence, machine learning, and data science. Give also the examples for each terms.

ai

A course named Artificial Intelligence is given as part of 2019 curriculum of Master Program in Computational Science, Institut Teknologi Bandung, which is an elective course for 3 credit hours.

• Task for refining document for this course is canceled and the whole tasks are redistributed among team member.

ds

Another course name Data Science is also available as part of 2019 curriculum of an undergraduate program of a university.

notes