**Provider**Swayam

**Cost**Free Online Course

**Session**Finished

**Language**English

**Certificate**Paid Certificate Available

**Duration**8 weeks long

## Overview

This course gives a hands-on introduction to computational thinking applied to basic undergraduate physics. A strong emphasis is placed on translating physics problems into a form suitable for analysis on a computer, with visual aids and computer programming tools. The focus here is primarily to develop the cognitive skill of computational thinking in Physics rather than elaborate numerical methods or exhaustive study of Physics. Our approach to problem solving is as follows:

a) Formulate a basic problem that is amenable to full analytical solution.

b) Translate the problem into a form that can be analyzed on a computer, first by visual tools followed by more sophisticated computational tools.

c) Design complementary computational approaches whose results can be subjected to test against the analytical solutions, thus building confidence and making transparent both the methods.

d) Exploit the confidence thus developed to tackle problems that are not amenable to a full analytical solution.

INTENDED AUDIENCE : Nil

PREREQUISITES : Newtonian Mechanics, Modern Physics, Electrostatics.

INDUSTRY SUPPORT : Quantitative Finance and Scientific consulting companies

a) Formulate a basic problem that is amenable to full analytical solution.

b) Translate the problem into a form that can be analyzed on a computer, first by visual tools followed by more sophisticated computational tools.

c) Design complementary computational approaches whose results can be subjected to test against the analytical solutions, thus building confidence and making transparent both the methods.

d) Exploit the confidence thus developed to tackle problems that are not amenable to a full analytical solution.

INTENDED AUDIENCE : Nil

PREREQUISITES : Newtonian Mechanics, Modern Physics, Electrostatics.

INDUSTRY SUPPORT : Quantitative Finance and Scientific consulting companies

## Syllabus

**COURSE LAYOUT**Week 1 : Intro to Computational Thinking, Visual Thinking and Mathematica Week 2 : Dimensional Analysis, non-dimensionalization, scales of a physical problem Week 3 : Data Analysis: Estimation of errors, and curve fitting Week 4 : Periodic motion 1: simple, damped, and anharmonic oscillators Week 5 : Dynamics through numerical methods: Euler, RK methods. Week 6 : Periodic motion 2: forced oscillations, resonance, friction. Week 7 : Intro. to Monte Carlo simulation Week 8 : Intro. to random walks