Introductory Excel for Scientists and Engineers
4.1 (3 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
22 students enrolled

Introductory Excel for Scientists and Engineers

Solve Differential Equations and Analyse Experimental Results Using Only Simple Spreadsheet Software
4.1 (3 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
22 students enrolled
Created by Philip Baldock
Last updated 12/2019
English
English [Auto]
Current price: $48.99 Original price: $69.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 7 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Differential Equations and applications
  • Numerical Methods for solving differential equations in realistic circumstances
  • Statistics for the Sciences with only simple spreadsheet software
Requirements
  • Good knowledge of basic algebra
  • Some experience with calculus is helpful but not essential
  • Excel or any equivalent spreadsheet software
Description

This course is designed to teach you the broad outlines of modern computational physics using no programming or coding whatsoever. To do this, we'll use the sort of tool almost everyone has installed on their machines: spreadsheet software. Excel, WPS, Libreoffice, any will do. We're going to see that just the capacity to add in formulas and iteratively calculate across your worksheet is enough to achieve spectacular things.

This course is split into two sections, representing the most common uses of computing for students of the sciences and engineering:

Differential Equations

We're going to use modern techniques, especially variants of the finite difference method, to find solutions to differential equations numerically without any expensive or complicated specialist software.

  • Euler's Method

  • Taylor Series

  • Runge-Kutta

  • Higher Order Equations

  • Stiff Equations

  • Predictor-Corrector Methods

While for advanced applications like fluid dynamics this must be extended, these topics provide a good grounding of the fundamentals for all modern methods.

Experimental Statistics

If you have experimental data, interpreting its meaning can be complicated and prone to mistakes that can destroy the validity of your whole experiment! We're going to look at the tools common spreadsheet software has available to us to fit distributions, extract statistical details and test hypotheses.

  • Normal distributions

  • The Mean and Standard Deviation

  • The Weibull Distribution

  • Failure analysis

  • Student's T-Test

Disclaimer:

This course is not a substitute for a degree in applied mathematics or specialist consultancy, by purchasing this course you agree that the course instructor is in no way liable for any disputes, claims, losses, injuries, or damage of any kind that might arise out of or relate to the content of this course or any supporting communications between instructor and student.

Who this course is for:
  • Scientists and Engineers looking to learn the power of computational physics using only simple spreadsheet software
Course content
Expand all 86 lectures 06:47:24
+ Differential Equations on a Computer
12 lectures 01:02:47
Section 01: Euler's Method
00:50
Derivatives on a Computer prt 01
05:41
Derivatives on a Computer prt 02
05:37
Euler's Method
07:43
Euler's Method in Excel - Exercise 1 prt 01
06:05
Euler's Method in Excel - Exercise 1 prt 02
05:29
Euler's Method in Excel - Exercise 2 prt 01
04:02
Euler's Method in Excel - Exercise 2 prt 02
04:43
Euler's Method in Excel - Exercise 2 prt 03
05:21
Euler's Method in Excel - Exercise 2 prt 04
06:39
Euler's Method in Excel - Exercise 2 prt 05
06:40
Euler's Method in Excel - Exercise 2 prt 06
03:57
+ Finite Difference Methods
14 lectures 01:15:47
Section 02: Finite Difference Equations
02:01
Finite Difference Equations prt 02
04:25
Finite Difference Equations prt 03
03:34
FDEs - Exercise 01 prt 01
06:58
FDEs - Exercise 01 prt 02
07:04
FDEs - Exercise 01 prt 03
06:16
FDEs Ex02 - The Logistic Equation prt 01
05:23
FDEs Ex02 - The Logistic Equation prt 02
06:28
FDEs Ex02 - The Logistic Equation prt 03
05:36
FDEs Ex03 - The Relaxation Method prt 01
05:20
FDEs Ex03 - The Relaxation Method prt 03
06:12
FDEs Ex03 - The Relaxation Method prt 04
05:44
+ Advanced Methods - Taylor Series and Convergence Analysis
20 lectures 01:29:02
Section 03: The Trick (for dealing with Higher Order Systems)
01:24
Systems of DEs
09:46
Section 04: Taylor Series
00:57
Taylor Series prt 01
04:20
Taylor Series prt 02
06:45
Taylor Series prt 03
02:28
Taylor Series Ex 01 - Preparing Derivatives prt 01
05:11
Taylor Series Ex 01 - Preparing Derivatives prt 02
04:45
Taylor Series Ex 01 - Preparing Derivatives prt 03
02:33
The Big Mistake
00:33
Taylor Series Ex 01 - Modelling in Excel prt 01
06:39
Taylor Series Ex 01 - Modelling in Excel prt 02
06:02
Taylor Series Ex 01 - Modelling in Excel prt 03
03:46
Taylor Series Ex 01 - Modelling in Excel prt 04
05:13
Taylor Series Ex 01 - Modelling in Excel prt 05
04:46
Convergence Analysis - Checking for Mistakes prt 01
06:23
Convergence Analysis - Checking for Mistakes prt 02
07:01
Convergence Analysis - Checking for Mistakes prt 03
06:22
Convergence Analysis - Checking for Mistakes prt 04
03:22
+ Advanced methods - Runge-Kutta
8 lectures 29:37
Section 06: Runge-Kutta Methods
00:51
Motivation for Runge Kutta
04:19
Runge - Kutta prt 01
04:32
Runge - Kutta prt 02
03:47
Runge-Kutta Ex01 prt 01
05:21
Runge-Kutta Ex01 prt 02
01:59
Runge-Kutta Ex01 - Convergence Analysis - prt 01
04:58
Runge-Kutta Ex01 - Convergence Analysis - prt 02
03:50
+ Stiff Equations
6 lectures 27:02
Section 07: Stiff Equations
01:08
Stiff Equations prt 1
06:32
Implicit Methods Exercise 01 prt 01
04:49
Implicit Methods Exercise 01 prt 02
05:43
Predictor-Corrector Methods
04:31
Predictor-Corrector Methods Exercise 01
04:19
+ Experimental Statistics - The Normal Distribution
9 lectures 46:35
Introduction to Statistical Methods
02:23
Section 08: The Normal Distribution
01:30
Normal Distribution prt 01
05:12
Normal Distribution prt 02
04:53
Normal Distribution prt 03
05:15
Normal Distributions prt 04
06:12
Normal Distribution Ex01 prt 01
06:08
Normal Distribution Ex01 prt 02
07:16
Normal Distribution Ex01 prt 03
07:46
+ The Weibull Distribution
6 lectures 30:41
Section 09: The Weibull Distribution
03:03
Weibull Distribution prt 01
05:16
Weibull Distribution prt 02
05:45
Weibull Distribution Ex01 prt 01
07:04
Weibull Distribution Ex01 prt 02
06:25
Weibull Distribution Ex01 prt 03
03:08
+ Student's T-Test
7 lectures 30:56
Section 10: Student's T-Test
02:44
Student's T-Test prt 01
05:29
Student's T-Test prt 02
07:38
Student's T-Test Exercise - Sourcing Gaussian Distributed Random Numbers
00:42
Student's T-Test Exercise prt 01
06:22
Student's T-Test Exercise prt 02
07:18
Course End
00:43