- Learn about numerical & symbolic computing using MATLAB.
- Enhance your problem-solving skills in programming and building algorithms in MATLAB.
- Implement MATLAB in your work and research.
- Numerical Methods for Mechanical Engineers
- Matlab scripting
- Create and manipulate Matrices which are the key to MATLAB programming.
- Learn how to use MATLAB in some elementary mathematics problems.
- Learn how to use MATLAB to produce 2D & 3D graphs.
- Learn how to build 2D animations in MATLAB.
- Learn how to use MATLAB as a programming language to build your own Algorithms.
- Learn how to import and analyze data to MATLAB.
- Get introduced to the symbolic capabilities of MATLAB.
- Computer programming in general and the MATLAB language in particular.
- S. in mechanical, electrical or civil engineering or relevant engineering experience.
- You should have a basic mathematical background
Design, project, mechanical, electrical and R&D engineers, and R&D managers.
After the completion of the program, learners can apply for job roles in:
- Research centers
- Scientific labs
- Educational institutes
- Industrial roles
Learners can also pursue higher education in
- Mechanical Engineering
- Automotive Systems Engineering
- Aerospace Engineering
- Electrical Engineering
- Robotic Technology
- MATLAB syntax and commands
- Methods and ways to use commands in different scenarios
- Manipulation of calculations and comparisons
- Use of arrays.
- Functions (plotting, creating animations, creating figures, and more)
- Manipulator motion using ImageMagick
- Simulation of a 2R robotic arm manipulator
- Creating a movie clip with the spatial motions of a robotic arm
- ‘For’ loop in programming
- Working of the “hold on” command
- Arrays and linspace commands
- Solving piston kinematics equation to calculate volume trace
- PV diagrams for different operating conditions.
- Thermodynamic relationships
- Pressure-volume variations
- Order of the program
- Plots & legends used in the graphs
- Piston kinematics
- Backward difference formula (BDF) and forward difference formula (FDF) methods to solve ODEs
- Real use of differential equations
- How differential equations relate to real-world applications
- Solving differential equations
- ODE solvers, syntax of ODEs, and various supplementary commands
- Polynomials and their best fits
- PolyFit and PolyVal commands
- Calculating errors
- Sum of squares regression (SSR)
- Sum of squares error (SSE)
- Sum of squares total (SST)
- Optimization techniques
- Working on the genetic algorithm
- Genetic algorithm syntax and finding the global maxima
- Stalagmite functions and how it works
- Population size, number of generations, fitness value, and termination of further generations
- Introduction to Programming With MATLAB
- M-Files In MATLAB
- Inputs & Outputs Commands In MATLAB
- fprintf Function In MATLAB
- The If, elseIf, else Statements In MATLAB
- For & While Loops In MATLAB
- Logical Operators (and, or, xor, not) In MATLAB
- Import Spreedsheets from Excel To MATLAB
- Import & Analyze Data from Text Files To MATLAB
- Getting Started with Symbolic Math Toolbox In MATLAB
- Differentiation In MATLAB
- Limits In MATLAB
- Integration In MATLAB
- Solving Algebraic Equations In MATLAB
- Solving Differential Equations In MATLAB
- Solving One Non Linear Equation In MATLAB Using Fzero Function
- On Solving Multiple Non Linear Equations In Matlab Using Fsolve
- Application Multi Level Inverte