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  1. Courses
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  3. Matlab and Simulink Basics

Matlab and Simulink Basics

This course provides a comprehensive introduction to Matlab and Simulink, focusing on foundational aspects and practical applications, for those looking to enhance their skills in engineering, science, and research.

Karlis Zars
Karlis Zars
Data Science | core | 4 hours |   Published: Jul 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
96.9%RECOMMEND*

This course includes:

  • 4 hours of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

This course offers a comprehensive introduction to Matlab and Simulink, focusing on their foundational aspects and practical applications. It's tailored for individuals seeking to enhance their skills in these powerful tools for engineering, science, and research.  The course is designed to transition from basic concepts to specific applications, emphasizing real-world relevance and skill-building. It will cover Matlab's programming environment and Simulink's modeling capabilities, aiming to equip participants with practical skills for their academic or professional endeavors. 

Skills You Will Gain

Data Analysis
Engineering Tools
Matlab
Model Simulation
Simulink

Learning Outcomes (At the end of this program you will be able to)

  • Identify basic features and capabilities of Matlab and Simulink. 
  • Apply Matlab and Simulink tools to solve simple computational problems. 
  • Analyze data using Matlab’s advanced functions. 
  • Design and simulate models in Simulink for various applications. 

Prerequisites

Participants should have a basic understanding of programming concepts and fundamental knowledge of mathematics and engineering principles.

 

 

Who Should Attend

Engineers, Scientists, Researchers, and Students looking to build a Solid Foundation in Computational Problem-Solving and Simulation using Matlab and Simulink.

 

 

Curriculum

Instructors

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
Karlis Zars

Karlis Zars

Karlis is a dedicated professional committed to shaping the next generation of software developers. With over seven years of experience, he serves as a JAVA Trainer at Software Development Academy, where he mentors aspiring developers and equips them with the skills needed to thrive in the fast-paced tech industry.

Beyond the classroom, Karlis is deeply involved in cutting-edge research as a PhD student in Computer Science at the University of Latvia. His research focuses on artificial intelligence and machine learning, exploring innovative applications that drive industry advancements.

Karlis began his journey in technology with hands-on experience as a Robotic Process Automation Developer at Rimi Baltic Group, where he designed and implemented automated solutions that transformed business processes. His previous roles as a Developer at ELVA and a Junior Software Developer at D8 Corporation allowed him to hone his expertise in Java, JavaScript, Linux, and Flutter, contributing to his well-rounded understanding of software development.

Throughout his career, Karlis has remained committed to delivering high-quality, user-friendly solutions that address complex challenges. His experience as a System Administrator at Lauku Avīze AS and a Software Tester at Lattelecom helped cultivate a diverse skill set and a keen eye for detail.

Karlis’ academic journey at Latvijas Universitāte, where he is pursuing a Doctor of Philosophy in Computer Science, has further enriched his knowledge and reinforced his commitment to excellence in both academia and industry.

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1Module 1.1: Basics of Matlab
2Module 1.2: Intermediate Matlab Features
3Module 1:3: Data Visualization and Analysis
4Module 2.1: Advanced Data Structures
5Module 2.2: Scientific Computing with Matlab
6Module 2.3: Matlab Programming Best Practices
7Module 3.1: Simulink Fundamentals
8Module 3.2: Building Basic Models in Simulink
9Module 3.3: Simulink for Engineering Applications
10Module 4.1: Combined Applications
11Module 4.2: Real-World Projects
12Module 4.3: Capstone Project and Conclusion

Segment 05 - Data Types and Structures

Segment 06 - Matlab Functions and Scripts

Segment 07 - Control Flow and Logical Operations

Segment 25 - Developing Complex Simulink Models 

Segment 26 - Simulink for Control Systems 

Segment 27 - Using Simulink for Dynamic Systems Simulation

Segment 11 - Introduction to Module 2

Segment 12 - Working with Matrices and Arrays

Segment 13 - Cell Arrays, Tables, and Structures

Segment 14 - File I-O and Data Import-Export

Segment 08 - Introduction to Plotting and Graphs

Segment 09 - Customizing Matlab Plots

Segment 10 - Handling Multidimensional Data

Segment 01 - Introduction and Welcome

Segment 02 - Introduction to Matlab Interface

Segment 03 - Fundamental Matlab Operations

Segment 04 - Basic Matlab Programming Concepts

Segment 15 - Numerical Methods and Algorithms

Segment 16 - Optimization and Computational Techniques

Segment 17- Matlab for Simulation

Segment 28 - Electrical Systems Modeling

Segment 29 - Mechanical Systems Simulation

Segment 30 - Using Simulink in Research

Segment 21 - Introduction to Module 3

Segment 22 - Navigating the Simulink Environment

Segment 23 - Building Basic Models in Simulink

Segment 24 - Simulating Models in Simulink 

Segment 31 - Introduction to Module 4

Segment 32 - Interfacing Matlab with Simulink

Segment 33 - Data Sharing Between Matlab and Simulink

Segment 34 - Project-Based Learning with Matlab and Simulink

Segment 35 - Case Studies in Engineering and Science

Segment 36 - Matlab and Simulink in Industry

Segment 37 - Collaborative Projects Using Matlab and Simulinks

Segment 38 - Planning and Starting Your Capstone Project

Segment 39 - Development and Implementation of the Project

Segment 40 - Presentation of Projects and Course Summary

Segment 41 - Wrap up and key takeaways

Segment 18 - Efficient Code Writing in Matlab

Segment 19 - Debugging and Error Handling

Segment 20 - Integration with Other Programming Languages