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AI-assisted MATLAB Programming with ChatGPT
This course is part of MATLAB Programming for Engineers and Scientists.
Course Cost
Free course
Intermediate
Skill Level
13 Hours
Self-paced Video lessons
Explore how to leverage ChatGPT as a powerful assistant for MATLAB programming in this comprehensive course. Learn to write, debug, and optimize code more efficiently through hands-on experience using ChatGPT to generate MATLAB programs, analyze data, and solve engineering and scientific problems. The course covers key MATLAB concepts, AI-assisted coding strategies, and best practices for integrating ChatGPT into your development workflow. Designed for both beginners and experienced users, this course enhances MATLAB proficiency while demonstrating the synergy between AI and computational problem-solving. Master prompt engineering techniques specifically tailored for MATLAB programming, including few-shot prompting, component-based prompting, and iterative refinement. Learn how to use ChatGPT as a personalized MATLAB tutor, get code walkthroughs and feedback, and leverage template-based prompting for code generation and debugging. By the end of the course, you'll be able to use ChatGPT effectively to accelerate coding tasks and significantly improve your productivity in MATLAB.
English
What you'll learn
Understand the fundamentals of Large Language Models and ChatGPT
Master prompt engineering techniques for MATLAB programming including few-shot and component-based prompting
Learn to use ChatGPT as a personalized MATLAB tutor for conceptual questions and code feedback
Develop skills in AI-assisted code generation using template-based prompting approaches
Gain expertise in debugging MATLAB code with ChatGPT assistance
Apply iterative refinement strategies to optimize MATLAB programs
Complete hands-on programming assignments to solve real-world engineering problems
Skills you'll gain
This course includes:
458 Minutes PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course provides comprehensive training on leveraging ChatGPT as an AI assistant for MATLAB programming. Students will explore foundational concepts of Large Language Models and ChatGPT before diving into practical prompt engineering techniques for programming. The curriculum covers essential skills including few-shot prompting, component-based prompting, and iterative refinement strategies. Learners will discover how to use ChatGPT as a personalized MATLAB tutor, gaining expertise in asking conceptual questions, receiving code walkthroughs, and obtaining constructive code feedback. The course progresses to advanced topics in code generation and debugging, featuring template-based prompting approaches and comprehensive debugging strategies. Through hands-on programming assignments including Search Radius, Wordle Helper, Two Sums, Movies, Mystery, and Huge Sums problems, participants will develop practical expertise in integrating AI assistance into their MATLAB development workflow.
Introduction
Module 1 · 1 Hours to complete
Prompt Engineering for Programming
Module 2 · 4 Hours to complete
ChatGPT as a MATLAB Tutor
Module 3 · 4 Hours to complete
Code Generation and Debugging
Module 4 · 4 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: MATLAB Programming for Engineers and Scientists
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.8
5,353
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5,02,107
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4
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Dr. Ákos Lédeczi is a leading researcher in wireless sensor networks (WSN) and Model Integrated Computing. His team developed one of the first WSN-based countersniper systems, which has evolved into a soldier-wearable version capable of highly accurate shooter localization, as well as identifying the caliber and weapon type. The most recent iteration of the system is smartphone-based. Additionally, Dr. Lédeczi's work in Model Integrated Computing includes the development of the Web-based Generic Modeling Environment, an open-source, web- and cloud-based toolkit for creating domain-specific visual modeling and program synthesis environments.
4.8
5,353
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5,01,084
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Mike Fitzpatrick is doing research in computer-assisted surgery, image registration, and medical imaging.
Frequently asked Questions
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