EdX

AI Applications and Prompt Engineering (edX)

Offered by edX,
AI Applications and Prompt Engineering (edX)

Learn to create AI applications with prompt engineering in this introductory online course. Go beyond AI basics, and learn technical and practical skills to harness the power of this emerging technology. Some experience with JavaScript, Node.js, and APIs is recommended.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Are you looking to expand your AI application knowledge and create your own application? Enroll in our Intro to AI Applications and Prompt Engineering course to see how you can make AI work for you.
By the end of the course, you will be able to:

  • Articulate key benefits and limitations of generative AI.
  • Understand how to use AI applications and prompt engineering to drive results.
  • Create an AI-powered command line interface application.

To enroll in this course and utilize ChatGPT's API, which is a required part of the course, students must have a credit card to access OpenAI's ChatGPT API. Your credit card will be charged whatever usage amounts you incur by OpenAI to access the ChatGPT API, and this dollar charge is separate from and in addition to the fee paid to enroll in the verified course track.

What you'll learn

  • How to define AI applications, prompt engineering, and machine learning, and how to leverage these tools and knowledge for your own initiatives.
  • How to structure questions or requests in a way that guides an AI application to give the best possible answer.
  • How to leverage LangChain and ChatGPT to create your own application.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Python for Data Science (edX) EdX
University of California, San Diego,UC San DiegoX

Python for Data Science (edX)

Statistics & Data Analysis CS: Programming

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets. In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?

Self Paced
Self-Paced
Programming Python Machine Learning
Details
AI in Practice: Preparing for AI (edX) EdX
Delft University of Technology,DelftX

AI in Practice: Preparing for AI (edX)

Robotics & Computer Vision

Learn to recognize and understand the implications of Artificial Intelligence for organizations, and the importance of compliance and ethics when AI is applied in practice. This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning about the benefits and implications of AI when applied in practical settings.

Self Paced
Self-Paced
Education Artificial Intelligence Organization
Details
CS50's Introduction to Artificial Intelligence with Python (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Artificial Intelligence with Python (edX)

Robotics & Computer Vision

Learn to use machine learning in Python in this introductory course on artificial intelligence. AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.

Self Paced
Self-Paced
Python Artificial Intelligence Machine Learning
Details
PyTorch Basics for Machine Learning (edX) EdX
IBM

PyTorch Basics for Machine Learning (edX)

Statistics & Data Analysis Data Science

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

Self Paced
Self-Paced
ML Machine Learning Linear Regression
Details
Advanced Bayesian Statistics Using R (edX) EdX
University of Canterbury,UCx

Advanced Bayesian Statistics Using R (edX)

Statistics & Data Analysis Data Science

Now that you know the basics of Bayesian inference, dive deeper to explore its richness and flexibility more fully. Let’s take a closer look at modeling latent variables, Bayesian model averaging, generalised linear models, and MCMC methods. Advanced Bayesian Data Analysis Using R is part two of the Bayesian Data Analysis in R professional certificate.

Self Paced
Self-Paced
Calculus Algorithms Machine Learning
Details
Fundamentals of TinyML (edX) EdX
HarvardX,Harvard University

Fundamentals of TinyML (edX)

Statistics & Data Analysis Data Science

Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML. What do you know about TinyML? Tiny Machine Learning (TinyML) is one of the fastest-growing areas of Deep Learning and is rapidly becoming more accessible. This course provides a foundation for you to understand this emerging field.

Self Paced
Self-Paced
Machine Learning Embedded Systems Data Science
Details
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Statistics & Data Analysis Data Science

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Probability Machine Learning Regression
Details
High-Dimensional Data Analysis (edX) EdX
HarvardX,Harvard University

High-Dimensional Data Analysis (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

A focus on several techniques that are widely used in the analysis of high-dimensional data. If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis.

Self Paced
Self-Paced
Machine Learning Clustering Data Analysis
Details
Applications of TinyML (edX) EdX
HarvardX,Harvard University

Applications of TinyML (edX)

Statistics & Data Analysis

Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition. Do you know what happens when you say “OK Google” to a Google device? Is your Google Home always listening? Following on the Foundations of Tiny ML course, Applications of TinyML will give you the opportunity to see tiny machine learning applications in practice. This course features real-world case studies, guided by industry leaders, that examine deployment challenges on tiny or deeply embedded devices.

Self Paced
Self-Paced
Machine Learning Anomaly Detection Tiny Machine Learning (TinyML) Professional Certificate
Details