Prompt Engineering in Python, with GPT, and the OpenAI API from Coursera

Master the art of prompt engineering in Python and unlock the full potential of GPT models and the OpenAI API. This course will teach you how to create, improve, and fine-tune prompts for various tasks, from personal coaching to building chatbots. You'll gain hands-on experience in iterative prompt design, mitigating hallucinations, and extracting structured information with JSON mode.

The course begins with an introduction to prompt engineering fundamentals and explores how GPT models work in practical scenarios. You'll learn to set up your OpenAI API key, implement chain-of-thought prompting, and compare model versions like GPT-3.5 and GPT-4. Through real-world examples, you’ll also tackle advanced topics such as emotion-driven prompts and exponential backoff strategies.

In later modules, you'll build your own Python API chatbot, enhance multi-turn conversations, and use GPT for extracting numerical values and image-based input. Techniques like "prompt hacking" and smart prompting will teach you how to maximize GPT’s performance, even with older models.

This course is ideal for developers, data enthusiasts, and AI professionals seeking to master prompt engineering. Basic Python knowledge is required, and the course is designed for an intermediate difficulty level.

What's inside

Syllabus

Introduction

In this module, we will introduce the course by outlining its structure, goals, and unique value propositions. You will gain an understanding of prompt engineering basics and learn how the course content and instruction remain up-to-date with cutting-edge developments in the field.

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Read about what's good

what should give you pause

and possible dealbreakers

Teaches prompt engineering, which is a crucial skill for developers looking to integrate large language models into applications and workflows

Explores techniques like chain-of-thought prompting and mitigating hallucinations, which are essential for building reliable and trustworthy AI systems

Requires basic Python knowledge, suggesting that learners should already have some programming experience before taking this course

Covers the OpenAI API, which is subject to change, so learners should be prepared to adapt to updates and modifications

Explores prompt hacking and smart prompting, which are useful for maximizing the performance of GPT models, even older ones

Includes a module on multimodal prompting, which explores how GPT models interpret and utilize images to improve the accuracy of model outputs

Reviews summary

Practical prompt engineering with python & api

According to students, this course offers a practical introduction to prompt engineering using Python and the OpenAI API. Learners praise the hands-on examples and clear explanations of essential techniques like chain-of-thought and JSON mode. The content is consistently described as up-to-date and relevant for real-world application, providing a solid foundation in the field. However, some students note that the pace can be inconsistent and that the course lacks depth on some more complex or advanced topics, suggesting it may feel a bit basic for those with prior knowledge seeking a deep dive.

Course content is current and applicable.

"The content is up-to-date..."

"...The content is relevant to current practices."

"The content is current."

"The content is highly relevant and directly applicable."

Excellent for getting started in the field.

"...overall it provided a solid foundation."

"Solid course. It gives a good overview of prompt engineering principles..."

"A good course for getting started with prompt engineering in Python."

"Still, a solid foundation."

"Good foundational course."

"It's a starting point..."

Covers key methods like JSON mode & Chain-of-Thought.

"...covers both fundamental concepts and advanced techniques like chain-of-thought and JSON mode."

"...I liked the focus on mitigating hallucinations and structured data extraction."

"The sections on mitigating hallucinations and using JSON mode were particularly useful for real-world applications."

"...I learned a lot about structuring prompts for better results and using JSON mode for reliable data extraction."

"The sections on chain-of-thought and mitigating hallucinations were very helpful."

Strong focus on hands-on Python & API use.

"This course was exactly what I needed... The Python examples are clear and easy to follow, making the integration with the OpenAI API straightforward."

"Fantastic course! ... Integrating with the API in Python was explained thoroughly."

"Perfect course to get hands-on with prompt engineering using Python and the OpenAI API. The practical examples and coding exercises are the highlight."

"Very practical and well-structured course... Learning to use the OpenAI API with Python was seamless thanks to the clear examples."

"This course cuts straight to the chase and teaches you how to effectively use prompt engineering with the OpenAI API in Python. The practical focus is its main strength."

Some sections rushed, others lacked detail.

"...I found the pace inconsistent. Some sections dragged, while others sped through complex ideas without enough detail."

"The code examples were helpful but sometimes lacked explanation on why certain approaches were taken."

"...sometimes hard to follow without spending extra time debugging."

"The pace felt inconsistent."

Lacks depth on some complex or advanced topics.

"...doesn't go deep enough into complex topics."

"Some more depth on advanced tuning or specific industry use cases would be beneficial."

"It felt a bit like a quick tour rather than a deep dive."

"...for someone with some prior knowledge, it might feel a bit basic in parts."

"I would have liked to see more advanced topics or troubleshooting tips for common issues."

"Found the course a bit too basic in places..."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Prompt Engineering in Python, with GPT, and the OpenAI API with these activities:

Review Python Fundamentals

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Reviewing Python fundamentals will ensure a solid foundation for understanding the Python API interactions within the course.

Browse courses on Python Basics

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Review basic syntax and data structures.
Practice writing simple Python scripts.
Familiarize yourself with Python libraries.

Read 'Python Crash Course'

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Reading 'Python Crash Course' will help solidify your Python skills, which are essential for working with the OpenAI API.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

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Read the first half of the book covering basic Python concepts.
Complete one or two of the projects to practice coding.

Practice Prompt Engineering Exercises

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Practicing prompt engineering exercises will help you internalize the concepts taught in the course and improve your prompt design skills.

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Experiment with different prompt structures for various tasks.
Analyze the outputs and refine your prompts iteratively.
Try to extract structured information from text using prompts.

Four other activities

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Build a Simple Chatbot

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Building a chatbot will allow you to apply the prompt engineering techniques learned in the course in a practical setting.

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Design the chatbot's functionality and user interface.
Implement the chatbot using the OpenAI API and Python.
Test and refine the chatbot's prompts and responses.

Document Your Prompt Engineering Experiments

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Documenting your experiments will help you track your progress and share your findings with others.

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Create a blog or notebook to record your prompt engineering experiments.
Document the prompts you used, the results you obtained, and any insights you gained.
Share your findings with the community.

Read 'Generative AI with Python and TensorFlow 2'

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Reading 'Generative AI with Python and TensorFlow 2' will give you a deeper understanding of the technology behind GPT models.

View Generative AI with Python and TensorFlow 2:... on Amazon

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Read the sections on transformers and language models.
Experiment with building your own generative models.

Contribute to a Prompt Engineering Project

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Contributing to an open-source project will give you valuable experience working with real-world prompt engineering challenges.

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Find an open-source project related to prompt engineering.
Identify a bug or feature that you can contribute to.
Submit a pull request with your changes.

Career center

Learners who complete Prompt Engineering in Python, with GPT, and the OpenAI API will develop knowledge and skills that may be useful to these careers:

Prompt Engineer

As a Prompt Engineer, you're at the forefront of AI, crafting innovative prompts that unlock the full potential of large language models. Your work focuses on designing, testing, and refining prompts to generate desired and accurate outputs for various applications. This course is directly relevant, as it teaches you how to create, improve, and fine-tune prompts using Python, GPT models, and the OpenAI API. The course will help you gain hands-on experience in iterative prompt design, mitigating hallucinations, and extracting structured information, all essential skills for a successful Prompt Engineer. Learning how to implement chain-of-thought prompting, and use techniques like prompt hacking and smart prompting to maximize model performance is also key.

See salaries and explore the career path for Prompt Engineer

Chatbot Developer

A Chatbot Developer specializes in designing and building conversational AI applications. They create chatbots that can interact with users in a natural and helpful way, often automating customer service or providing information. This course is valuable because it teaches you how to build your own Python API chatbot, enhance multi-turn conversations, and implement exponential backoff strategies for robust interactions. You'll learn how to maximize GPT's performance through techniques like prompt hacking and smart prompting, even with older models. The concepts of prompt engineering fundamentals, mitigating hallucinations, and extracting structured information learned in this course are essential for developing effective and engaging chatbots as a Chatbot Developer.

See salaries and explore the career path for Chatbot Developer

AI Trainer

An AI Trainer is responsible for developing and delivering training programs focused on artificial intelligence technologies. They educate individuals and teams on how to effectively use AI tools and techniques. This course provides you with the knowledge and skills to teach others about prompt engineering, GPT models, and the OpenAI API. You'll learn how to create, improve, and fine-tune prompts for various tasks. The course also helps you to build your own Python API chatbot, enhance multi-turn conversations, and extract data using GPT. This experience will directly translate into your ability to train others on how to leverage these technologies effectively.

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AI Developer

An AI Developer builds and implements AI solutions, integrating machine learning models into applications and systems. They work with various AI technologies to create intelligent software and improve existing processes. This course may be useful if you intend to become an AI Developer because it provides you with hands-on experience using Python, GPT models, and the OpenAI API. You'll learn how to build a Python API chatbot, enhance multi-turn conversations, and extract numerical values and image-based input using GPT. Mastering prompt engineering, as taught in this course, helps you to create effective AI solutions. The course may also help you tackle emotion-driven prompts and exponential backoff strategies.

See salaries and explore the career path for AI Developer

Data Analyst

A Data Analyst collects, cleans, and analyzes data to identify trends and insights that can inform business decisions. This course may be useful as it teaches you how to extract numerical values from text data and use JSON mode for structured outcomes. The course provides hands-on experience using Python, GPT models, and the OpenAI API, which may be invaluable for certain data analysis tasks. The course may help you to extract structured data from unstructured sources for analysis.

See salaries and explore the career path for Data Analyst

Natural Language Processing Engineer

A Natural Language Processing Engineer focuses on enabling computers to understand, interpret, and generate human language. Their work involves developing algorithms and models for tasks like sentiment analysis, language translation, and text summarization. This course may be useful because it teaches you how to leverage GPT models and the OpenAI API for various tasks. The course provides practical experience implementing chain-of-thought prompting, mitigating hallucinations, and extracting structured information with JSON mode. As an NLP Engineer this course may help you learn to maximize GPT’s performance, even with older models, through techniques like prompt hacking and smart prompting.

See salaries and explore the career path for Natural Language Processing Engineer

Data Scientist

Data Scientists analyze large datasets to extract meaningful insights and develop data-driven solutions. They use statistical techniques, machine learning algorithms, and programming skills to solve complex business problems. It may be useful to take this course as a Data Scientist because it teaches you how to extract numerical values from text data and use JSON mode for structured outcomes. The course provides hands-on experience using Python, GPT models, and the OpenAI API, which may be invaluable for certain data analysis tasks. In particular, the course may help you with multimodal prompting.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers develop, test, and deploy machine learning models. They often work on large datasets, using programming skills and knowledge of algorithms to create predictive models and improve system performance. This course may be useful if you want to become a Machine Learning Engineer because it teaches you how to create, improve, and fine-tune prompts for various tasks using Python, GPT models, and the OpenAI API. You'll gain experience in iterative prompt design and extracting structured information, which may be relevant in certain machine learning applications. This course may help you learn how to mitigate hallucinations and implement exponential backoff strategies.

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AI Consultant

An AI Consultant advises organizations on how to leverage artificial intelligence to improve their operations, products, and services. They assess client needs, recommend AI solutions, and guide the implementation process. This course may be useful because it provides a practical understanding of prompt engineering and the capabilities of GPT models. The knowledge gained from this course may help provide your clients with effective AI strategies and solutions. As an AI Consultant, you may be able to recommend how to create, improve, and fine-tune prompts for various tasks.

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AI Product Manager

An AI Product Manager guides the strategy, roadmap, and feature definition of AI-powered products. They work closely with engineering, design, and marketing teams to bring innovative AI solutions to market. It may be useful to take this course to see how it provides an understanding of the capabilities and limitations of GPT models and prompt engineering. This understanding may help refine product strategies and make informed decisions about the use of AI in product development. This course may help you to learn how to leverage ChatGPT as a personal coach to support your growth and learning.

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Technical Writer

A Technical Writer creates documentation and guides for technical products and services. They translate complex information into clear, concise, and user-friendly content for various audiences. The skills learned in this course may be useful so that you can document the use of GPT models and the OpenAI API, as well as create tutorials on prompt engineering techniques. This course may help you to explain how to mitigate hallucinations and extract structured information with JSON mode. This course may help provide the knowledge needed to produce high-quality documentation.

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Solutions Architect

A Solutions Architect designs and implements technology solutions for businesses, ensuring they align with business goals and technical requirements. This course may be useful in understanding how to integrate GPT models and prompt engineering techniques into broader technology solutions. It provides insights into building Python API chatbots and extracting structured information, which may be relevant for certain architectural designs. As a solutions architect, you may learn how to maximize GPT’s performance, even with older models, through techniques like prompt hacking and smart prompting.

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Content Creator

A Content Creator develops engaging and informative content for various platforms, such as websites, blogs, and social media. This course may be useful because it provides you with the skills to leverage GPT models and the OpenAI API to generate high-quality content. You'll learn how to fine-tune prompts for various tasks and extract structured information, which may be invaluable for creating compelling content. The course may help you to build prompts that generate effective content.

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Digital Marketing Specialist

A Digital Marketing Specialist develops and executes digital marketing campaigns to promote products or services online. It may be useful to take this course to understand how to leverage GPT models for content creation, ad copywriting, and customer engagement. The skills learned in this course may help create more effective and targeted marketing campaigns. You may also be able to implement chain-of-thought prompting, mitigate hallucinations, and extract structured information with JSON mode.

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Business Analyst

A Business Analyst identifies business needs and determines solutions to business problems. They gather requirements, analyze data, and recommend changes to processes and systems. The concepts learned in this course may be helpful in understanding how AI and GPT models can be applied to solve business challenges. The course may help you to analyze data, extract insights, and recommend AI-driven solutions. In particular, the course may help you to extract numerical values from text data and use JSON mode for structured outcomes.

See salaries and explore the career path for Business Analyst

Prompt Engineering in Python, with GPT, and the OpenAI API

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Practical prompt engineering with python & api

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