Building Production-Ready Apps with Large Language Models from Coursera

In the age of artificial intelligence (AI), it is essential to learn how to apply the power of large language models (LLMs) for building various production-ready applications. In this hands-on-course, learners will gain the necessary skills for building and responsibly deploying a conversational AI application.

Following the demo provided in this course, learners will learn how to develop a FAQ chatbot using HuggingFace, Python, and Gradio. Core concepts from applying prompt engineering to extract the most value from LLMs to infrastructure, monitoring, and security considerations for real-world deployment will be covered.

Important ethical considerations such as mitigating bias, ensuring transparency, and maintaining user trust will also be covered to help learners understand the best practices in developing a responsible and ethical AI system.

By the end, learners will have developed familiarity with both the technical and human aspects of building impactful LLM applications. The learners can design, develop, and deploy production-ready applications powered by Large Language Models.

This course is designed for individuals with a basic understanding of programming and application development concepts. It is suitable for developers, data scientists, AI enthusiasts, and anyone interested in using LLMs to build practical applications. you need basic concepts, software tools, and an internet-connected computer.

What's inside

Syllabus

BUILDING PRODUCTION READY APPS WITH LLMs

In this course, learners will learn how to develop a FAQ chatbot using HuggingFace, Python, and Gradio. Core concepts from applying prompt engineering to extract the most value from LLMs, to infrastructure, monitoring and security considerations for real-world deployment will be covered.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops conversational AI using HuggingFace, Python, and Gradio, which are core skills for building natural language applications

Suitable for developers, data scientists, AI enthusiasts, and individuals interested in LLMs, making it accessible to a wide range of learners

Covers important ethical considerations like mitigating bias, ensuring transparency, and maintaining user trust, equipping learners with responsible AI practices

Offers a course designed for individuals with a basic understanding of programming and application development concepts, making it accessible to beginners

Provides a practical approach to building production-ready LLM applications, emphasizing real-world deployment considerations

Taught by Reza Moradinezhad, who has expertise in AI and chatbot development

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 Building Production-Ready Apps with Large Language Models with these activities:

Review Python Programming Concepts

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Ensure you have the necessary programming skills to succeed in this course.

Browse courses on Python

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Review basic Python syntax, data types, and control structures.
Practice solving simple coding problems using Python.

Read "Deep Learning with Python" by François Chollet

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Gain a solid foundation in deep learning concepts and techniques by reading this comprehensive book.

View Deep Learning with Python, Second Edition on Amazon

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Read the book thoroughly, taking notes and highlighting important concepts.
Implement the code examples provided in the book to reinforce your understanding.
Apply the techniques you learn to your own projects.

Participate in Study Groups or Discussion Forums

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Engage with peers to discuss course topics, share insights, and learn from others' perspectives.

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Join or create study groups with fellow students.
Participate in online discussion forums related to the course topics.
Share your knowledge and help others understand course concepts.

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Practice Building Conversational AI Applications

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Reinforce your understanding of building conversational AI applications by practicing the techniques you're learning in the course.

Browse courses on Conversational AI

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Identify a specific use case for a conversational AI application.
Choose an appropriate LLM and language model for your use case.
Design and develop the conversational flow of your application.
Implement your application using the appropriate programming language and tools.
Test and refine your application to ensure it meets the user's needs.

Explore Tutorials on Advanced LLM Techniques

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Expand your knowledge of LLM techniques by exploring tutorials on advanced topics.

Browse courses on Prompt Engineering

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Identify specific LLM techniques you want to learn more about.
Search for and select high-quality tutorials on these techniques.
Follow the tutorials step-by-step and implement the techniques in your own projects.
Experiment with different parameters and settings to optimize your results.

Attend Workshops on LLM Applications

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Gain hands-on experience and learn from experts by attending workshops on LLM applications.

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Research and identify upcoming workshops on LLM applications.
Register for and attend the workshops.
Actively participate in the workshops and ask questions.
Network with other attendees and industry professionals.

Develop a Real-World Conversational AI Project

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Apply your knowledge and skills by developing a real-world conversational AI project.

Browse courses on Conversational AI

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Define the scope and objectives of your project.
Choose an appropriate dataset and train your LLM.
Design and implement the user interface and conversational flow.
Deploy your project and monitor its performance.

Contribute to Open-Source Projects Related to LLM Applications

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Gain practical experience and contribute to the LLM community by participating in open-source projects.

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Identify open-source projects related to LLM applications.
Review the project documentation and codebase.
Identify areas where you can contribute your skills.
Submit pull requests with your proposed changes.

Career center

Learners who complete Building Production-Ready Apps with Large Language Models will develop knowledge and skills that may be useful to these careers:

LLM Engineer

As an LLM Engineer, you will design, develop, and deploy production-ready applications powered by Large Language Models. This course can help you build the skills you need to succeed in this role by teaching you how to use HuggingFace, Python, and Gradio to develop a FAQ chatbot. You will also learn about prompt engineering, infrastructure, monitoring, and security considerations for real-world deployment, which are all essential skills for an LLM Engineer.

See salaries and explore the career path for LLM Engineer

Data Scientist

As a Data Scientist, you will use your skills in programming, mathematics, and statistics to extract insights from data. This course can help you build the skills you need to succeed in this role by teaching you how to apply prompt engineering to extract the most value from LLMs. You will also learn about infrastructure, monitoring, and security considerations for real-world deployment, which are all important considerations for Data Scientists who work with LLMs.

See salaries and explore the career path for Data Scientist

Software Engineer

As a Software Engineer, you will design, develop, and maintain software applications. This course can help you build the skills you need to succeed in this role by teaching you how to use Python and Gradio to develop a FAQ chatbot. You will also learn about infrastructure, monitoring, and security considerations for real-world deployment, which are all essential skills for Software Engineers who work with LLMs.

See salaries and explore the career path for Software Engineer

Product Manager

As a Product Manager, you will be responsible for the development and launch of new products. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for Product Managers who work with LLMs.

See salaries and explore the career path for Product Manager

Machine Learning Engineer

As a Machine Learning Engineer, you will use your skills in machine learning and artificial intelligence to develop and deploy machine learning models. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for Machine Learning Engineers who work with LLMs.

See salaries and explore the career path for Machine Learning Engineer

UX Designer

As a UX Designer, you will design the user experience for software applications. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to develop and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for UX Designers who work with LLMs.

See salaries and explore the career path for UX Designer

Software Architect

As a Software Architect, you will design and develop the architecture of software applications. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for Software Architects who work with LLMs.

See salaries and explore the career path for Software Architect

Product Designer

As a Product Designer, you will design the user experience and user interface for software applications. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for Product Designers who work with LLMs.

See salaries and explore the career path for Product Designer

AI Engineer

As an AI Engineer, you will use your skills in machine learning and artificial intelligence to develop and deploy AI systems. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for AI Engineers who work with LLMs.

See salaries and explore the career path for AI Engineer

CTO

As a CTO, you will be responsible for the technical strategy and vision of an organization. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for CTOs who work with LLMs.

See salaries and explore the career path for CTO

CIO

As a CIO, you will be responsible for the overall IT strategy and vision of an organization. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for CIOs who work with LLMs.

See salaries and explore the career path for CIO

IT Manager

As an IT Manager, you will be responsible for the planning, implementation, and maintenance of an organization's IT systems. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for IT Managers who work with LLMs.

See salaries and explore the career path for IT Manager

AI Researcher

As an AI Researcher, you will conduct research in the field of artificial intelligence. This course can help you build the skills you need to succeed in this role by teaching you how to use LLMs to build and deploy production-ready applications. You will also learn about the ethical considerations of developing and deploying AI systems, which is an important consideration for AI Researchers who work with LLMs.

See salaries and explore the career path for AI Researcher

Data Analyst

As a Data Analyst, you will use your skills in data analysis and visualization to extract insights from data. This course may be useful for you if you want to learn how to use LLMs to build and deploy production-ready applications.

See salaries and explore the career path for Data Analyst

Statistician

As a Statistician, you will use your skills in statistics to collect, analyze, and interpret data. This course may be useful for you if you want to learn how to use LLMs to build and deploy production-ready applications.

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Building Production-Ready Apps with Large Language Models

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