Understanding Large Language Models in Business from Coursera

This course offers a deep dive into Large Language Models (LLMs), exploring their capabilities, applications, challenges, and future potential in the business landscape. Through a blend of theoretical insights and practical examples, learners can review and acquire concepts related to LLMs and their transformative impact on various industries.

Today, major organizations use related LLM technologies such as Customer Support Chatbots, Marketing Content Generation, and Software Development tools. The impact of these technologies combined with real-time Data Analytics has transformed a wide range of industries, from airlines, advertising agencies, legal firms, and health care, just to name a few. Overall, Generative AI is changing the landscape faster than ever.

As we dive into the lessons of this course, we will frame our discussions through several cases for marketing, software programming, content creation, and analytics. This course provides a 360° overview of the current abilities of state-of-the-art LLMs for businesses. Moreover, through this course, you will learn to identify some of the trends behind LLMs such as Neural Networks, Transformers, source models, and APIs.

This program is designed for:

1- Entrepreneurs, business executives, and employees in general, will be able to evaluate how LLMs could affect their business.

2- Non-technical participants who can detect areas in which LLMs can improve their productivity.

3- Technical participants who will generate ideas to apply their skills and use LLMs to their advantage.

4- Learners who will have an opportunity to foresee what areas of business are likely to be impacted by LLMs.

Learners should ideally possess the following prerequisite skills: Basic knowledge about business and startups; Curiosity for the field of AI; and General interest in machine learning and AI-related technologies.

What's inside

Syllabus

Understanding LLMs and their Business Application

This course offers a deep dive into Large Language Models (LLMs), exploring their capabilities, applications, challenges, and future potential in the business landscape. Through a blend of theoretical insights and practical examples, learners will be able to review, and acquire concepts related to LLMs and their transformative impact on various industries.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines Large Language Models (LLMs), which are highly relevant to business

Develops foundational knowledge and practical skills in LLMs, which are essential tools for various industries

Covers core concepts, applications, and trends in LLMs, making it suitable for both beginners and those seeking to advance their knowledge

Led by instructors with expertise in LLMs, providing learners with access to cutting-edge knowledge and industry insights

Requires basic business knowledge and interest in AI, making it accessible to a wide range of learners

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 Understanding Large Language Models in Business with these activities:

Review foundational concepts in natural language processing

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Strengthen your understanding of the fundamental principles of NLP, which form the foundation for LLMs.

Browse courses on Natural Language Processing

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Review textbooks or online resources on NLP.
Complete practice exercises on NLP algorithms.
Summarize key concepts in NLP.

Form a study group with other learners

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Collaborate with fellow learners to reinforce concepts, share insights, and motivate each other throughout the course.

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Gather a team of interested learners.
Review the proposed timeframe and ensure everyone is available.
Schedule the first peer session.

Summarize key concepts and insights from course materials

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Regularly review and synthesize course materials to enhance comprehension and retention.

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Review lecture notes and readings.
Identify key concepts and insights.
Create a summary or mind map.
Review and revise summaries regularly.

Six other activities

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Show all nine activities

Read and summarize GPT-3 and Beyond: Generative AI and the Future of Creativity

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Identify the potential benefits and challenges of LLMs in the context of the evolving business landscape.

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Gather a team of interested learners.
Review the proposed timeframe and ensure everyone is available.
Schedule the first peer session.

Complete exercises on using LLMs for content creation

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Gain hands-on experience in applying LLMs to generate engaging and informative content.

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Identify a topic of interest.
Select an LLM tool.
Write a prompt that aligns with your topic.

Practice using LLMs in software development

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Develop proficiency in utilizing LLMs to automate coding tasks and enhance code quality.

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Choose a programming language.
Find a suitable LLM.
Create a coding challenge.

Develop a marketing campaign that leverages LLMs

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Apply the principles of LLM-driven marketing to create a comprehensive and effective campaign.

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Define your target audience.
Set campaign objectives.
Select LLM tools.

Attend industry conferences on LLMs and AI

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Connect with experts and practitioners in the field to gain insights and expand your professional network.

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Research upcoming conferences and events.
Register and prepare for the conference.
Attend sessions and engage in discussions.

Contribute to open-source projects related to LLMs

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

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Identify open-source projects related to LLMs.
Review the project documentation and select a task.
Make a pull request with your contribution.

Career center

Learners who complete Understanding Large Language Models in Business will develop knowledge and skills that may be useful to these careers:

NLP Researcher

An NLP Researcher studies and develops new methods for natural language processing. Understanding Large Language Models is vital for an NLP Researcher as LLMs are a central topic in the field of NLP.

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Content Writer - AI-Generated Content

A Content Writer specializing in AI-Generated Content creates content using AI tools. Understanding Large Language Models is a must for this role, as it provides knowledge on the capabilities and limitations of AI content generation.

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Natural Language Processing Engineer

A Natural Language Processing Engineer develops, deploys, and maintains NLP systems. Understanding Large Language Models is critical for a Natural Language Processing Engineer, as LLMs are widely used in NLP applications.

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Software Engineer - Natural Language Processing

A Software Engineer specializing in Natural Language Processing develops software that can understand and generate human language. Understanding Large Language Models is important for this career as it can provide the theoretical foundation necessary to build NLP systems.

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AI Engineer

An AI Engineer designs and builds AI systems. In this role, knowledge of Large Language Models can be utilized to better understand and integrate natural language capabilities into AI systems.

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AI Architect

An AI Architect designs and implements AI solutions. Understanding Large Language Models can be advantageous because Large Language Models are a key component of AI systems.

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AI Product Owner

An AI Product Owner manages the development and launch of AI products. Understanding Large Language Models can provide a solid foundation for understanding the capabilities and limitations of MLMs in product development.

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Product Manager - AI

A Product Manager specializing in AI manages the development and launch of AI products. Knowledge gained from Understanding Large Language Models can provide valuable foundational knowledge for this role.

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AI Consultant

An AI Consultant advises organizations on the implementation of AI solutions. Understanding Large Language Models can be useful for an AI Consultant as it can provide knowledge necessary to assess and recommend LLM solutions.

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Machine Learning Engineer

A Machine Learning Engineer develops, deploys, and maintains machine learning models. Understanding Large Language Models can help with this, as a foundational knowledge of Machine Learning is necessary.

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Data Scientist

A Data Scientist collects, analyzes, and interprets data. Completing Understanding Large Language Models can be helpful for those seeking to enter this role as it may build foundational knowledge to investigate and leverage data.

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Computational Linguist

A Computational Linguist studies the relationship between language and computation. Understanding Large Language Models may be helpful for this role, as it can provide a foundation in the computational applications of language.

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Business Analyst

A Business Analyst evaluates business processes and makes recommendations for improvements. Understanding Large Language Models might be helpful for a Business Analyst as it may provide insights on how to leverage new technologies to streamline operations.

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Machine Learning Researcher

A Machine Learning Researcher develops new machine learning methods and algorithms. Understanding Large Language Models may be helpful for a Machine Learning Researcher as it can provide insights into the latest advancements in natural language processing.

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Marketing Analyst

A Marketing Analyst researches and analyzes data to develop marketing strategies. Taking Understanding Large Language Models can help provide a foundation for understanding the impact of LLMs on marketing strategies.

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