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  1. Courses
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  3. Understanding LLMs and Their Business Applications

Understanding LLMs and Their Business Applications

This course offers a deep dive into Large Language Models (LLMs), exploring their capabilities, applications, challenges, and future potential in the business landscape.

Soheil Haddadi
Reza Moradinezhad
Reza MoradinezhadSoheil Haddadi
Business | core | 1 hour 15 minutes |   Published: Apr 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
92.6%RECOMMEND*

This course includes:

  • 75 minutes of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 
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.   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 have 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, Open-Sources models, and APIs.

Skills You Will Gain

Customer Support Chatbots
Data Analytics
Generative AI
Large Language Models (LLMs)
Open-Sources models

Learning Outcomes (At the end of this program you will be able to)

  • Evaluate the opportunity of LLMs and utilize their capabilities for their business. 
  • Review the opportunities provided by current LLMs, as well as current limitations in certain business applications. 
  • Develop a roadmap to design and implement new business ideas using LLMs. 
  • Analyze current trends of LLMs and work to “cut through the noise.

Prerequisites

Learners should ideally possess the following prerequisite skills:

  • Basic knowledge about business and startups
  • Curiosity for the field of AI
  • General interest about machine learning
  • AI related technologies

Who Should Attend

Office Professionals, Consultants, Students, Small Business Owners, Automation Enthusiasts 

Curriculum

Instructors

Frequently Asked Questions

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Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.

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Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.

*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 0 - The Significance of Large Language Models (LLMs): Understanding Key Concepts
2Module 1 - Current Landscape of LLM Applications
3Module 2 - Harnessing LLMs: Opportunities, Challenges and Practical Techniques
4Module 3 - Takeaways: Implementing LLMs in Your Own Business
Reza Moradinezhad

Reza Moradinezhad

Reza is a passionate advocate for fostering effective and trustworthy collaboration between humans and artificial intelligence, with a strong commitment to advancing the ethical use of Generative AI. Holding a PhD in Computer Science from Drexel University, his research focuses on enhancing human trust in Embodied Virtual Agents (EVAs). Through collaborations with prestigious institutions such as MIT Media Lab, CMU HCII, Harvard University, and UCSD, Reza has contributed impactful research published in leading journals like Springer Nature, ACM CHI, and ACM C&C. His work has gained recognition from the academic community, earning him accolades such as the Outstanding Reviewer award by ACM ICMI 2019 and ACM CHI 2021. His research has also been featured in media outlets including The Next Web, TechXplore, and CBS News.

As an Assistant Teaching Professor at Drexel University's College of Computing and Informatics, Reza has shaped the minds of both undergraduate and graduate students, guiding them through complex topics such as Artificial Intelligence, Software Engineering, and Computer Graphics. His dedication to education extends beyond teaching, mentoring research projects on topics ranging from mind-wandering in the human brain to the effectiveness of creativity support tools in fostering innovation.

In addition to his academic work, Reza served as an AI Scientist at TulipAI, where he focused on ensuring the ethical and responsible application of Generative AI in media creation. He is driven by the vision of making AI more trustworthy for humanity and believes in designing transparent, fair, and responsible interactions with AI systems. Through his work, Reza aims to harness the full potential of AI while adhering to ethical principles and promoting responsible innovation.

With a proven track record in academic research, collaborative projects, and a deep passion for ethical AI development, Reza is committed to making significant contributions to the evolving field of Human-AI interaction.

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Soheil Haddadi

Soheil Haddadi

Soheil is a Postdoctoral Researcher with a strong academic foundation in Control and Automation Systems Engineering, specializing in Artificial Intelligence. His expertise spans across Data Science, Machine Learning, LLMs, Deep Learning, Natural Language Processing (NLP), and Robotics. Soheil has successfully applied his skills in both industry and research environments, contributing to advancements in AI.

Currently, as a Postdoctoral Researcher, Soheil is dedicated to pushing the boundaries of AI. His technical proficiency in Python, SQL, TensorFlow, and Keras, combined with a deep understanding of AI methodologies, has enabled him to deliver innovative solutions and insights. His prior work includes leading diverse projects such as sales forecasting using time series and LSTM neural networks, autonomous indoor navigation for quadrotors using ORB-SLAM, and deep learning-based credit scoring in the banking sector.

Soheil’s experience in data analysis and visualization further enhances his comprehensive understanding of how AI can address complex problems and create tangible value. His contributions are a testament to his dedication to advancing AI research and its real-world applications.

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Segment 06 - Can LLMs do the Programming for You?

Segment 07 - Prompt Engineering for Defeating Hallucination

Segment 08 - Can LLMs Automate Marketing Content for you?

Segment 09 - Fast Track of the AI Landscape

Segment 01 - Introduction & Meet the Instructor

Segment 02 - Defining Large Language Models (LLMs)

Segment 03 - Evolution of LLMs Over the Last Decade

Segment 04 - The Key Concepts in LLM Technology: Token and Embedding (Part 1)

Segment 05 - The Key Concepts in LLM Technology: Transformers and Self-Attention (Part 2)

Segment 10 - Opportunities with LLMs

Segment 11 - Fast Forward: 10 Challenges with LLMs (Part 1)

Segment 12 - Fast Forward: 10 Challenges with LLMs (Part 2)

Segment 13 - Solving: Is Prompt Engineering All That You Need?

Segment 14 - Build a roadmap to implement LLMs in your business

Segment 15 - Continuous Learning and Exploration of LLMs

Segment 16 - Recap of Key Concepts and Insights for understanding LLMs

Segment 17 - Opportunities and Threats: The Future of LLM