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  1. Courses
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  3. GenAI for Customer Service Representatives

GenAI for Customer Service Representatives

This course will illuminate how GenAI can revolutionize customer service by enhancing response times, personalizing interactions, and analyzing large volumes of feedback efficiently.

Reza Moradinezhad
Soheil Haddadi
Soheil HaddadiReza Moradinezhad
Data Science | intermediate | 2 hours 30 minutes |   Published: Oct 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
98.4%RECOMMEND*

This course includes:

  • 2 hours and 30 minutes of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

"GenAI for Customer Service Representative" is an introductory course designed to equip customer service professionals with the knowledge and tools of Generative AI (GenAI) to enhance their service delivery. This course demystifies GenAI, illustrating its potential to transform how customer service is managed, from improving response times and personalizing interactions to efficiently analyzing large volumes of feedback. 

Participants will gain a comprehensive understanding of the fundamentals of GenAI and its practical applications in real-world customer service scenarios. The curriculum covers a range of topics, including key GenAI tools, their capabilities, and ethical considerations, ensuring that learners can harness these technologies responsibly. 

The course aims to build a strong foundational understanding of GenAI, enabling customer service representatives to explore innovative ways to apply these technologies in their daily tasks. By the end of the course, learners will be adept at using GenAI to enhance service efficiency, personalization, and overall customer satisfaction, paving the way for advanced studies or immediate application in their professional roles. 

Skills You Will Gain

Integration
Ethical AI
Productivity
Innovation

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

  • Understand what Generative AI (GenAI) is and its potential in customer service.
  • Examine real-world applications of GenAI for streamlining service workflows and driving innovation.
  • Compare the risks, challenges, and ethical implications of using GenAI in customer service.

Prerequisites

Participants should have a basic understanding of customer service processes and tools. While a deep technical background is not required, a curiosity and willingness to explore new technologies will be beneficial. This course is designed for those open to integrating GenAI tools into their customer service workflows.
 

Who Should Attend

This course is tailored for customer service representatives eager to leverage GenAI technologies to enhance their daily operations. It is also suitable for customer service managers aiming to integrate GenAI into their strategic initiatives, and IT professionals or technical support staff interested in the technological aspects of GenAI for seamless implementation and innovation.
 

Curriculum

Instructors

Frequently Asked Questions

How much do the courses at Starweaver cost?

We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.

Do you offer any certifications upon completion of a course at Starweaver?

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

Does Starweaver offer any free courses or trials?

No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.

Are Starweaver's courses designed for beginners or advanced students?

Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.

What payment options are available for Starweaver courses?

We accept various payment methods such as major credit cards, PayPal, wire transfer, and company purchase orders. For more information related to payments contact customer support.

Do you offer refunds?

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.
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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1Module 1: GenAI for Customer Service Representatives

Segment 01 - Introduction to GenAI for Customer Service Representatives

Segment 02 - Glossary for GenAI and Customer Service Representatives 1

Segment 03 - History & Background for GenAI and Customer Service Representatives

Segment 04 - Demo for Resolving Customer Issues with Copilot of Microsoft Dynamics 365

Segment 05 - Demo for Enabling Intelligent Self-Service with Microsoft Dynamics 365 1

Segment 06 - Demo for Optimizing Service with Analytics in Microsoft Dynamics 365 1

Segment 07 - Remediating Risks and Ethical Concerns

Segment 08 -Demo for Using Microsoft Dynamics 365 for Better Customer Service

Segment 09 - Demo for Improving Service Operations with Microsoft Dynamics 365 1

Segment 10 - Practice Project for Customer Service Representatives

Segment 11 - Closing Thoughts: What’s Next