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  1. Courses
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  3. GenAI for Customer Service Teams

GenAI for Customer Service Teams

This course demystifies GenAI, making it accessible for customer service professionals to enhance team coordination, automate tasks, and improve customer interactions.

Reza Moradinezhad
Soheil Haddadi
Soheil HaddadiReza Moradinezhad
Data Science | core | 1 hour |   Published: Oct 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
98.3%RECOMMEND*

This course includes:

  • 1 hour of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online

GenAI for Customer Service Teams" is an introductory course designed to bridge the gap between generative AI (GenAI) technologies and customer service practices. This course demystifies GenAI, making it accessible for customer service professionals to enhance team coordination, automate tasks, and improve customer interactions. Through engaging content and practical applications, learners will gain a solid foundation in how GenAI can revolutionize customer service operations and enhance customer satisfaction. 

Learners will explore GenAI concepts tailored for customer service, including task automation, intelligent scheduling, real-time communication tools, and data privacy. The course covers essential topics such as enhancing teamwork and cross-functional collaboration, applying GenAI for better team coordination and management, and empowering service teams with AI tools. 

The course includes instructional videos, readings, and practical assignments. Key readings focus on customer privacy and data protection, ensuring learners understand compliance with global privacy regulations. Practical assignments and peer reviews provide opportunities for hands-on experience and community feedback.

By the end of this course, learners will be equipped to creatively apply GenAI tools in their customer service workflows, enhancing team performance and driving innovation within their organization. 

Skills You Will Gain

Data Privacy
Cross-functional Collaboration

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

  • Acquire a basic understanding of GenAI and available GenAI tools and strategies for increasing team collaboration and efficiency.
  • Create a working framework for staying ahead of GenAI advancements.
  • Apply GenAI tools practically in real-world customer service scenarios to improve outcomes.

Prerequisites

Learners should have a fundamental understanding of customer service principles and strategies, along with an eagerness to learn and adapt to new technologies. While a deep technical background is not required, an openness to integrating GenAI tools into customer service workflows will be beneficial.
 

Who Should Attend

This course is tailored to customer service team leaders, including Customer Service Managers, Team Leads, and Senior Customer Service Representatives, aiming to enhance leadership skills and drive GenAI adoption. It is also valuable for individuals entering the customer service field with a focus on AI technologies, as well as IT Professionals and Software Engineers interested in cross-disciplinary innovation in customer service.
 

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.
1Module 1: GenAI for Customer Service Teams
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 01 - Introduction to GenAI for Customer Service Teams

Segment 02 - Resources for GenAI for Customer Service Teams

Segment 03 - The GenAI Future-Ready Framework for Customer Service Teams

Segment 04 - Ethical Concerns and Remediating Risks

Segment 05 - Demo for Executing GenAI Strategies for Customer Service with Pecan AI

Segment 06 - Practice Project for Customer Service Teams

Segment 07 - Promoting Cross-Functional Customer Service Collaboration Strategies with GenAI

Segment 08 - GenAI in Project Management

Segment 09 - GenAI for Boosting Creativity & Communication

Segment 10 - Protecting Customer Data Within Customer Service Teams Using GenAI 1

Segment 11 - Closing Thoughts: What’s Next