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  1. Courses
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  3. GenAI for Computer Support Specialists (IT Support)

GenAI for Computer Support Specialists (IT Support)

This course introduces GenAI for IT support, helping participants automate tasks, solve problems, and personalize customer service with practical GenAI applications.

Reza Moradinezhad
Soheil Haddadi
Soheil HaddadiReza Moradinezhad
Data Science | intermediate | 2 hours 15 minutes |   Published: Oct 2024
In partnership with:  Coursera

    Discussions

Overview

1kSTUDENTS*
98.5%RECOMMEND*

This course includes:

  • 2 hours and 10 minutes of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

This course provides an opportunity to understand and utilize Generative AI (GenAI) in problem-solving and customer interactions. Participants will learn how to automate tasks, resolve issues more quickly with AI assistance, and improve customer support with personalized service. The program covers the core functionalities and limitations of GenAI, offering practical applications for troubleshooting and support in real-world IT scenarios. Strategies for integrating GenAI into daily routines are also discussed. 

The course also addresses the ethical considerations of GenAI implementation in IT support. Topics include data privacy and security, ensuring transparency and accountability in automated decision-making, and mitigating potential biases in AI algorithms. Participants will learn how to use GenAI tools responsibly and ethically in their professional practice. Through this course, participants will acquire the knowledge and skills needed to effectively use GenAI, enhance problem-solving efficiency, and improve support services. 

Skills You Will Gain

Problem-Solving
Automation
Troubleshooting
Efficiency

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

  • Identify the capabilities of GenAI for basic IT support tasks. 
  • Examine real-world applications of GenAI in IT support scenarios. 
  • Deploy strategies to responsibly integrate GenAI into IT support practices. 

Prerequisites

Participants should be familiar with fundamental IT support concepts, troubleshooting procedures, and customer interaction protocols. Experience with programming languages or low-code platforms like Python or PowerShell is beneficial. Curiosity, an open mindset toward GenAI tools, and eagerness to experiment with GenAI are crucial. While deep technical knowledge isn't necessary, prior IT support experience will help learners understand and apply the GenAI-focused content.
 

Who Should Attend

Our learners include IT leaders, mid-career and senior IT support specialists, aspiring entry-level IT support specialists, and help desk professionals. IT leaders will understand how GenAI drives innovation and efficiency. Mid-career and senior specialists will enhance workflows and problem-solving with GenAI tools. Aspiring specialists will gain in-demand, future-proof skills, while help desk professionals will improve troubleshooting through AI-powered insights.
 

Curriculum

Instructors

Frequently Asked Questions

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*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 Computer Support Specialists (IT Support)
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 Computer Support Specialists (IT Support)

Segment 02 - Glossary for GenAI and Computer Support Specialists (IT Support)

Segment 03 - History & Background for GenAI and Computer Support Specialists (IT Support)

Segment 04 - Demo for Synthetic Dataset Creation and Troubleshoot Process Enhancement with Console.gretel.ai and ChatGPT

Segment 05 - Demo for Creating Batch Files with Gemini

Segment 06 - Demo for Implementing Sentiment Analysis with Perplexity.ai

Segment 07 - Remediating Risks and Ethical Concerns

Segment 08 - Demo for Creating a Synthetic Time-Series Logs Dataset with Console.gretel.ai.

Segment 09 - Demo for Generating Real-Time Alerts for System Anomalies with Console.gretel.ai

Segment 10 - Practice Project for Account Executives

Segment 11 - Closing Thoughts: What’s Next