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Thuan L. Nguyen

Title: Clinical Associate Professor

Department: ADA - Advanced Data Analytics

College: University of North Texas

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, NOVA Southeastern University, 2016
    Major: Information Systems
    Specialization: Knowledge Management
    Dissertation: Assessing Knowledge Management Values By Using Intellectual Capital to Measure Organizational Performance
  • MS, The University of Texas at Dallas, 2011
    Major: Management Information Systems
  • BS, The University of Texas at Austin, 1995
    Major: Computer Science

Current Scheduled Teaching

ADTA 5750.501Applied Natural Language ProcessingFall 2024 Syllabus
ADTA 5340.400Discovery and Learning with Big DataFall 8W1 2024 Syllabus
ADTA 5340.502Discovery and Learning with Big DataFall 2024 Syllabus
ADTA 4340.501Methods for Discovery and Learning from DataFall 2024 Syllabus
ADTA 5560.411Recurrent Neural Networks for Sequence DataFall 8W2 2024
ADTA 5900.002Special ProblemsFall 2024 Syllabus
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching

ADTA 5550.400Deep Learning with Big DataSpring 8W1 2024 SPOT
ADTA 5340.413Discovery and Learning with Big DataSpring 8W2 2024 SPOT
ADTA 5760.501Natural Language Processing with Artificial Neural NetworksSpring 2024 SPOT
ADTA 5560.501Recurrent Neural Networks for Sequence DataSpring 2024 SPOT
ADTA 5750.501Applied Natural Language ProcessingFall 2023 SPOT
ADTA 5550.100Deep Learning with Big DataFall 8W1 2023 SPOT
ADTA 5340.501Discovery and Learning with Big DataFall 2023 SPOT
ADTA 5560.110Recurrent Neural Networks for Sequence DataFall 8W2 2023 SPOT
ADTA 5750.001Applied Natural Language ProcessingSpring 2023 SPOT
ADTA 5550.110Deep Learning with Big DataSpring 8W2 2023 SPOT
ADTA 5560.100Recurrent Neural Networks for Sequence DataSpring 8W1 2023 SPOT
ADTA 5560.501Recurrent Neural Networks for Sequence DataSpring 2023 SPOT
ADTA 5240B.001Data Storing and RetrievingFall 4W3 2022
ADTA 5550.110Deep Learning with Big DataFall 8W2 2022 SPOT
ADTA 5550.501Deep Learning with Big DataFall 2022 SPOT
ADTA 5560.100Recurrent Neural Networks for Sequence DataFall 8W1 2022 SPOT
ADTA 5550.110Deep Learning with Big DataSummer 8W2 2022 SPOT
ADTA 5550.110Deep Learning with Big DataSpring 8W2 2022 SPOT
ADTA 5240.501Harvesting, Storing and Retrieving DataSpring 2022 SPOT
IPAC 4240.501Principles of Data Structures, Harvesting and WranglingSpring 2022 Syllabus SPOT
ADTA 5560.100Recurrent Neural Networks for Sequence DataSpring 8W1 2022 SPOT
ADTA 5550.100Deep Learning with Big DataFall 8W2 2021 Syllabus SPOT
ADTA 5550.501Deep Learning with Big DataFall 2021 SPOT
ADTA 5250.001Large Data VisualizationFall 2021 SPOT
ADTA 5560.100Recurrent Neural Networks for Sequence DataFall 8W1 2021 SPOT
ADTA 5560.126Recurrent Neural Networks for Sequence DataFall 8W1 2021 SPOT
ADTA 5550.100Deep Learning with Big DataSummer 8W2 2021 SPOT
ADTA 5550.101Deep Learning with Big DataSummer 8W2 2021 SPOT
IPAC 4240.700Principles of Data Structures, Harvesting and WranglingSummer 8W1 2021 Syllabus SPOT
IPAC 4240.750Principles of Data Structures, Harvesting and WranglingSummer 8W1 2021 Syllabus SPOT
ADTA 5550.001Deep Learning with Big DataSpring 8W2 2021 SPOT
ADTA 5550.100Deep Learning with Big DataSpring 8W2 2021 SPOT
ADTA 5240.001Harvesting, Storing and Retrieving DataSpring 2021 SPOT
ADTA 5240.501Harvesting, Storing and Retrieving DataSpring 2021 SPOT
ADTA 5250.800Large Data VisualizationSpring 3W1 2021 SPOT
ADTA 5250.826Large Data VisualizationSpring 3W1 2021
IPAC 4240.001Principles of Data Structures, Harvesting and WranglingSpring 2021 Syllabus SPOT
ADTA 5560.100Recurrent Neural Networks for Sequence DataSpring 8W1 2021 SPOT
ADTA 5560.126Recurrent Neural Networks for Sequence DataSpring 8W1 2021 SPOT
ADTA 5550.100Deep Learning with Big DataFall 8W1 2020 SPOT
ADTA 5550.501Deep Learning with Big DataFall 2020 SPOT
ADTA 5340.501Discovery and Learning with Big DataFall 2020 SPOT
CSCE 5215.501Machine LearningFall 2020 SPOT
ADTA 5550.100Deep Learning with Big DataSummer 8W2 2020 SPOT
ADTA 5550.126Deep Learning with Big DataSummer 8W2 2020 SPOT
ADTA 5550.080Deep Learning with Big DataSpring 8W2 2020
ADTA 5550.086Deep Learning with Big DataSpring 8W2 2020
ADTA 5550.100Deep Learning with Big DataSpring 8W2 2020
ADTA 5340.501Discovery and Learning with Big DataSpring 2020
ADTA 5240.080Harvesting, Storing and Retrieving DataSpring 8W1 2020
ADTA 5240.086Harvesting, Storing and Retrieving DataSpring 8W1 2020
ADTA 5240.100Harvesting, Storing and Retrieving DataSpring 8W1 2020
CSCE 5200.100Information Retrieval and Web SearchSpring 8W1 2020
ADTA 5250.800Large Data VisualizationSpring 3W1 2020
ADTA 5250.880Large Data VisualizationSpring 3W1 2020
ADTA 5250.886Large Data VisualizationSpring 3W1 2020
CSCE 5215.501Machine LearningSpring 2020
ADTA 5900.001Special ProblemsSpring 2020
ADTA 5900.003Special ProblemsSpring 8W2 2020
ADTA 5550.080Deep Learning with Big DataFall 8W2 2019 SPOT
ADTA 5550.100Deep Learning with Big DataFall 8W2 2019 SPOT
ADTA 5340.501Discovery and Learning with Big DataFall 2019 SPOT
ADTA 5240.080Harvesting, Storing and Retrieving DataFall 8W1 2019 SPOT
ADTA 5240.086Harvesting, Storing and Retrieving DataFall 8W1 2019 SPOT
ADTA 5240.100Harvesting, Storing and Retrieving DataFall 8W1 2019 SPOT
ADTA 5240.501Harvesting, Storing and Retrieving DataFall 2019 SPOT
CSCE 5200.080Information Retrieval and Web SearchFall 8W1 2019 SPOT
CSCE 5200.501Information Retrieval and Web SearchFall 2019 SPOT
CSCE 5215.501Machine LearningFall 2019 SPOT
ADTA 5250.080Large Data VisualizationSummer 8W2 2019 SPOT
ADTA 5250.100Large Data VisualizationSummer 8W2 2019 SPOT
CSCE 5320.080Scientific Data VisualizationSummer 8W2 2019 SPOT
ADTA 5900.080Special ProblemsSummer 8W2 2019 SPOT
ADTA 5900.100Special ProblemsSummer 8W2 2019 SPOT
ADTA 5900.126Special ProblemsSummer 8W2 2019 SPOT
ADTA 5340.501Discovery and Learning with Big DataSpring 2019 SPOT
ADTA 5240.080Harvesting, Storing and Retrieving DataSpring 8W1 2019 SPOT
ADTA 5240.100Harvesting, Storing and Retrieving DataSpring 8W1 2019 SPOT
CSCE 5200.100Information Retrieval and Web SearchSpring 2019
ADTA 5250.080Large Data VisualizationSpring 8W1 2019 SPOT
ADTA 5250.100Large Data VisualizationSpring 8W1 2019 SPOT
CSCE 5215.501Machine LearningSpring 2019 SPOT
ADTA 5900.080Special ProblemsSpring 3W1 2019 SPOT
ADTA 5900.100Special ProblemsSpring 3W1 2019 SPOT
ADTA 5900.501Special ProblemsSpring 2019
ADTA 5240.080Harvesting, Storing and Retrieving DataFall 8W1 2018 SPOT
ADTA 5240.100Harvesting, Storing and Retrieving DataFall 8W1 2018 SPOT
ADTA 5240.126Harvesting, Storing and Retrieving DataFall 8W1 2018 SPOT
ADTA 5240.501Harvesting, Storing and Retrieving DataFall 2018 SPOT
ADTA 5250.100Large Data VisualizationFall 8W1 2018 SPOT
ADTA 5250.501Large Data VisualizationFall 2018 SPOT
CSCE 5320.501Scientific Data VisualizationFall 2018 SPOT
INSD 5150.080Large Data VisualizationSummer 8W2 2018 SPOT
INSD 5150.086Large Data VisualizationSummer 8W2 2018 SPOT
INSD 5150.100Large Data VisualizationSummer 8W2 2018 SPOT
INSD 5150.126Large Data VisualizationSummer 8W2 2018 SPOT
CSCE 5320.080Scientific Data VisualizationSummer 8W2 2018 SPOT
INSD 5170.080Discovery and Learning with Big DataSpring 8W2 2018 SPOT
INSD 5170.086Discovery and Learning with Big DataSpring 8W2 2018
INSD 5170.100Discovery and Learning with Big DataSpring 8W2 2018 SPOT
INSD 5170.701Discovery and Learning with Big DataSpring 8W2 2018
INSD 5160.080Harvesting, Storing and Retrieving DataSpring 8W1 2018 SPOT
INSD 5160.100Harvesting, Storing and Retrieving DataSpring 8W1 2018
INSD 5160.701Harvesting, Storing and Retrieving DataSpring 8W1 2018
INSD 5150.086Large Data VisualizationSpring 8W1 2018
INSD 5150.501Large Data VisualizationSpring 2018 SPOT
INSD 5150.701Large Data VisualizationSpring 8W1 2018 SPOT
HLSV 5300.810Information Systems for Healthcare ManagementFall 8W1 2017 SPOT
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Intellectual Contributions

    Conference Proceeding

  • NGUYEN, T.L. (2019). AI: Deep Learning with Artificial Neural Networks. SWDSI.ORG. http://swdsi.org/proceedings/2019/Papers/AB052.PDF
  • Nguyen, T.L. (2019). A Framework for Five Big V's of Big Data and Organizational Culture in Firms. IEEE Proceedings. New York, NY, IEEE. https://ieeexplore.ieee.org/document/8622377
  • Nguyen, T.L. (2018). Teaching Big Data and Machine Learning with Cloud Technology and Python. AMCIS: Americas Conference on Information Systems. https://aisel.aisnet.org/amcis2018/Workshops/Presentations/14/
  • Nguyen, T.L. (2018). A Review of the Theoretical Views of the Firm – The Foundation of Research on the Impact of Knowledge Management and Intellectual Capital on Organizational Performance. 9. SWDSI: Southwest Decision Sciences Institute. http://www.swdsi.org/proceedings/2018/Papers/Papers/PA030.pdf
  • Nguyen, T.L. (2018). Apache Hadoop Ecosystem in Cloud: A Hands-On Workshop. 5. SWDSI: Southwest Decision Sciences Institute. http://www.swdsi.org/proceedings/2018/Papers/Papers/PA017.pdf
  • Nguyen, T.L. (2017). Setting Up a Hadoop System in Cloud - A Lab Activity for Big Data Analytics. 3 (ISSN 2473 - 3857) 22. EDSIGCON (EDSIG Conference on Information Systems and Computing Education). http://proc.iscap.info/2017/cases/4480.pdf
  • Nguyen, T.L. (2017). Evaluate Impacts of Big Data on Organizational Performance: Using Intellectual Capital as a Proxy. (ISBN: 1-60132-448-0) 7. CSREA Press. https://csce.ucmss.com/books/LFS/CSREA2017/ABD6102.pdf

    • Journal Article

  • Nguyen, T. (2021). Set up a Deep Learning Server on Google Cloud Platform. Medium. https://medium.com/p/b4d6823d6cd8
,
Overall
Summative Rating		 Challenge and
Engagement Index		 Response Rate

out of 5
out of 7		 %
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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