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MOOC
This data analytics course takes an interdisciplinary approach to demonstrate the data analytics process in the context of accounting and finance. The growing volume of both structured and unstructured data has pushed forward a more data-driven form of decision-making in accounting and finance. In order to keep up with the Big Data era advancements, accountants and finance professionals need to have a data analyst mindset to excel in their jobs. This course will illustrate different concepts of accounting and finance with the application of data analytics. It will not only help the learners to develop their skills to ask the right questions but also teach them how to master the data and use different tools like Excel and Tableau to analyze the data. In the end, the learners will be able to interpret the results and make their decisions effectively.
This course will use a simple framework that helps the learners to develop an analytical mindset. This framework (QDAR) has four major components:
1. Ask the right Q uestions to address an issue in accounting or finance contexts.
2. Understand the different data types and how to retrieve and clean D ata.
3. Conduct different data A nalyses to answer the questions
4. Communicate the R esults to the decision-makers using graphs, visualizations and reports.
The whole course will cover different aspects of the framework in conjunction with different types of analyses. There will be additional datasets for the verified learners through which they can practice what they have learned during the course.
- Subjects:
- Accounting and Finance
- Keywords:
- Accounting -- Data processing Finance -- Data processing
- Resource Type:
- MOOC
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MOOC
Aviation is essential for global business as it supports worldwide travelling and cargo transportation. Before COVID-19, the economic benefits generated by the industry across countries showed a growing trend. This course is aimed to provide learners with a broad understanding of airport services in different phases in terms of design and engineering. Learners will receive basic knowledge of how an airport operates. Key topics include the future perspective of air traffic control, air traffic flow management, airport management, facility planning, airport terminal design for the post-pandemic world and ground services.
- Subjects:
- Aeronautical and Aviation Engineering and Logistics
- Keywords:
- Airports -- Management Aeronautics Commercial -- Management Airlines -- Management
- Resource Type:
- MOOC
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MOOC
“Easy Vlogging – making Interactive Self-introduction Videos” is an online course for people to learn, in self-paced format, how to create effective job interview videos for either academic pursuit or career needs. With the contents learned from this course, it helps learners apply for dream jobs easier and more successfully, producing self-introduction videos with good visual quality, superior self-expression and professional presence.
The purpose of this course is to offer students with:
• An overview of digital video production, including script writing and other preparation works;
• An introduction on various video production techniques, including the use of camera, lighting and video editing techniques; and
• An understanding on the role of digital self-introduction video for interview purposes.
- Keywords:
- Video recordings -- Production direction
- Resource Type:
- MOOC
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Others
Learn more about finding a journal for publication, open access, predatory journals, your copyright as an author, social media in academics, enhancing your visbility, networking, tools for sharing and co-writing or research data management.
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Video
Convex Matrix Optimization (MOP) arises in a wide variety of applications. The last three decades have seen dramatic advances in the theory and practice of matrix optimization because of its extremely powerful modeling capability. In particular, semidefinite programming (SP) and its generalizations have been widely used to model problems in applications such as combinatorial and polynomial optimization, covariance matrix estimation, matrix completion and sensor network localization. The first part of the talk will describe the primal-dual interior-point methods (IPMs) implemented in SDPT3 for solving medium scale SP, followed by inexact IPMs (with linear systems solved by iterative solvers) for large scale SDP and discussions on their inherent limitations. The second part will present algorithmic advances for solving large scale SDP based on the proximal-point or augmented Lagrangian framework In particular, we describe the design and implementation of an augmented Lagrangian based method (called SDPNAL+) for solving SDP problems with large number of linear constraints. The last part of the talk will focus on recent advances on using a combination of local search methods and convex lifting to solve low-rank factorization models of SP problems.
Event date: 11/10/2022
Speaker: Prof. Kim-Chuan Toh (National University of Singapore)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Semidefinite programming
- Resource Type:
- Video
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Video
We introduce a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method preserves the convergence of the second-order method while using only Hessian-vector products in two directions. Moreover; the computational overhead remains comparable to the first-order such as the gradient descent method. We show that the method has a local super-linear convergence and a global convergence rate of 0(∈-3/2) to satisfy the first-order and second-order conditions under a commonly used approximated Hessian assumption. We further show that this assumption can be removed if we perform one step of the Krylov subspace method at the end of the algorithm, which makes DRSOM the first first-order-type algorithm to achieve this complexity bound. The applicability and performance of DRSOM are exhibited by various computational experiments in logistic regression, L2-Lp minimization, sensor network localization, neural network training, and policy optimization in reinforcement learning. For neural networks, our preliminary implementation seems to gain computational advantages in terms of training accuracy and iteration complexity over state-of-the-art first-order methods including SGD and ADAM. For policy optimization, our experiments show that DRSOM compares favorably with popular policy gradient methods in terms of the effectiveness and robustness.
Event date: 19/09/2022
Speaker: Prof. Yinyu Ye (Stanford University)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Nonconvex programming Mathematical optimization
- Resource Type:
- Video
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Video
Academic advising has great potential in helping students learn to learn. In this activity, we will walk through the basic concepts of L2L, and provide tips on how to support students' L2L development through academic advising. This activity is designed particularly for academic advisors but everyone is welcome to join. It will be recorded and the recording will be uploaded to the Learning to Learn Website for sharing.
Event Date: 19/8/2022
Facilitator(s): Kevinia Cheung, Kenneth Tam
- Subjects:
- Lesson Design and Student Engagement
- Keywords:
- Learning
- Resource Type:
- Video
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Video
The QS Stars Reimagine Education Awards, backed by the Wharton School, describes itself as "The global awards for innovative higher education pedagogies enhancing learning and employability”. Over the past few years PolyU has enjoyed much success at these awards with multiple shortlisted and winning entries. In this workshop, recent PolyU winners will share their insights on converting great educational innovations into award-winning applications.
Event Date: 5/8/2022
Facilitator(s): Daniel Shek, Fridolin Ting, Johnny Yuen, Kai Pan Mark
- Subjects:
- Good Practices
- Keywords:
- Educational innovations
- Resource Type:
- Video
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Video
This EDC and ITS collaborative workshop series consists of two hybrid workshops about how to develop rubrics both theoretically and technically. Demonstration, discussion activities and hands-on exercises are designed for the participants to enrich their learning experience. Topics include: Introduction to rubrics Rubric policy Types of rubrics Developing rubrics and evaluating their quality How to set up rubrics in Learn@Polyu and Turnitin How to grade your students' work using rubrics in Learn@Polyu and Turnitin
Event Date: 27/7/2022
Facilitator(s): Eric Ng, Jamie Lee, Roy Kam
- Subjects:
- Assessment & Feedback
- Keywords:
- Educational tests measurements College students -- Evaluation
- Resource Type:
- Video
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Video
Join us in this online showcase that looks at assessment solutions that leverage technology to help you assess student learning outcomes. We will consider examples from PolyU and HKBU that move beyond large-hall exams and their online invigilated equivalents to offer a more holistic solution.
Event Date: 7/7/2022
Facilitator(s): Darren Harbutt, Wallace Lai, Bruce Li, Theresa Kwong
- Subjects:
- Assessment & Feedback
- Keywords:
- Educational tests measurements Web-based instruction
- Resource Type:
- Video