How to use network models to address the main challenges of our Generation?
Course Overview:
The last several years have witnessed major advancements in the development of sensor technologies and data measuring instruments with the goal of collecting various types of data in to be used in various application domains. Although these developments are certainly welcomed, so much left to be done to take full advantage of the data gathered by such technologies. The critical missing component is the lack of impactful data analytics. How to leverage all available raw data to advance scientific domains and industry applications can be considered one of the most exciting scientific challenges of our generation. Such challenges exist in many critical medical, business, engineering, and education applications. In this workshop, we familiarize the participants with the basic concepts of data analytics and introduce them to new data analytics tools using network models. The workshop illustrates how to effectively utilize various types of networks and population-based approaches to analyze complex data and reveal useful relationships in several application domains. We also utilize graph mechanisms to zoom in and out of network models and extract different types of information at various granularity levels. This approach paves the way towards a new direction to develop decision support systems that lead to new discoveries in healthcare, engineering, education, and business applications.
Objectives:
The course objectives and student learning outcomes can be summarized as follow:
- Introduce the participants to key concepts associate with data and the value of having data-driven cultures in businesses and organizations.
- Provide an in-depth understanding of the basic concepts of data analytics from the foundational as well as the practical perspectives.
- Introduce the basic concepts of network modeling and population analysis and how they can be used to model complex data and solve big data problems.
- Explore the advantages of using data analytics in practical applications and how to define critical domain/business questions that enhance organizational value using data and data analytics.
- Use a combination of case studies and individual projects to give the workshop participants the opportunity to grasp the main concepts of data analytics and apply them to address practical questions related to their businesses or organizations.
Outcome:
After completing the six modules of the workshop, participants will be able to:
- Have a good overall understanding of the main topics related to data and the wide-range concepts associated of data analytics.
- Apply ethical principles in the collection and use of data and demonstrate an ability to extract, clean, reshape, and prepare data for analysis.
- Learn how to use networks and graphs to model complex data and extract relevant knowledge from available data to support their organizations.
- Develop clear understanding of how to formulate data-related business questions and apply various analytical tools to determine the most appropriate answer such questions.
- Develop appreciation for data-driven cultures and acquire the basic knowledge for using data-driven decision-making practices.
- Apply tools of data analysis to communicate results through reports and/or presentations.
Course Content:
Unit 1: Introduction to data Literacy: General introduction to key concepts related to data along with the associated classifications and variations.
Unit 2: Introduction to data analytics: Overview of key concepts related to data and analytics with the focus on the impact of adopting data-driven cultures in organizations.
Unit 3: Challenges and opportunities in data analytics: A focus on major challenges facing data analytics and how to address them including data ethics and Privacy; robustness and reproducibility, and overall credibility of data analytics.
Unit 4: Data analytics tools using network models: Introduction to network modeling and how graphs/networks can be used to model complex data and provide a powerful and flexible tool for data analytics.
Unit 5: Case studies to illustrate data analytics tools: how to formulate data-related business questions and how to employ network models and population-based approaches to effectively answer business questions and analyze complex data in several application domains.
Unit 6: Workshop project: With each participant proposing his/her data and application domain, the project focused on how the introduced tools can help every participant extract useful knowledge from the input raw data.
Who can attend?
We are witnessing a revolution in the ability to collect data with various types, formats, technologies, and application domains. In addition, the availability of all sorts of data in public domains makes it possible to take advantage not only of the data locally collected, but also from data collected from groups all over the world. The critical question is how to maximize the benefits of the available data, and how to extract useful knowledge to help advance the mission of various organizations. Hence, it is hard to imagine any business, institute or organization that would not benefit from learning about data analytics. In particular, the following groups would significantly benefit from the proposed data analytics workshop:
- IT professionals including data analysts, data scientists, database engineers, and software developers.
- Managers and decision makers in various organizations with access to data that can be used to enhance productivity, practices, or profits in their organizations.
- Members of development groups or research teams in data-rich organizations such as hospitals, health-care institutions, media companies, and transportation groups.
For inquiries and corporate deals, please send us an email on pda@ngu.edu.eg