The lecture presents information about how the Internet works so students studying …
The lecture presents information about how the Internet works so students studying cyber security can better understand how cybercriminals commit their crimes. The lecture provides elemental concepts so students of all disciplines, from computer engineering to criminal justice and law can obtain a basic foundation.
Google Security Princess Parisa Tabriz and Jenny Martin from Symantec introduce the …
Google Security Princess Parisa Tabriz and Jenny Martin from Symantec introduce the most common types of cybercrime, including viruses, malware, DDOS attacks and phishing scams.
DASHlink is a virtual laboratory for scientists and engineers to disseminate results …
DASHlink is a virtual laboratory for scientists and engineers to disseminate results and collaborate on research problems in health management technologies for aeronautics systems. Managed by the Integrated Vehicle Health Management project within NASA's Aviation Safety program, the Web site is designed to be a resource for anyone interested in data mining, IVHM, aeronautics and NASA.
Abstract Training materials. The DATUM for Health training programme covers both generic …
Abstract Training materials. The DATUM for Health training programme covers both generic and discipline-specific issues, focusing on the management of qualitative, unstructured data, and is suitable for students at any stage of their PhD. It aims to provide students with the knowledge to manage their research data at every stage in the data lifecycle, from creation to final storage or destruction. They learn how to use their data more effectively and efficiently, how to store and destroy it securely, and how to make it available to a wider audience to increase its use, value and impact.
A Document Type Definition (DTD) defines the structure and the legal elements …
A Document Type Definition (DTD) defines the structure and the legal elements and attributes of an XML document. A DTD can be declared inside an XML document or in an external file.
Physical movement is one of the most engaging ways to interact with …
Physical movement is one of the most engaging ways to interact with AI systems. Dancing with AI is a week-long workshop curriculum in which students conceptualize, design, build, and reflect on interactive physical-movement-based multimedia experiences. Students will learn to build interactive AI projects using two new Scratch Extension tools developed for this curriculum.
The goal of this curriculum is to engage students with interactive lessons and projects, and to have them think critically about AI and natural interaction. Throughout this course, students will have open-ended discussions on questions such as:
- How do we compare and contrast forms of representation? - How do we interact with other humans vs. how do we interact with AI? - What are forms of bias that can arise from improperly trained machine learning models, and how can we remediate those biases? - What kind of projects can you create with interactive AI that will benefit your community?
These questions will allow students to reflect on their own abilities as consumers and creators of interactive AI, and have them think critically about the ways it can help and harm society.
Short Description: Innocent trends may foreshadow a grimmer future. You may wonder …
Short Description: Innocent trends may foreshadow a grimmer future. You may wonder why the title refers to pleasures. If you have read Huxley's Brave New World, you may understand how pleasures can be motors of control and manipulation, which makes them dangerous.
Long Description: Canceling” and calling out appear as the struggle against the opposite world views. I invite you to look at this cultural phenomenon from an economic perspective that outlines the social stakes of its practice. This book will encourage you to consider the unintended consequences of cancel culture and question its reliability as a tool of activism.
Word Count: 24104
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Python is a general purpose programming language that is useful for writing …
Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be taught in one and a half days (~ 10 hours). They start with some basic information about Python syntax, the Jupyter notebook interface, and move through how to import CSV files, using the pandas package to work with data frames, how to calculate summary information from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from Python.
Data Carpentry lesson from Ecology curriculum to learn how to analyse and …
Data Carpentry lesson from Ecology curriculum to learn how to analyse and visualise ecological data in R. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R.
Python is a general purpose programming language that is useful for writing …
Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about Python syntax, the Jupyter notebook interface, and move through how to import CSV files, using the pandas package to work with data frames, how to calculate summary information from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from Python.
Short Description: Data analytics is a rapidly evolving field. In today's labour …
Short Description: Data analytics is a rapidly evolving field. In today's labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, "a new online course" if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.
Long Description: Data analytics is a rapidly evolving field. In today’s labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, “a new online course” if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.
Word Count: 2054
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Short Description: Data analytics is a rapidly evolving field. In today's labour …
Short Description: Data analytics is a rapidly evolving field. In today's labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, "a new online course" if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.
Long Description: Data analytics is a rapidly evolving field. In today’s labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, “a new online course” if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.
Word Count: 2038
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Beta Version Word Count: 92165 ISBN: 979-8-88895-422-5 (Note: This resource's metadata has …
Beta Version
Word Count: 92165
ISBN: 979-8-88895-422-5
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Data Carpentry's aim is to teach researchers basic concepts, skills, and tools …
Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working more effectively with data. The lessons below were designed for those interested in working with Genomics data in R.
The Biology Semester-long Course was developed and piloted at the University of …
The Biology Semester-long Course was developed and piloted at the University of Florida in Fall 2015. Course materials include readings, lectures, exercises, and assignments that expand on the material presented at workshops focusing on SQL and R.
A part of the data workflow is preparing the data for analysis. …
A part of the data workflow is preparing the data for analysis. Some of this involves data cleaning, where errors in the data are identified and corrected or formatting made consistent. This step must be taken with the same care and attention to reproducibility as the analysis. OpenRefine (formerly Google Refine) is a powerful free and open source tool for working with messy data: cleaning it and transforming it from one format into another. This lesson will teach you to use OpenRefine to effectively clean and format data and automatically track any changes that you make. Many people comment that this tool saves them literally months of work trying to make these edits by hand.
6.263J / 16.37J focuses on the fundamentals of data communication networks. One …
6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.
The A2DataDive assembled representatives from nonprofit organizations, U-M statistics and data sciences …
The A2DataDive assembled representatives from nonprofit organizations, U-M statistics and data sciences departments, and members of the community to collectively address the data analysis and visualization needs for area nonprofits and local organizations. Open.Michigan was one of the organizers of the A2DataDive, and worked with two School of Information graduate students to scope and implement the event. After identifying two organizations who had data needs:ŰÖFocus HopeŰÖand theŰÖAfrican Health OER Network, this joint community/university datadive took place over a weekend in February 2012 in North Quads space 2435, an adaptable space especially suited to collaborative, participatory work. The A2DataDive was a successful proof-of-concept for a joint collaboration between an academic institution and local organizations and businesses, and demonstrated that sharing skills and expertise to address a need is also a great way to help others.
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