Data Science and AI in Psychology is an interactive eTextbook that provides …
Data Science and AI in Psychology is an interactive eTextbook that provides an introduction to data science, big data, and machine learning in psychology. It covers current trends in data science and big data in the field of psychology (Chapter 1), applications of AI in the field of psychology (Chapter 2), the psychology of data visualization (Chapter 3), data ethics (Chapter 4), an introduction to how machines learn (Chapter 5), a hands-on guide for reading and critiquing machine learning research articles that are relevant to psychological topics (Chapters 6 and 7), and an introduction to coding in Python (Chapter 8). This eTextbook also includes an introduction to ChatGPT and tips for using ChatGPT to assist with writing and coding without plagiarizing (Chapters 6 and 8). This is an interactive resource that provides students with opportunities to engage with their peers and develop critical thinking skills through problem-based, active learning.
Word Count: 6664 Included H5P activities: 11 (Note: This resource's metadata has …
Word Count: 6664
Included H5P activities: 11
(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 lesson to learn how to use command-line tools to perform …
Data Carpentry lesson to learn how to use command-line tools to perform quality control, align reads to a reference genome, and identify and visualize between-sample variation. A lot of genomics analysis is done using command-line tools for three reasons: 1) you will often be working with a large number of files, and working through the command-line rather than through a graphical user interface (GUI) allows you to automate repetitive tasks, 2) you will often need more compute power than is available on your personal computer, and connecting to and interacting with remote computers requires a command-line interface, and 3) you will often need to customize your analyses, and command-line tools often enable more customization than the corresponding GUI tools (if in fact a GUI tool even exists). In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these samples. As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.
Cleaning, reshaping, and transforming data for analysis and visualization, with R and …
Cleaning, reshaping, and transforming data for analysis and visualization, with R and the Tidyverse
Word Count: 3515
(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: Database Design - 2nd Edition covers database systems and database …
Short Description: Database Design - 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter.
Long Description: This second edition of Database Design book covers the concepts used in database systems and the database design process. Topics include: The history of databases Characteristics and benefits of databases Data models Data modelling Classification of database management systems Integrity rules and constraints Functional dependencies Normalization Database development process
Word Count: 30650
(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.)
Database Design - 2nd Edition covers database systems and database design concepts. …
Database Design - 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter.
This course addresses information technology fundamentals, including project management and software processes, …
This course addresses information technology fundamentals, including project management and software processes, data modeling, UML, relational databases and SQL. Topics covered include internet technologies, such as XML, web services, and service-oriented architectures. This course provides an introduction to security and presents the fundamentals of telecommunications and includes a project that involves requirements / design, data model, database implementation, website, security and data network. No prior programming experience required.
Database Security is the utmost key part for any type of database, …
Database Security is the utmost key part for any type of database, .for example financial information, personal information, employee information and enterprise information. This book will cover following topics such as creating and altering database user, password profiling, various privileges and virtual private database. All the topics are implemented by using oracle 11g software. Especially for readers this book will give clarity about database security concepts such as Authorization, Authentication and Access control. The practical part using oracle provides how to carry out database security concepts technically for the reader.
This course relies on primary readings from the database community to introduce …
This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.
This course relies on primary readings from the database community to introduce …
This course relies on primary readings from the database community to introduce graduate/undergraduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, transactions, and other more advanced topics. No prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.
Software Carpentry lesson that teaches how to use databases and SQL In …
Software Carpentry lesson that teaches how to use databases and SQL In the late 1920s and early 1930s, William Dyer, Frank Pabodie, and Valentina Roerich led expeditions to the Pole of Inaccessibility in the South Pacific, and then onward to Antarctica. Two years ago, their expeditions were found in a storage locker at Miskatonic University. We have scanned and OCR the data they contain, and we now want to store that information in a way that will make search and analysis easy. Three common options for storage are text files, spreadsheets, and databases. Text files are easiest to create, and work well with version control, but then we would have to build search and analysis tools ourselves. Spreadsheets are good for doing simple analyses, but they don’t handle large or complex data sets well. Databases, however, include powerful tools for search and analysis, and can handle large, complex data sets. These lessons will show how to use a database to explore the expeditions’ data.
A number of publishers and funders, including PLOS, have recently adopted policies …
A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing.
This Lecturer notes explain data warehousing architecture design and how it is …
This Lecturer notes explain data warehousing architecture design and how it is implemented using oracle. The main objective of lecture notes is student can print and use in easier way.
No restrictions on your remixing, redistributing, or making derivative works. Give credit to the author, as required.
Your remixing, redistributing, or making derivatives works comes with some restrictions, including how it is shared.
Your redistributing comes with some restrictions. Do not remix or make derivative works.
Most restrictive license type. Prohibits most uses, sharing, and any changes.
Copyrighted materials, available under Fair Use and the TEACH Act for US-based educators, or other custom arrangements. Go to the resource provider to see their individual restrictions.
