Write a document using R markdown, integrate live R code into a literate statistical program, compile R markdown documents using knitr and related tools, and organize
a data analysis so that it is reproducible and accessible to others.
Statement of Accomplishment: Data Science Specialization V - Reproducible Res...Folco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 5th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
Covers exploratory data summarization techniques that are
applied before modeling to inform development of complex
models. Topics include plotting in R, principles of constructing graphics, and common multivariate techniques used for high dimensional data visualization.
Dom Fernandez completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Dom Fernandez completed The Data Scientist's Toolbox course from Johns Hopkins University on Coursera with distinction. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was offered online through Coursera and does not reflect the entire curriculum available to students enrolled at Johns Hopkins University.
This course covers how to use & program in R for effective data analysis. It covers practical issues in statistical computing: programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, & organizing and commenting R code.
Al French successfully completed Coursera's online course "R Programming" from Johns Hopkins University with distinction. The course covered using and programming in R for effective data analysis, including programming in R, reading data, accessing packages, writing functions, debugging, profiling code, and organizing/commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo from Johns Hopkins Bloomberg School of Public Health.
Obtain data from the web, APIs, databases, and colleagues in various formats, as well as the basics of cleaning and “tidying” data. It also covers the components of a complete data set: raw data, processing instructions, code-books, &
processed data.
Beniamin Zahiri-Coursera R Programming 2015BZahiri
This document is a Statement of Accomplishment from Coursera.org indicating that Beniamin Zahirisabzevar successfully completed the online course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was instructed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Statement of Accomplishment: Data Science Specialization V - Reproducible Res...Folco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 5th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
Covers exploratory data summarization techniques that are
applied before modeling to inform development of complex
models. Topics include plotting in R, principles of constructing graphics, and common multivariate techniques used for high dimensional data visualization.
Dom Fernandez completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Dom Fernandez completed The Data Scientist's Toolbox course from Johns Hopkins University on Coursera with distinction. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was offered online through Coursera and does not reflect the entire curriculum available to students enrolled at Johns Hopkins University.
This course covers how to use & program in R for effective data analysis. It covers practical issues in statistical computing: programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, & organizing and commenting R code.
Al French successfully completed Coursera's online course "R Programming" from Johns Hopkins University with distinction. The course covered using and programming in R for effective data analysis, including programming in R, reading data, accessing packages, writing functions, debugging, profiling code, and organizing/commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo from Johns Hopkins Bloomberg School of Public Health.
Obtain data from the web, APIs, databases, and colleagues in various formats, as well as the basics of cleaning and “tidying” data. It also covers the components of a complete data set: raw data, processing instructions, code-books, &
processed data.
Beniamin Zahiri-Coursera R Programming 2015BZahiri
This document is a Statement of Accomplishment from Coursera.org indicating that Beniamin Zahirisabzevar successfully completed the online course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was instructed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Khan Safayet Hossin completed an online Coursera course in Exploratory Data Analysis from Johns Hopkins University with distinction in June 2015. The course covered exploratory data summarization techniques and plotting in R for high-dimensional data visualization before modeling. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Kristian Kragh successfully completed Coursera's online course "R Programming" from Johns Hopkins University with distinction in May 2014. The course covered practical issues in statistical computing using the R programming language, including programming, reading data, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was taught by Roger D. Peng, Brian Caffo, and Jeffrey Leek from Johns Hopkins Bloomberg School of Public Health.
Maloy Manna successfully completed an online course in Exploratory Data Analysis from Johns Hopkins University with distinction in September 2014. The course covered exploratory data summarization techniques and visualization methods used before modeling, including plotting in R and common techniques for high-dimensional data. The course was led by professors Roger D. Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Broad overview of the goals, assumptions, and modes of statistical inference. Can perform inferential tasks in highly targeted settings and are able to use the skills developed for more complex inferential challenges.
Maloy Manna successfully completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered practical issues in statistical computing including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The certificate was signed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Statement of Accomplishment - R ProgrammingDale Ross
Dale Ross completed the Coursera course "R Programming" from Johns Hopkins University with distinction on May 12, 2015. The course covered using and programming in R for effective data analysis, including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Asela Dassanayake successfully completed the Coursera course "Exploratory Data Analysis" from Johns Hopkins University with distinction on June 29, 2015. The course covered exploratory data summarization techniques and principles for constructing graphics that are applied before modeling to inform the development of complex models, including topics like plotting in R and common techniques for visualizing high-dimensional data. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Alexander Voronov successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of the Johns Hopkins Bloomberg School of Public Health.
Robert E Sharp (with Shannon K King, Rachel K Owen, Jonathan T Stemmle and Shaozhong Kang), Division of Plant Sciences, University of Missouri. Missouri China Programme: Science Communication
Mohamed Ramadan and Hassan Khalawy successfully completed Coursera's online course "The Data Scientist’s Toolbox" from Johns Hopkins University with distinction. The course provided an overview of the conceptual and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. It was taught by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Krishna Mohan Avancha successfully completed The Data Scientist's Toolbox course offered by Johns Hopkins University on Coursera with distinction on January 13, 2015. The course provided an overview of the conceptual and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger D. Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
This document provides statements of accomplishment for an individual who completed several online courses offered through Coursera and affiliated with Johns Hopkins University. The courses covered topics including R programming, exploratory data analysis, getting and cleaning data, developing data products, machine learning, statistical inference, and more. The statements recognize completion of the Coursera offerings but note they do not reflect the full curriculum or confer credit, grades, or degrees from Johns Hopkins University.
Julie Hansen Pinto has extensive experience in forensic science research, particularly with entomology. She holds a Master's degree in Forensic Science from the University of New Haven and a Bachelor's degree in Psychology from James Cook University in Australia. Her work experience includes over 15 years of research support roles at Yale University and other institutions. She has focused her research on topics like alcohol and drug abuse, human trafficking, and tick-borne diseases. Pinto is currently a researcher for the Doe Network, working on unidentified and missing persons cases in Connecticut.
Bhavana Venkateshappa received a course certificate from Johns Hopkins University dated August 7, 2016 for successfully completing an online R Programming course through Coursera. The certificate was authorized and signed by Jeff Leek, Roger Peng, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and can be verified on Coursera's website.
Asela Dassanayake successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction in February 2015. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists such as version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Bhavana Venkateshappa completed the online course "The Data Scientist's Toolbox" offered through Coursera and authorized by Johns Hopkins University. The certificate verifies that Bhavana successfully finished the course, which was taught by Jeff Leek, Roger Peng, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Coursera confirmed Bhavana's identity and participation in the course.
Randy Cruz is a junior at Johns Hopkins University majoring in Molecular and Cellular Biology with a 3.71 GPA. He has conducted research at the Johns Hopkins School of Public Health since 2014 investigating novel olfactory receptors in human airway smooth muscle cells. His research has found five receptors expressed in these cells and shown that signaling from one receptor decreases cytoskeletal dynamics and cell proliferation when the cells are treated with propionate. He has also conducted phage research and taken on leadership roles as Treasurer of the Latino student group OLÉ and as a mentor in the MAPP program.
Renato Silveira Carvalho successfully completed the University of Toronto's non-credit online Introduction to Psychology course with distinction on January 31, 2014. The course provided an overview of core areas of psychology including learning, memory, perception, consciousness, human development, and mental illness. The statement acknowledges that the online course does not reflect the entire curriculum offered to enrolled University of Toronto students.
The document proposes ways for an interviewee to improve their communication and problem solving skills through conversation. It recommends talking to various people like colleagues, elders, peers, students, friends to build relationships and receive feedback. The interviewee felt talking to many people was the most practical idea to improve their communication skills without costs. A feedback grid shows the interviewee's preferences for conversations and areas to improve like conversing with peers.
Renato Silveira Carvalho completed a 6 week online Gamification course through Coursera authorized by the University of Pennsylvania. The course was taught by Professor Kevin Werbach of the Wharton School at the University of Pennsylvania. Coursera verified Carvalho's identity and participation in the course.
Tex Gamvrelis successfully completed a Coursera course on Design: Creation of Artifacts in Society from the University of Pennsylvania with distinction on February 10, 2015. The graduate-level course emphasized the basic design process of defining, exploring, selecting, and refining concepts through lectures and design challenges to solve real problems. The course was taught by Professor Karl T. Ulrich of The Wharton School at the University of Pennsylvania.
Khan Safayet Hossin completed an online Coursera course in Exploratory Data Analysis from Johns Hopkins University with distinction in June 2015. The course covered exploratory data summarization techniques and plotting in R for high-dimensional data visualization before modeling. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Kristian Kragh successfully completed Coursera's online course "R Programming" from Johns Hopkins University with distinction in May 2014. The course covered practical issues in statistical computing using the R programming language, including programming, reading data, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was taught by Roger D. Peng, Brian Caffo, and Jeffrey Leek from Johns Hopkins Bloomberg School of Public Health.
Maloy Manna successfully completed an online course in Exploratory Data Analysis from Johns Hopkins University with distinction in September 2014. The course covered exploratory data summarization techniques and visualization methods used before modeling, including plotting in R and common techniques for high-dimensional data. The course was led by professors Roger D. Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Broad overview of the goals, assumptions, and modes of statistical inference. Can perform inferential tasks in highly targeted settings and are able to use the skills developed for more complex inferential challenges.
Maloy Manna successfully completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered practical issues in statistical computing including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The certificate was signed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Statement of Accomplishment - R ProgrammingDale Ross
Dale Ross completed the Coursera course "R Programming" from Johns Hopkins University with distinction on May 12, 2015. The course covered using and programming in R for effective data analysis, including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Asela Dassanayake successfully completed the Coursera course "Exploratory Data Analysis" from Johns Hopkins University with distinction on June 29, 2015. The course covered exploratory data summarization techniques and principles for constructing graphics that are applied before modeling to inform the development of complex models, including topics like plotting in R and common techniques for visualizing high-dimensional data. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Alexander Voronov successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of the Johns Hopkins Bloomberg School of Public Health.
Robert E Sharp (with Shannon K King, Rachel K Owen, Jonathan T Stemmle and Shaozhong Kang), Division of Plant Sciences, University of Missouri. Missouri China Programme: Science Communication
Mohamed Ramadan and Hassan Khalawy successfully completed Coursera's online course "The Data Scientist’s Toolbox" from Johns Hopkins University with distinction. The course provided an overview of the conceptual and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. It was taught by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Krishna Mohan Avancha successfully completed The Data Scientist's Toolbox course offered by Johns Hopkins University on Coursera with distinction on January 13, 2015. The course provided an overview of the conceptual and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger D. Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
This document provides statements of accomplishment for an individual who completed several online courses offered through Coursera and affiliated with Johns Hopkins University. The courses covered topics including R programming, exploratory data analysis, getting and cleaning data, developing data products, machine learning, statistical inference, and more. The statements recognize completion of the Coursera offerings but note they do not reflect the full curriculum or confer credit, grades, or degrees from Johns Hopkins University.
Julie Hansen Pinto has extensive experience in forensic science research, particularly with entomology. She holds a Master's degree in Forensic Science from the University of New Haven and a Bachelor's degree in Psychology from James Cook University in Australia. Her work experience includes over 15 years of research support roles at Yale University and other institutions. She has focused her research on topics like alcohol and drug abuse, human trafficking, and tick-borne diseases. Pinto is currently a researcher for the Doe Network, working on unidentified and missing persons cases in Connecticut.
Bhavana Venkateshappa received a course certificate from Johns Hopkins University dated August 7, 2016 for successfully completing an online R Programming course through Coursera. The certificate was authorized and signed by Jeff Leek, Roger Peng, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and can be verified on Coursera's website.
Asela Dassanayake successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction in February 2015. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists such as version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Bhavana Venkateshappa completed the online course "The Data Scientist's Toolbox" offered through Coursera and authorized by Johns Hopkins University. The certificate verifies that Bhavana successfully finished the course, which was taught by Jeff Leek, Roger Peng, and Brian Caffo of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Coursera confirmed Bhavana's identity and participation in the course.
Randy Cruz is a junior at Johns Hopkins University majoring in Molecular and Cellular Biology with a 3.71 GPA. He has conducted research at the Johns Hopkins School of Public Health since 2014 investigating novel olfactory receptors in human airway smooth muscle cells. His research has found five receptors expressed in these cells and shown that signaling from one receptor decreases cytoskeletal dynamics and cell proliferation when the cells are treated with propionate. He has also conducted phage research and taken on leadership roles as Treasurer of the Latino student group OLÉ and as a mentor in the MAPP program.
Renato Silveira Carvalho successfully completed the University of Toronto's non-credit online Introduction to Psychology course with distinction on January 31, 2014. The course provided an overview of core areas of psychology including learning, memory, perception, consciousness, human development, and mental illness. The statement acknowledges that the online course does not reflect the entire curriculum offered to enrolled University of Toronto students.
The document proposes ways for an interviewee to improve their communication and problem solving skills through conversation. It recommends talking to various people like colleagues, elders, peers, students, friends to build relationships and receive feedback. The interviewee felt talking to many people was the most practical idea to improve their communication skills without costs. A feedback grid shows the interviewee's preferences for conversations and areas to improve like conversing with peers.
Renato Silveira Carvalho completed a 6 week online Gamification course through Coursera authorized by the University of Pennsylvania. The course was taught by Professor Kevin Werbach of the Wharton School at the University of Pennsylvania. Coursera verified Carvalho's identity and participation in the course.
Tex Gamvrelis successfully completed a Coursera course on Design: Creation of Artifacts in Society from the University of Pennsylvania with distinction on February 10, 2015. The graduate-level course emphasized the basic design process of defining, exploring, selecting, and refining concepts through lectures and design challenges to solve real problems. The course was taught by Professor Karl T. Ulrich of The Wharton School at the University of Pennsylvania.
Caroline Peelo earned a Certificate of Achievement for successfully completing an online advertising course, achieving an overall score of 85%. The course covered topics such as the evolution of online advertising, types of online advertising, digital platforms, and digital campaign planning and measurement. Caroline scored highest on the module about digital platforms.
El documento es un certificado de finalización con distinción de un curso sobre corrección y estilo en español impartido por la Universitat Autònoma de Barcelona. El curso, con una perspectiva policéntrica del idioma, fomentó el interés por corregir textos propios y ajenos. El certificado acredita la superación del curso pero no tiene validez académica oficial ni otorga créditos en ningún plan de estudios.
Este documento es un certificado de logro con distinción emitido el 23 de abril de 2014 a Julio César Contreras de León por haber completado con éxito el curso en línea de Tecnologías de información y comunicación en la educación impartido por Coursera, el cual analizó el impacto de las TIC en la educación y los nuevos ambientes de aprendizaje, y requirió 40 horas de trabajo y una calificación superior a 79 puntos.
Nilam Shete completed the Coursera course "Reproducible Research" from Johns Hopkins University with distinction in March 2015. The course covered writing documents using R markdown, integrating live R code, compiling documents using knitr, and organizing analyses to be reproducible. The course was taught by Roger Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Statement of Accomplishment: Data Science Specialization II - R ProgrammingFolco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 2nd Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Basics of creating data products using Shiny, R packages, and interactive graphics. Focuses on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.
Isabelle Claire Valette successfully completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered how to program in R for effective data analysis, including programming syntax, reading data, using packages, writing functions, debugging code, and organizing code. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Pushpa Latha completed the Coursera course "R Programming" from Johns Hopkins University with distinction in June 2015. The course covered using and programming in R for effective data analysis, including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo from Johns Hopkins Bloomberg School of Public Health.
Laurent Debacker successfully completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered practical issues in statistical computing including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was instructed by Roger D. Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Al French completed The Data Scientist's Toolbox course from Johns Hopkins University on Coursera with distinction in August 2014. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Isabelle Claire Valette successfully completed the Coursera course "Reproducible Research" offered by Johns Hopkins University with distinction. The course taught how to write documents using R markdown by integrating live R code, compile documents using knitr, and organize analyses to be reproducible. It was overseen by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Hetvi Patel completed an online Coursera course in R Programming from Johns Hopkins University. The course covered using and programming in R for effective data analysis, including programming in R, reading data, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The certificate was signed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health and notes that the online course does not reflect the entire on-campus curriculum.
This document is a Statement of Accomplishment from Coursera.org indicating that Atul Shrinivas Khot has successfully completed the online course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including programming, reading data, accessing packages, writing functions, debugging, profiling code, and organizing/commenting code. The statement was signed by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Yujuan Wang completed the Coursera course "R Programming" from Johns Hopkins University with distinction in June 2015. The course covered using and programming in R for effective data analysis, including programming in R, reading data into R, accessing packages, writing functions, debugging, profiling code, and organizing and commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo from Johns Hopkins Bloomberg School of Public Health.
Harish successfully completed The Data Scientist's Toolbox course from Johns Hopkins University on Coursera with distinction in October 2014. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was led by Jeffrey Leek, Brian Caffo, and Roger Peng from Johns Hopkins Bloomberg School of Public Health.
Statement of Accomplishment: Data Science Specialization IV - Exploratory Dat...Folco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 4th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
Saumya Tewari successfully completed the Coursera course "R Programming" offered by Johns Hopkins University. The course covered using and programming in R for effective data analysis, including programming in R, reading data, accessing packages, writing functions, debugging, profiling code, and organizing/commenting code. The course was led by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Understand the components of a machine learning algorithm and how to apply multiple basic machine learning tools. Build and Evaluate Predictors on real data.
Darshit Dani completed the Coursera course "R Programming" from Johns Hopkins University with distinction on July 02, 2015. The course covered practical issues in statistical computing including programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling code, and organizing and commenting code. The course was instructed by Roger D. Peng, Jeffrey Leek, and Brian Caffo from the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Asela Dassanayake successfully completed the Coursera course "R Programming" from Johns Hopkins University with distinction. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo from Johns Hopkins Bloomberg School of Public Health.
This document is a statement of accomplishment from Coursera that Shivee Pradeep Gupta successfully completed the course "Developing Data Products" from Johns Hopkins University with distinction on February 11, 2015. The course covered creating interactive data products using Shiny, R packages, and graphics, with a focus on using data to tell stories to a mass audience. The statement was signed by Brian Caffo, Jeffrey Leek, and Roger Peng from Johns Hopkins Bloomberg School of Public Health.
Sanne Smith successfully completed The Data Scientist's Toolbox course from Johns Hopkins University on Coursera with distinction in October 2014. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists, including version control, markdown, git, GitHub, R, and RStudio. The course was overseen by Jeffrey Leek, Brian Caffo, and Roger Peng from Johns Hopkins Bloomberg School of Public Health.
Krishna Mohan Avancha successfully completed the Coursera course "R Programming" offered by Johns Hopkins University with distinction in January 2015. The course covered programming in R for effective data analysis, including reading data into R, accessing packages, writing functions, debugging code, and organizing code. It was taught by Roger D. Peng, Jeffrey Leek, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
Delta Lake is an open format storage layer that delivers reliability, security and performance on your data lake — for both streaming and batch operations;
(please review the document)
I have earned several achievements and badges from SAP related to implementing SAP HANA, developing applications on SAP Cloud Platform, using design-led processes to solve business challenges, and modeling programs in Java. These achievements demonstrate my skills in scaling SAP HANA systems, developing on an enterprise platform-as-a-service, identifying solutions through human-centered design, and applying object-oriented programming principles.
The Travel Industry Council of Ontario (TICO) informs Dominic Fernandez that he has passed the TICO Education Standards Travel Counsellor Exam. While passing the exam allows Dominic to sell travel services on behalf of a TICO-registered travel agency, TICO does not directly register individuals. Dominic's employer will require a copy of his certificate as proof that he has met the education requirements to work as a travel counsellor.
Training is intended for business people who may well be doing what data scientists or technical developers would be doing - To Analyze Mounds of Data!
Data Analytics may sound frightening and technical, but this training is to have business-minds really understand data, AND identify some tools that make data analytics look like child's play!
As users spend more time on mobile devices, getting mobile sites right is crucial to success. If your client’s website is too slow to load, users will drop off. On the other hand, a fast-loading site with bad UX design makes it hard for users to complete their desired action. In a mobile-led world, consumer expectations are high.
Win customers with mobile sites - Improve conversions with small, but mighty, mobile site changes
Cut load times with Developer Tools - Identify inefficiencies in the critical rendering path
Speed up mobile site rendering
Key metrics for testing your site
Optimize mobile site transfer size
Optimize images and fonts
Focus on mobile user experience
Deliver user-centered mobile experiences - Craft a mobile site that delivers a great user experience
Make mobile sites drive conversions - Deliver a mobile site that lets users easily convert
Test and optimize mobile experiences - Discover what your users really want with testing
Create super fast sites with AMP - Get your content seen quickly with Accelerated Mobile Pages (AMP)
Create Progressive Web Apps - Learn to build engaging and reliable Progressive Web Apps
Engage users with APIs - Increase user engagement and conversions with new mobile web APIs
Text Analytics (unstructured - Twitter, Facebook posts) :
Information Extraction is the problem of distilling structured information from unstructured text, for example, finding entities such as persons and organizations, and the relationships between them. Using SystemT - a state-of-the-art Information Extraction System.
Text Analytics (unstructured - Twitter, Facebook posts):
Information Extraction is the problem of distilling structured information from unstructured text, for example, finding entities such as persons and organizations, and the relationships between them. Using SystemT - a state-of-the-art Information Extraction System.
SQL is a language used to communicate with databases and manage data. This course will teach fundamental SQL concepts like querying, filtering, and sorting data. Students will learn how to write basic SELECT statements to retrieve data from one or more database tables.
Dom Fernandez received a Certificate of Completion from Big Data University for successfully completing and passing Predictive Modeling Fundamentals I in October 2016. The certificate recognizes his achievement in the program and signifies that he met the requirements to earn the credential.
NoSQL and DBaaS are database technologies. Dom Fernandez gave an introduction to NoSQL and Database as a Service (DBaaS) on September 17, 2015. The document provides an overview of these database technologies.
This document contains information about a DB2 training course. Dom Fernandez took an essential DB2 training course on October 8, 2016. The instructor for the course was Raul Chong.
Dom Fernandez received a Certificate of Completion in Data Science 101 from Big Data University after successfully completing the course and receiving a passing grade. The certificate was awarded on September 22, 2016 for the DS0101EN course.
Dom Fernandez submitted a Big Data Fundamentals assignment to instructor Raul Chong on September 18, 2015. The document appears to be a student submission with the student's name, class name, date, and instructor's name listed. In 3 sentences or less, it provides the essential information that the document involves a student submitting an assignment to their instructor for a named class on a specific date.
This document appears to be a cover page for a course titled "Introduction to Data Analysis using R" taught by instructor Dom Fernandez on September 21, 2015. The cover page lists the course title, instructor name, and date.
The document outlines the key features and benefits of the ecommerce platform Shopify, including its rapid deployment, extensive app and partner ecosystem, scalability, reliability, and merchant support. It discusses how Shopify handles all the technical aspects of running an online store so merchants can focus on design, sales, and customer experience. The document also provides testimonials from large brands that use Shopify praising its flexibility, ease of use, and ability to customize stores and integrate with other systems and sales channels.
Shopify Plus is a fully-featured eCommerce platform for major brands that offers unlimited bandwidth and storage, 99.98% uptime, and the ability to sell online, in stores, and on social media across multiple languages and currencies. It provides customizable storefronts, hundreds of apps, 24/7 priority support, advanced reporting and analytics, and payment processing for 2.4% per transaction.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Natural Language Processing (NLP), RAG and its applications .pptxfkyes25
1. In the realm of Natural Language Processing (NLP), knowledge-intensive tasks such as question answering, fact verification, and open-domain dialogue generation require the integration of vast and up-to-date information. Traditional neural models, though powerful, struggle with encoding all necessary knowledge within their parameters, leading to limitations in generalization and scalability. The paper "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks" introduces RAG (Retrieval-Augmented Generation), a novel framework that synergizes retrieval mechanisms with generative models, enhancing performance by dynamically incorporating external knowledge during inference.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
1. coursera.org
Statement of Accomplishment
WITH DISTINCTION
AUGUST 11, 2014
DOM FERNANDEZ
HAS SUCCESSFULLY COMPLETED THE JOHNS HOPKINS UNIVERSITY'S OFFERING OF
Reproducible Research
This course covers how to write a document using R markdown,
integrate live R code into a literate statistical program, compile R
markdown documents using knitr and related tools, and organize
a data analysis so that it is reproducible and accessible to others.
ROGER D. PENG, PHD
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
JEFFREY LEEK, PHD
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
BRIAN CAFFO, PHD, MS
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
PLEASE NOTE: THE ONLINE OFFERING OF THIS CLASS DOES NOT REFLECT THE ENTIRE CURRICULUM OFFERED TO STUDENTS ENROLLED AT
THE JOHNS HOPKINS UNIVERSITY. THIS STATEMENT DOES NOT AFFIRM THAT THIS STUDENT WAS ENROLLED AS A STUDENT AT THE JOHNS
HOPKINS UNIVERSITY IN ANY WAY. IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY GRADE; IT DOES NOT CONFER JOHNS HOPKINS
UNIVERSITY CREDIT; IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY DEGREE; AND IT DOES NOT VERIFY THE IDENTITY OF THE
STUDENT.