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Qualitative Data Analysis with MAXQDA Software
by Karen Andes, PhD- 4.6
Approx. 16 hours to complete
This course will introduce you to MAXQDA software for easier data analysis during the qualitative research process. You'll explore how to do memos, variables, segmentation, coding, and data reduction techniques all in this course! Introduction to Qualitative Data Analysis [Handouts] Tools & Processes of Data Analysis [Prep] Download Initial Data Files...
Social Media Data Analytics
by Chirag Shah- 4.1
Approx. 13 hours to complete
Final Project Deliverable/ Artifact: The course will have a series of small assignments or mini-projects that involve data collection, analysis, and presentation involving various social media sources using the techniques learned in the class. (Optional) Introduction to Python for Econometrics, Statistics and Data Analysis Video-4: Social Media Data Analysis with R...
Population Health: Responsible Data Analysis
by Mar Rodriguez Girondo , Jelle Goeman , Saskia le Cessie- 4.6
Approx. 21 hours to complete
In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. Welcome to Responsible Data Analysis Population health: Responsible Data Analysis Initial data analysis Case study: Initial data analysis in practice...
Data Science in Stratified Healthcare and Precision Medicine
by Dr Areti Manataki , Dr Frances Wong- 4.6
Approx. 17 hours to complete
An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. About the Course Demystifying Data Science Course Logistics Course Team...
Analysis for Business Systems
by Ken Reily- 4.8
Approx. 9 hours to complete
During the Analysis for Business Systems course, you’ll learn about the standard model for systems development: the systems development lifecycle, or SDLC. 3-2 Feasibility Analysis Analysis Phase Documentation 1-1 Analysis Phase to System Proposal Module 2: Analysis Phase Documentation Quiz Analysis Phase Diagrams 4-3 Course Wrap Up Course Project Course Project Overview...
Machine Learning With Big Data
by Mai Nguyen , Ilkay Altintas- 4.6
Approx. 22 hours to complete
Want to make sense of the volumes of data you have collected? Association Analysis Association Analysis in Detail Machine Learning With Big Data - Final Remarks Cluster Analysis in Spark Slides: Cluster Analysis Slides: Association Analysis Cluster Analysis in Spark PDFs of Cluster Analysis in Spark Hands-On Readings Regression, Cluster Analysis, & Association Analysis...
Code Free Data Science
by Natasha Balac, Ph.D.- 4.3
Approx. 14 hours to complete
The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Welcome to the Code Free Data Science Class...
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Genomic Data Science with Galaxy
by James Taylor, PhD- 3.6
Approx. 7 hours to complete
This is the second course in the Genomic Big Data Science Specialization. Working with sequence data Sequence Data Quality Control ChIP-Sequence Analysis with MACS...
Apache Spark (TM) SQL for Data Analysts
by Kate Sullivan- 4.6
Approx. 14 hours to complete
Apache Spark is one of the most widely used technologies in big data analytics. You will also learn how to work with Delta Lake, a highly performant, open-source storage layer that brings reliability to data lakes. Common struggles with big data Big Data Needs Exploratory Data Analysis lab introduction Your turn! Exploratory Data Analysis lab 3 Exploratory Data Analysis Quiz...
Experimental Design Basics
by Douglas C. Montgomery- 4.7
Approx. 13 hours to complete
This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Course Introduction Course Description Course Textbook and Resources Course Project...