Search result for Bias in data analysis Online Courses & Certifications
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Analyze Datasets and Train ML Models using AutoML
by Antje Barth , Shelbee Eigenbrode , Sireesha Muppala , Chris Fregly- 4.6
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Approx. 14 hours to complete
In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms. Practical data science is geared towards handling massive datasets that do not fit in your local hardware and could originate from multiple sources. Week 2: Data Bias and Feature Importance...
Introduction to Systematic Review and Meta-Analysis
by Tianjing Li, MD, MHS, PHD , Kay Dickersin, PhD- 4.8
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Approx. 14 hours to complete
We will cover how to formulate an answerable research question, define inclusion and exclusion criteria, search for the evidence, extract data, assess the risk of bias in clinical trials, and perform a meta-analysis. Searching Principles and Bias Assessment Searching Principles and Assessing Bias Lecture 4D: Bias in the Analysis Lecture 5D: Bias in the Analysis...
Promote the Ethical Use of Data-Driven Technologies
by Renée Cummings , Aaron Hui , Megan Smith Branch , Eleanor 'Nell' Watson , Tania De Gasperis- 4.7
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Approx. 21 hours to complete
The greatest risk in emerging technology is the perpetuation of bias in automated technologies dependent upon data sets. A Day in the Life of an Ethical Data Scientist Data Science Ethics in Practice Data Collection Bias Confirmation Bias in Data Science Racial Bias in Criminal Risk Assessment Algorithms Bias in Facial Recognition Case Study...
Detect and Mitigate Ethical Risks
by Renée Cummings , Jennifer Fischer , Eleanor 'Nell' Watson- 0.0
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Approx. 20 hours to complete
Data-driven technologies like AI, when designed with ethics in mind, benefit both the business and society at large. Ethical Risk Analysis Fundamentals Implicit Bias Sampling Bias Reinforcement Bias Temporal Bias Overfitting to Training Data Analyze Models in Different Environments Protect the Security of Data in Storage Protect the Security of Data in Transit...
Performing Network, Path, and Text Analyses in SAS Visual Analytics
by Nicole Ball- 4.7
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Approx. 4 hours to complete
In this course, you learn about the data structure needed for network, path, and text analytics and how to create network analysis, path analysis, and text analytics in SAS Visual Analytics. Demo: Creating a Network Analysis Data Source Practice: Analyzing a Network Analysis Data Source Demo: Analyzing a Path Analysis Data Source...
Structuring Machine Learning Projects
by Andrew NgTop Instructor , Younes Bensouda MourriTop Instructor , Kian KatanforooshTop Instructor- 4.8
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Approx. 6 hours to complete
In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. Avoidable Bias Lectures in PDF Bird Recognition in the City of Peacetopia (Case Study) Bias and Variance with Mismatched Data Distributions...
Machine Learning With Big Data
by Mai Nguyen , Ilkay Altintas- 4.6
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Approx. 22 hours to complete
• Design an approach to leverage data using the steps in the machine learning process. Data Exploration in Spark Data Exploration in Spark Data Exploration in KNIME and Spark Quiz Association Analysis in Detail Cluster Analysis in Spark Cluster Analysis in Spark PDFs of Cluster Analysis in Spark Hands-On Readings Cluster Analysis in Spark Quiz...
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Advanced Manufacturing Process Analysis
by Rahul Rai- 4.6
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Approx. 13 hours to complete
Variability is a fact of life in manufacturing environments, impacting product quality and yield. Through this course, students will learn why performing advanced analysis of manufacturing processes is integral for diagnosing and correcting operational flaws in order to improve yields and reduce costs. The Data Analysis Process Data Collection in Different Manufacturing Settings...
Managing Data Analysis
by Jeff Leek, PhD , Brian Caffo, PhD , Roger D. Peng, PhD- 4.6
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Approx. 9 hours to complete
We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results. Routine Communication in Data Analysis...
Foundations of mining non-structured medical data
by Alejandro Rodríguez González , Consuelo Gonzalo-Martín , Ernestina Menasalvas- 4
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Approx. 7 hours to complete
Big Data in medical domain: opportunities and challenges Data generated in the health domain Challenges in unstructured data in health domain Challenges and problems in biomedical texts Challenges and problems in medical images Challenges in unstructured data in health: evaluation test NLP in medical domain NLP in medical domain: evaluation test Data Analysis of structured information...
