Cloud Computing and Big Data Analytics
Date & Time: Wed., July 6, 2022 • 1–3 p.m. CT Instructor: Jian Tao | Texas A&M’s School of Performance, Visualization & Fine Arts | jtao@tamu.edu Cloud Computing and Big Data Analytics Learning Objectives: Understand the basics of Cloud Computing and its benefits. Become familiar with Spark APIs and its basic abstractions like Resilient Distributed Dataset (RDD) and DataFrame. …
Algorithmic Fairness and Social Ramifications
Date & Time: Wed., June 1, 2022 • 1–3 p.m. CT Instructor: Theodora Chaspari | Texas A&M Computer Science & Engineering | chaspari@tamu.edu Algorithmic Fairness and Social Ramifications Learning Objectives: Identify terms and fundamental concepts related to fairness in AI. Identify methods to analyze bias and fairness in data. Identify methods to debias data. Identify methods …
Data Privacy and Policy
Date & Time: Wed., May 11, 2022 • 1–3 p.m. CT Instructor: Hye-Chung Kum | Texas A&M School of Public Health | kum@tamu.edu Cason Schmit | Texas A&M School of Public Health | schmit@tamu.edu Data Privacy and Policy Learning Objectives: Describe the legal and ethical issues of privacy in sensitive data. Summarize basic privacy and security …
FAIR in the Real World
Date & Time: Wed., April 6, 2022 • 1–3 p.m. CT Instructors: Laura Sare | Texas A&M University Libraries | lsare@library.tamu.edu Daniel Tabor | Texas A&M Chemistry | daniel_tabor@tamu.edu John Watts | Texas A&M University Libraries | jwatts@library.tamu.edu FAIR in the Real World Learning Objectives: Choose appropriate FAIR solutions in biomedical research settings Appraise data using …
Fundamentals of FAIR Research Data
Date & Time: Wed., March 9, 2022 • 1–3 p.m. CT Instructors: Laura Sare | Texas A&M University Libraries | lsare@library.tamu.edu Daniel Tabor | Texas A&M Chemistry | daniel_tabor@tamu.edu John Watts | Texas A&M University Libraries | jwatts@library.tamu.edu Fundamentals of FAIR Research Data Learning Objectives: Identify the characteristics of FAIR data. Design workflows that enable FAIR …
Statistical Learning: Dimension Reduction
Date & Time: Thu., Feb. 17, 2022 • 1–3 p.m. CT Instructor: Sutanoy Dasgupta | Texas A&M Statistics | sutanoy@tamu.edu STATISTICAL LEARNING: DIMENSION REDUCTION Learning Objectives: Recognize the potential impact of the curse of dimensionality in statistical learning problems. Apply PCA as a dimension reduction technique in R. Apply the concept of non-negative matrix factorization. Identify the appropriate type of …
Statistical Learning: Clustering
Date & Time: Thu., Jan. 20, 2022 • 1–3 p.m. CT Instructor: Sutanoy Dasgupta | Texas A&M Statistics | sutanoy@tamu.edu STATISTICAL LEARNING: Clustering Learning Objectives: Apply K-mean clustering algorithm to relevant datasets using R. Apply Gaussian mixture clustering algorithm to relevant datasets using R. Apply Hierarchical clustering algorithm to relevant datasets using R. Apply DBSCAN density based clustering to relevant …
Statistical Learning: Classification
Date & Time: Thu., Dec. 16, 2021 • 1–3 p.m. CT Instructor: Sutanoy Dasgupta | Texas A&M Statistics | sutanoy@tamu.edu STATISTICAL LEARNING: CLASSIFICATION Learning Objectives: Identify the appropriate type of machine learning algorithm based on problem description. Apply Naive Bayes Classification to Biomedical datasets using R. Apply Decision Trees Classification to Biomedical datasets using R. Apply Random Forest Method to …
Statistical Learning: Regression
Date & Time: Thu., Nov. 18, 2021 • 1–3 p.m. CT Instructor: Sutanoy Dasgupta | Texas A&M Statistics | sutanoy@tamu.edu STATISTICAL LEARNING: REGRESSION Learning Objectives: Identify the appropriate type of machine learning algorithm based on problem description. Apply simple linear regression models to Biomedical datasets using R software. Apply multiple linear regression models to Biomedical …
Manipulating and Displaying Big(ish) Data in R
Date & Time: Pre-recorded (previously delivered in the Texas A&M Superfund Big Data Series 2021) Instructors: Fred Wright | North Carolina State University’s Bioinformatics Research Center | fred_wright@ncsu.edu Burcu Beykal | University of Connecticut Department of Chemical & Biomolecular Engineering | burcu.beykal@uconn.edu Allison Dickey | North Carolina State University’s Bioinformatics Research Center| andickey@ncsu.edu MANIPULATING AND DISPLAYING BIG(ISH) DATA IN R …