
National Student Data Corps Video Library
Check out these videos on data science topics based on IBM’s OpenDS4All curriculum and presented by Columbia University Master’s students.
Welcome to the NSDC Video Library where you can watch videos on data science topics based on IBM’s OpenDS4All curriculum, as well as student-created SQL and R educational materials, data science use cases, and more, presented by data enthusiasts from around the world.
If you’re interested in creating video content leveraging IBM’s OpenDS4All content, please email the NSDC HQ team at nsdc@nebigdatahub.org.
Introduction to Data Science
Data Science Ethics
Data Acquisition & Wrangling
Data Integration
Data Visualization & Modeling
Computer Programming
Machine Learning
Artificial Intelligence
Data Science Use Case Scenarios
Introduction to Data Science
With Yucen Wang and Varalika Mahajan
Watch these videos to learn more about the difference between data science, data analytics, and data engineering. Become familiar with topics including data science models, knowledge graphs, and additional data science applications.
What is Data Science? - Part 1
What is Data Science? - Part 2
Introduction to Data Science
Data Science Ethics
With Abhishek Sinha, Varalika Mahajan, and Rahulraj Singh
These videos provide a framework for the important topic of ethics in the collection and usage of data. Watch these videos to learn more about privacy, transparency, consent, explainability and fairness in data science, and walk through a use case using the Breast Cancer Wisconsin (Diagnostic) Data Set in Part 1 of the AI Explainability series.
Data Science Ethics - Part 1
Data Science Ethics - Part 2
AI Explainability - Part 1
AI Explainability - Part 2
AI Fairness - Part 1
AI Fairness - Part 2
Data Acquisition & Wrangling
With Varalika Mahajan, Renyin Zhang and Sanket Bhandari
Learn more about structured and unstructured data, and practice acquiring, extracting, cleaning, plotting and grouping data from a dataset with real-world examples along the way.
Data Types
Data Acquisition and Wrangling - Part 1
Data Acquisition and Wrangling - Part 2
Data Acquisition and Wrangling - Part 3
Data Wrangling Jupyter Notebook - Part 1
Data Wrangling Jupyter Notebook - Part 2
Data Integration
With Stephanie Guo, Lylybell Teran, and Varalika Mahajan
Familiarize yourself with the process of data integration, including breakdowns of the most common data quality issues, feature selection approaches, and partitional clustering and hierarchical clustering methods. Learn how to detect inconsistencies, find duplicates, and handle outliers within your dataset.
Introduction to Data Cleaning
Feature Selection
Data Clustering
Data Visualization & Modeling
With Rahul Singh and Varalika Mahajan
Review how visual interfaces, knowledge graphs, and entity-relationship modeling can help analyze datasets and illustrate algorithmic performances, and practice your skills with a COVID Case Study.
Information Visualization and Visual Analytics
Data Exploration and Visualization – A COVID Case Study
Data Representation and Modeling
An Introduction to R
With Dashansh Prajapati
Familiarize yourself with R, a programming language commonly used for statistical analysis. Throughout this video you will learn about RStudio’s Source Pane, Console Pane, Environment/History Pane, and more.
An Introduction to R
An Introduction to Structured Query Language (SQL)
Content created by Hoang Luong and presented by Gabriella Qi
Discover relational databases and relational database management systems (RDBMS) including MySQL. Learn more about common operators and practice your skills with examples along the way.
An Introduction to SQL - Part 1
An Introduction to SQL - Part 2
An Introduction to SQL - Part 3
An Introduction to SQL - Part 4
An Introduction to SQL - Part 5
Supervised Machine Learning
with Tomislav Galjanic
Watch these videos to learn more about supervised machine learning, including topics such as classifiers, decision trees, and random forests.
Supervised Machine Learning - Part 1
Supervised Machine Learning - Part 2
Supervised Machine Learning - Part 3
Supervised Machine Learning - Part 4
Supervised Machine Learning - Part 5
Linear & Logistic Regression Presentation
Linear & Logistic Regression Jupyter Notebook
Regression Analysis
Artificial Intelligence
with Lylybell Teran and Sneha Dahiya
Watch these videos to learn how to solve machine learning and artificial intelligence problems with the use of artificial and convolutional neural networks.
Artificial Neural Networks - Part 1
Artificial Neural Networks - Part 2
Artificial Neural Networks - Part 3
Convolutional Neural Networks - Part 1
Convolutional Neural Networks - Part 2
Data Science Use Cases – from the AI for Social Good Fall 2020 Symposium
In 2020, the Association for the Advancement of Artificial Intelligence’s AI for Social Good Fall Symposium featured student and researcher presentations on the role of AI can play in data science for social good initiatives.
Recent developments in the availability of big data and computational power are continuing to revolutionize several domains opening up new opportunities and challenges. In this symposium, we highlight two specific themes of humanitarian relief and healthcare where AI could be used for social good to achieve the United Nations (UN) sustainable development goals in those areas, which touch every aspect of human, social, and economic development. We expect the symposium to identify the critical needs and pathways for responsible AI solutions for achieving the sustainable goals, which demand holistic thinking on optimizing the trade-off between automation benefits and their potential side-effects.
Health Care Misinformation: An AI Challenge for Low-Resource Languages
Robust Lock-Down Optimization for COVID-19 Policy Guidance
Socioeconomic and Geographic Variations that Impact the Spread of Malaria
Asymptotic Cross-Entropy Weighting and Guided-Loss in Supervised Hierarchical Setting using Deep Attention Network
Clean Water: How the AI community can contribute to accessing water sources in developing countries
Measuring and Visualizing Social Distancing Using Deep Learning and 3D Computer Vision
Artificial Intelligence and Resource Allocation in Health Care: The Process-Outcome Divide in Perspectives on Moral Decision-Making
Two-Step Framework for Parkinson’s Disease Classification: Multiple One-Way ANOVA on Speech Features and Decision Trees
Check out the NSDC Educator Central and NSDC Learner Central for more data science resources.
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