Assignments should be linked from lessons for which they provide either a formative or summative assessment of the lesson’s learning objective.
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A first assignment applying simple time-series forecasting algorithms such as Weighted Moving Average, Exponential Smoothing, and Linear Regression Trend Line. Introduces key concepts in predictive analytics and model evaluation. #R #dataframes #CSV #programming #R Studio #Posit Time: 5 hours · Level: beginner
An assignment that provides opportunities to explore the normalization of continuous variables and the encoding of categorical variables for distance-based machine learning algorithms such as kNN, k-means, and SVM. #R #kNN #categorical #encoding #normalization Time: 90 min · Level: beginner
An assignment to build a statistical learner using multiple linear regression. #R #regression #lm #multiple regression Time: 3 hours · Level: intermediate
A more elaborate exercise in R that utlizes programming to generate a synthetic CSV file for games in a sports league. #R #dataframes #CSV #programming #R Studio #Posit #synthetic data Time: 3 hrs · Level: intermediate
Write data analysis report using markdown in an R Notebook. Learn to produce analysis work that is reproducible. #R #dataframes #CSV #markdown #R Notebook #R Studio #Posit #LaTeX Time: 2 hrs · Level: intermediate
Most operating systems use a hierarchical file system for storing documents, images, media, programs, and any other type of data in files. The file system can act as a database and is often used to store large file objects, often in conjunction with a database (such as a relational database). In this assignment, you will experiment with navigating the file system in R and implement a simple query structure for a hierarchical document object data store. #R #dataframes #CSV #files #file system Time: 6 hrs · Level: intermediate
Conduct simple data analytics in an R Notebook. #R #dataframes #correlation #sampling #exploratory visualization #exploration Time: 90 min · Level: beginner
Build simple time-series forecasting models and test their fit in an R. Identify outliers. #R #time-series #forecasting #MAD #MSE #regression Time: 90 min · Level: beginner
Explore key concepts of probability, including event space, logical vs empirical probability, expected value, joint probability, and Bayes' Theorem. #probability #bayes #joint probability Time: 90 min · Level: beginner
In this assignment, learners will have the opportunity to express queries against a relational datastore in an abstract and language or database independent manner using both relational algebra and tuple relational calculus. In addition, learners will explore how relational algebra contrasts with SQL. #relational algebra #relational calculus # latex Time: 90 min · Level: graduate
In this assignment, learners will have the opportunity to query a relational database using SQL. #sql #sqlite #mysql #select Time: 90 min · Level: graduate
A first assignment in transforming a simple XML to another XML using XSLT. #XML #XPath #XSL #XSLT #transformation Time: 90 min · Level: graduate,undergraduate
Understanding the potential transfer time of data from a storage device is critical to building systems. After all, one must know how long it takes to bring virtual memory pages into memory, how long a file might take to read, or how long data takes to be transferred to a storage device. #reliability #systems #performance Time: 90 min · Level: graduate