CIS 700-003: Big Data Analytics (Spring 2017, Beta version)

Assignment 0 Getting Started. This simple assignment gets you started with Docker and Jupyter, as well as our course submission site.
Assignment 1 Data Wrangling. Learn to read, save, combine, and clean data in Pandas and SQL. Integrate across sources. Conduct simple analyses of data.
Assignment 2 Big Data, Graph Data. Learn to use Apache Spark. Traverse graph data. Compute measures of graph centrality. Recommend friends in a social network.
Assignment 3 The Cloud, Matrices, and Arrays. Learn to use Spark on Elastic MapReduce. Perform computations over graphs and documents using NumPy. Learn a bit about document vectors and information retrieval.
Assignment 4 Optimization, Search, and Clustering. Learn algorithmic primitives such as gradient-descent, search, genetic algorithms, dynamic programming, and clustering. Along the way you'll build a simple artificial neuron and learn about gene sequence alignment.
Assignment 5 Classification and TensorFlow. Build a classifier using spam, experimenting with different classifier methods and ensembles. Construct a neural network in Google's TensorFlow.
Assignment 6 Tuning, Time-Series Data and Visualization. Experiment with tuning classifiers for detecting seizures in dog EEG data. Visualize spatiotemporal activity from earthquakes.