CMSC 320 - Introduction to Data Science



Class:

Welcome to CMSC 320. This course focuses on (i) data management systems, (ii) exploratory and statistical data analysis, (iii) data and information visualization, and (iv) the presentation and communication of analysis results. It will be centered around case studies drawing extensively from applications, and will yield a publicly-available final project that will strengthen course participants' data science portfolios.

Schedule

Exam Dates:


  • Midterm: Monday, June 24th, in Lecture.
  • Final Tutorial: Friday, July 19th, 11:59 PM.

Lectures


Date
Topic (files)
Reading
Due
(When)
05/28 Course Intro What the fox knows Project 0
(11:59 PM 05/31)
05/29 Python Primer
05/30 Data Collection
05/31 Data Processing
06/03 Quiz, Data Processing, Pandas
Introduction to Pandas
06/04 Tidy Data, SQL
06/05 Tidy Data,
Regression Overview
06/06 Missing Values
06/07 Data Wrangling, Entity Resolution (Slides)
06/10 Quiz, Exploratory Data Analysis I Project 1
(11:59 PM 06/11)
06/11 Exploratory Data Analysis II, Graphs
06/12 Centrality, Community Detection
06/13 Intro to NLP
06/14 Linear Classifier, Language Modeling
06/17 Quiz, Statistical Inference Project 2
(11:59 PM 06/21)
06/18 Hypothesis testing, K-NN
06/19 Loss function, Optimization
06/20 Linear Regression, Gradient Descent
06/21 Review
06/24 Midterm Loss functions, regression and Gradient descent (Class slides)
06/25 Regression and Gradient Descent Contd.
06/26 Stochastic Gradient Descent, Logistic Regression
06/27 Logistic Regression, Model Selection (Overfitting)
06/28 Linear Regression Regularization (Ridge Regression)
07/01 Quiz, Logistic Regression Regularization Logistic Regression, Regularization (Class slides) Project 3
(11:59 PM 07/03)
07/02 Cross Validation
07/03 Decision Trees Example , Final Tutorial Introductions
07/04 No Class - 4th of July
07/05 No Class - Campus Closed, 4th of July extended
07/08 Quiz, Bagging, Random Forests, Intro to SVM Cross validation, Decision Trees, Random Forests (class slides)
07/09 SVM contd.
07/10 Clustering
07/11 PCA
07/12 More PCA
07/15 Quiz, Intro to Neural Networks Final Tutorial
(11:59 PM 07/19)
07/16 More Neural Networks
07/17 Wrap up
07/18 Final Presentations
07/19 Final Presentations

Staff

Instructor: Mohammad Nayeem Teli (nayeem at cs.umd.edu)

Office: 1228 IRB
Office Hours: ThF 3:30 - 4:30 PM


Teaching Assistants


Name Email Office hours (at IRB Level 2 lobby)
Hanyu Wang hywang66@cs.umd.edu TuTh 11:00 AM - 1:00 PM
Jue Xu juexu@terpmail.umd.edu MW 11:00 AM - 1:00 PM


Class Resources

Final Project
Online Course Tools


Projects

Homework Due Date***
Project 0 May 31, 2019
Project 1 June 11, 2019
Project 2 June 21, 2019
Project 3 July 3, 2019
Final Project July 19, 2019

*** Note: All projects are due at 11:59 PM.