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.
| Week Starting | Lecture |
|---|---|
| 07/10 | Day 1: Course Intro
Intro to Data Science / Intro to Python Day 2: Data Collection Day 3: Data Processing (Numpy ) Day 4: Pandas & Tidy Data Day 5: SQLite and Intro to Linear Regression |
| 07/17 |
Day 1: Missing Data
Day 2: Exploratory Data Analysis Day 3: Graph exploratory data analysis Day 4: Graph Measurements & Community Detection Day 5: Natural Language Processing |
| 07/24 |
Day 1: NLP (Contd.)
Day 2: Hypothesis Testing Day 3: Statistical Inference & KNN Day 4: ML Loss Functions Day 5: Midterm |
| 07/31 |
Day 1: Linear Regression: Least Squares Optimization
Day 2: Gradient Descent Day 3: Multi variate Linear Regression / Stochastic Gradient Descent Day 4: Logistic Regression Day 5: Decision Trees |
| 08/07 |
Day 1: Random Forests
Day 2: SVM Day 3: Cross Validation /Ridge Regression Day 4: Unsupervised Learning (KMeana, Aggl. Clustering) / Loss functions and distance metrics Day 5: Loss Functions / PCA |
| 08/14 |
Day 1: PCA Contd. / ML Hardware Day 2: Introduction to Neural Networks Day 3: Dimensionality Reduction using Neural Networks Day 4: Insight / Wrap-up Day 5: Final Exam |
Instructor: Mohammad Nayeem Teli (nayeem at cs.umd.edu)
Office Hours: Wednesday 10:30 AM - 11:30 AM (Online)
| Name | |
|---|---|
| Michael-Andrei Panaitescu-liess | mpanaite at umd.edu |
| Daeun Jung | daeunj at umd.edu |
| Rifaa Qadri | rqadri at umd.edu |
| Monday | Daeun: 11:00 AM - 1:00 PM |
| Thursday | Daeun: 11:00 - 1:00 PM , Michael-Andrei: 1:00 - 3:00 PM, Rifaa: 3:00 - 5:00 PM |
| Friday |
Michael-Andrei: 1:00 - 3:00 PM, Rifaa: 3:00 - 5:00 PM |