## Applied Data Analysis

Title | Applied Data Analysis (53120) |
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Quarter | Spring 2020 |

Instructor | Davender Singh Sahota (dsahota@cs.uchicago.edu) |

Website | |

Syllabus | This course provides a self-contained introduction to computational data analysis from an applied perspective. It is intended as a standalone course for students who are not pursuing the full data analysis sequence in the MPCS.
- Course overview
- Probability theory
- Random variables
- Distributions and densities
- Variables, objects, and functions in Python
- Working with data frames
- Data pre-processing and visualization
- Least-squares regression
- Logistic regression
- Hypothesis testing
Week 5: Machine Learning Models I - Perceptron classifier
- Neural networks
- Decision trees/Random forests
Week 7: Clustering - Unsupervised clustering
- Supervised clustering
- Support vector machines
- Common machine learning frameworks
- Big data analytics
Week 11: Project presentations |

Prerequisites (Courses) | MPCS 50103 Discrete Mathematics and Core Programming |

Prerequisites (Other) | Knowledge of Python is required for this class. |

Satisfies | Elective |

Time | Wednesday 5:30-8:30PM |

Location | Harper C03 |