Python Workshop IIII: warm up for "Data Science by Python" class

This meetup is a warm-up session for for our upcoming Python class. You may RSVP for the class at https://www.meetup.com/NYC-Data-Science-Academy/events/150712372/

John Downs is a Software Engineer in Test at Yodle. He is going to cover Python basics by building a feature for a data product. We're going to build a web interface using Flask to answer some questions about local restaurants.

Prerequisite:

you should have some programming experience in another language, but not necessarily Python.

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Data Science Academy Syllabus:

Date: Classes will be offered on Mar 8th, 15th, 22th, 29th, April 5th(Five Saturdays)

Time: 12:00-4:00pm

Instructor: John Downs

Course Outline:

(Content may be adjusted based on the experience of the class)

Week 1: Intro to Data Analysis with Python - 4 hours

Abstract: An introduction to the Python language and libraries for data analysis. An overview of data mining methods.

Exercises: Project Euler, New York City Housing Data

• How to learn Python
• Python resources
• IPython
• Language Overview
• Pandas
• Numpy
• Scipy
• Scikit-learn
• Data Analysis Overview

Week 2: Visualization and Algorithms - 4 hours

Abstract: Data visualization, collection and regression

Exercises: NYC Housing Data, Web Scraping

• Graphics with Matplotlib
• Collecting data from the web
• Data Aggregation
• Linear Regression
• Logistic Regression

Week 3: Machine Learning - 4 hours

Abstract: Machine learning with Scikit-Learn

Exercises: New York Times article classification, Ad Click prediction

• Decision Trees
• Scikit-Learn
• Supervised Learning
• K Nearest Neighbors
• Unsupervised Learning
• K Means
• Spam Filtering
• Naive Bayes

Week 4: Time Series and Financial Modeling - 4 hours

Abstract: Analysing time series data, models for finance, causality and feedback loops

Exercises: Yahoo Finance

• Selecting Features
• Time Series with Pandas
• Causality
• Feedback loops
• Financial Models

Week 5: Building a Data Product - 4 hours

Abstract: An overview of some data products and hands on work

Exercise: Recommendation Engine

• Web Frameworks
• Intrusion Detection
• Recommendation Engines