Data Bootcamp: Undergraduate Fall 2019
Where and When
- Instructor: Benjamin Zweig (email@example.com)
- Teaching Fellow: Richard Li (firstname.lastname@example.org)
- Meeting times: Tues/Thurs (2:00PM - 3:15PM; 3:30PM - 4:45PM)
- Meeting place: KMEC Room: 3-90, Washington Square
THE SYLLABUS All the important details about the course, procedures, important dates, etc.
THE BOOK The topics in the first half are all in the book. We will follow this closely. At the book link, click the large blue Read button to read online – or download the pdf. Both come with links.
NOTEBOOKS Github repository of notebooks used in class.
DISCUSSION GROUP Post your doubts on NYU Classes forum tab.
Final Project (Due Dec 19, 2019)
Problem Set Submissions
Assignments will be posted on NYU Classes. Submit your python code in ipython notebook format on NYU Classes.
Week By Week Topic Guide…
Python Fundamentals: (9/3 & 9/5)
Handouts: 9/3 Outline | 9/5 Outline | Book | Three ideas
Examples: Gapminder | Cancer Screening | Uber in NYC | Medical Expenditures | Mortality | Earthquake | Gender Pay Gap | Fertility | Vaccines
Summary: Intro; calculations; assignments; strings; lists; tuples; built-in functions; objects; methods; tab completion; True and False; comparisons; conditionals; slicing; loops; function definitions and returns; dictionaries.
Python Fundamentals II, Intro to Packages: (9/10 & 9/12)
Handouts: Outline | Book chapter
Summary: Slicing; loops; function definitions and returns; dictionaries; packages; import; Pandas.
What’s due: Problem Set 1 (9/12);
9/17 - NO CLASS
Cleaning & Filtering: (9/19, 9/24 & 9/26)
Handouts: Outline |Code_Pandas_Cleaning|Applications)
Summary: Cleaning and filtering data.
What’s due: Problem Set 2 (9/26); Team submission (Just team member names..) (9/26)
10/1 - NO CLASS (HOLIDAY)
Shaping and Matplotlib: (10/3, 10/8, 10/10 & 10/17)
Handouts: Shaping Outline | Matplotlib Outline | Book chapter
Code_Pandas_Shaping | Code_Matplotlib (Download “Raw” as ipynb)
Code (examples | current indicators | demography | Airbnb)
Summary: Aggregations and grouping data; three approaches to graphics: dataframe plot methods, plot(x,y), and fig/ax objects and methods; lines, scatters, bars, horizontal bars, styles.
What’s due: Problem Set 3 (10/8); Project ideas submission (10/8); Problem Set 4 (10/17);
10/15 & 10/22 - NO CLASS (HOLIDAY)
10/24 - EXAM REVIEW
10/29 - MIDTERM EXAM
Merging and Data Analysis Workflow I: (10/31, 11/5 & 11/7)
Summary: Merging and Data Analysis Workflow I.
What’s due: Problem Set 5
11/12 - PROJECT TOUCHPOINT
Regression: (11/14, 11/19 & 11/21)
Summary: Basic Regression Analysis
What’s due: Nothing!
11/26 - PROJECT TOUCHPOINT
11/28 - NO CLASS (THANKSGIVING)
Machine Learning: (12/3, 12/5 & 12/10)
(Code_Pandas_Combining | Summarizing)
Summary: Combining dataframes (merge, concatenate). We will also cover Scikit-learn, Machine Learning package to model various classification, regression and clustering algorithms.
What’s due: Problem Set 6; Submit project data & show input with basic diagnostics
Wrap Up & Data Analysis Workflow: (12/12)
Handouts: (Code_Pandas_Combining | Summarizing)
Summary: More into ML and project discussions.
Walk through a data analysis pipeline from importing, exploring, cleaning, visualizing and forming analysis.
What’s due: Problem Set 7
Final Project Due Date: Dec 19, 2019