Data Bootcamp: Undergraduate Fall 2019


Where and When



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.
What’s due:


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)

Handouts: Outline
Summary: Merging and Data Analysis Workflow I.
What’s due: Problem Set 5


11/12 - PROJECT TOUCHPOINT


Regression: (11/14, 11/19 & 11/21)

Handouts:
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)

Handouts: (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