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Updated Spring 2018 Syllabus
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\runningheadrule
\firstpageheadrule
\firstpageheader{\includegraphics[width=0.25\textwidth]{../Figures/stern_black1.pdf}}{}{Data Bootcamp}
\runningheader{Data Bootcamp}{}{Syllabus: ECON-UB.0011.02}
\runningheader{Data Bootcamp}{}{Syllabus: ECON-UB.0232}
\runningfooter{}{}{}

\begin{document}
\centerline{\Large\bf Syllabus: Data Bootcamp}
\vspace{3mm}
\centerline{\large\bf ECON-UB.0232 $|$ Fall 2017}
\centerline{\large\bf ECON-UB.0232 $|$ Spring 2018}
\vspace{3mm}
\centerline{\bf Revised: \today}

Expand All @@ -39,19 +39,28 @@ \subsubsection*{About the Instructor}
Email: \href{mailto:mailto:[email protected]}{[email protected]}\\
Office: KMC 7-74\\
Phone: 212-998-0288\\
Office hours: TBA, Monday and Wednesday.
Office hours: TBA

\subsubsection*{Where and When}
Meeting times: Monday and Wednesday 330-445pm
Meeting times: Tuesday and Thursday 11am-12:15pm

Meeting place: KMC 5-140
Meeting place: KMC 3-70

\subsection*{Important Dates}

Midterm Exam: \textbf{November 8, 2017}. Quick info: 75 minutes, in class, open book, open internet if the wireless is up, bring one page of notes. \\
\begin{itemize}

\item Mini-Midterm \#1: February 22nd, 2018. Quick info: Python fundamentals 1-2, 30 minutes, in class, open book, open internet if the wireless is up, bring one page of notes.

\item Mini-Midterm \#2: March 22nd, 2018. Quick info: Intro to Pandas and Matplotlib, 30 minutes, in class, open book, open internet if the wireless is up, bring one page of notes.

\item Three Project Ideas: March 29, 2018. Jupyter Notebook with three project ideas, briefly flushed out and potential data sources. Hard copy due at 5pm.

\href{https://github.com/NYUDataBootcamp/Materials/blob/master/Documents/bootcamp_project.pdf}{Final Project} Due Date: End of day \textbf{December 21, 2017.}
\item Final Project Proposal + Data Report: April 20th, 2018. Jupyter Notebook with final proposal. More details to be provided. Hard copy due at 5pm.

\item Final Project Due Date: End of Day May 14, 2018

\end{itemize}

\section*{Requirements}

Expand All @@ -73,17 +82,13 @@ \section*{Getting help}

\textbf{Teaching Fellows}\\
\\
Felipe Alves \\
Email: \href{mailto:mailto:falves@stern.nyu.edu}{falves@stern.nyu.edu}\\
Vineetha Kutty \\
Email: \href{mailto:vkk242@nyu.edu}{vkk242@nyu.edu}\\
Office hours: TBA\\

Guess what\ldots you also have classmates that can help!!! You can post questions (and maybe answer your classmates questions) on our discussion group (see below). Felipe and I will also monitor the discussion group.

The bottom line: {\bf If you're stuck, ask for help\/}.
Really. Don't be a hero, ask for help.



\section*{Course website and discussion groups}

Everything you need, including this document, is posted on
Expand All @@ -107,78 +112,47 @@ \section*{Course website and discussion groups}
There's a link to it on the course site.


We have set up {\bf announcement and discussion groups\/} (Google groups)
to make announcements and post questions. We will use this to post all assignments and
answer keys.
If you have coding or other questions, we encourage you to post them there.
If you know the answer to someone else's question, we {\bf strongly } encourage you to post that, too.
The links are
\vspace{-0.1in}
\begin{center}
\url{https://groups.google.com/d/forum/databootcamp_fall2017_undergrad}
\end{center}
\vspace{-0.1in}
You can access the same links from the course website. Follow the instructions to join under whatever email address you plan to use.


\section*{Deliverables and grades}

The course divides naturally into two parts.
The first part is an introduction to those aspects of the Python programming language
useful for data analysis.
We cover this material with as many applications to real data as we can think of.
It ends with an exam.
The second part covers advanced topics and ends with a project of your own.
The goal is for you to have a piece of work you can show potential employers to
illustrate your quantitative skill set.
Both parts include a number of graded deliverables.
The idea is to {\bf do some work all the time rather than lots of work once in a while.}
We don't believe the latter will work.
The course divides naturally into three parts.
\begin{itemize}
\item The first part is an introduction to basic aspects of the Python programming language. The mini-midterm \#1 covers this material.
\item The second part covers data analysis aspects of Python. The key tools we will learn about are Pandas and Matplotlib. We cover this material with as many applications to real data as we can think of. The mini-midterm \#2 covers this material.
\item The third covers advanced topics (mostly advanced functionality of Pandas and visualization) and ends with a project of your own. The ultimate goal is for you to have a piece of work you can show potential employers to illustrate your quantitative skill set.
\end{itemize}
All parts include a number of graded deliverables. The idea is to {\bf do some work all the time rather than lots of work once in a while.} We don't believe the latter will work.

Graded work includes:
%
\begin{itemize}

\item {\bf Code Practice.\/}
There are three such assignments in the first month.
We encourage you do to all of them|they're good practice|
but your grade will be based on the best two. We find that people who finish these assignments
tend to keep up with the material better and these are easy points to get in terms of grades.
We will also distribute Optional Code Practice ``assignments,''
but they will not be collected or graded.
They are, however, a good way to develop your coding skills.
There are four such assignments in the first month and a half. We encourage you do to all of them|they're good practice|but your grade will be based on the best three. We find that people who finish these assignments tend to keep up with the material better and these are easy points to get in terms of grades.

{\it These assignments have questions that range from easy to moderately difficult,
the latter marked {\it challenging\/}.
They're all good practice, but if you're new to programming you
might want to skip the challenging ones.
If you get 70-80 percent of them, you're on the right track. \/}

\item {\bf Examination.\/}
The exam will cover material from the first half of the course.
It takes 75 minutes and will be held in class.
It will involve coding.
{\bf Bring your computer.\/}
We suggest you also {\bf bring one page of notes\/}.
\item {\bf Exams.\/}
There will be two ``mini'' exams. These exams are mini in the sense that they are only 30 minutes long. It will involve coding. {\bf Bring your computer.\/} It will be open book, open internet if the wireless is up. We suggest you also {\bf bring one page of notes\/}.
If the internet is working you will be able to look things up on there.
If not, your notes will save you.
It's also a good study tool: When you decide what to include,
you'll be organizing your thoughts about what you've learned.


\item {\bf Project.\/}
We work our way up to the project one step at a time, starting with idea generation and ending
with a {\bf professional piece of data collection and analysis\/}
that you can share with potential employers.
The structure of the project is laid out in a separate document. We have found that the quality
that you can share with potential employers. We have found that the quality
of final project had a surprisingly low correlation to previous programming experience. A little thought and
effort go a long way in creating an interesting project.

\end{itemize}


{\bf Due dates} are posted on the course website.
Assignments, whether code practice or components of the project,
are due at the start of class on the specified dates.

{\bf Dates are not negotiable.
Anything handed in late will get a grade of zero.\/}
Expand All @@ -188,18 +162,15 @@ \section*{Deliverables and grades}
{\bf Final grades\/} will be computed from
\begin{center}
\begin{tabular}{ll}
Code Practice (best two of three) & 20\% \\
Exam & 30\% \\
Participation / Professionalism & 5\% \\
Code Practice (best three of four) & 15\% \\
Exam \#1 & 15\% \\
Exam \#2 & 15\% \\
Project & 50\% \\
\end{tabular}
\end{center}

Final grades are not subject to any fixed distribution or curve.
The number of A grades, for example,
will depend only on your performance in the course.
If you make a good-faith effort,
we expect it to be hard to get less than a B.
We are the sole judges of what constitutes good-faith effort.
Final grades are not subject to any fixed distribution or curve. The number of A grades, for example, will depend only on your performance in the course.


\section*{Recommended work habits}
Expand Down Expand Up @@ -241,6 +212,20 @@ \section*{Pacing}
The topics should take roughly one week each, but we can scale that up or down as needed.
If you're an expert, don't worry, we'll cover a lot of material either way.

\section*{Professional Behavior}
In the interest of having a high-quality experience for all, your classmates and I ask that you:
\begin{itemize}
\item Attend. They say ``eighty percent of success is just showing up.'' I see it often, those who show up perform systematically better.

\item Arrive to class on time and stay to the end of the class period. Chronically arriving late or leaving class early is unprofessional and disruptive to the entire class.

\item Eating or drinking in class in any way that interferes with class decorum is inappropriate.

\item Be respectful to myself, the teaching fellow, and your classmates.

\item Join your classmates. Avoid the last row. Be Engaged!
\end{itemize}


\section*{Other questions}

Expand All @@ -259,7 +244,7 @@ \section*{Viewing and printing pdf files}
For Mac OS users, Preview has this problem and others; for example,
links don't work and some fonts don't display or print.
The solution is to install Adobe Acrobat Reader or the equivalent
and set it up as your default for pdf files.
and set it up as your default for pdf files.


\section*{Policies}
Expand Down

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