MSE IN DATA SCIENCE Whos Who Susan Davidson

MSE IN DATA SCIENCE

Whos Who Susan Davidson Program Director, Academic Advisor and Weiss Professor Office: 566 Levine Linh Thi Xuan Phan Co-director and Associate Professor Office: 576 Levine Clayton Greenberg Teaching Faculty and Academic Advisor Office: 506 Levine Ammarah Aftab Program Coordinator Office: 308 Levine

WHAT SETS US APART? Introductions • Spend 2 minutes introducing yourself to the person/people sitting near you • • • What’s your name? Where are you from? What did you study as an undergrad? Where? Any previous graduate work? Where? Any previous professional experience? Where? • Then you’ll introduce someone sitting near you to the rest of the class

WHAT SETS US APART? Stay Connected Facebook and Twitter@Penn. DATS sharing articles, event updates, or students highlights Slack Channel@Penn. DATS Penndats. slack. com platform for students to interact Contact Email: datsmasters@seas. upenn. edu general program related questions or procedures

Website dats. seas. upenn. edu

Program Foundations (2 course units) Core Requirements (3 course units) Technical & Depth Area Electives (5 course units)

Curriculum Algorithms CIT 596 Core Requirements (3 CUs) Math CIS 515 or STAT 512 or ESE 542 Big Data Analytics CIS 545 Technical & Depth Area Electives (5 CUs) B. Biomedicine C. Social/Network Science D. Applications in Natural Science/Engineering (SCMP only) E. Data-Centric Programming F. Surveys and Statistical Methods G. Data Analysis, Artificial Intelligence Mining and Learning CIS 519 or CIS 520 or STAT 571 or ENM 531 or ESE 545 H. Simulation Methods for Natural Science/Engineering I. Mathematical and Algorithmic Foundations A. Thesis or Practicum (2 CUs) P M. S. E in Data Science Foundations (2 CUs) Programming Languages & Techniques CIT 590 or CIT 591

CIS 545: Big Data Analytics • The equalizer/orientation course: everyone has to take it. • How do you do data science at scale? Crawl ALL of Wikipedia? , 19 layers in your neural network? Answer: use Big Data tools • Holistic considerations, such as ethics. • Homework, midterm, final, and project.

Independent Work (IW) • A course project shows you can do an extended DATS task. • IW shows you can formulate a task. . . and then do it. • IW lasts 1 -2 semesters, so it’s bigger than a course project. • Two flavors: ○ Thesis - a scientific work. The deliverable is mainly theoretical/academic. ○ Practicum - an engineering work. The deliverable is mainly practical/applied.

Featured IW Project Can cell phone metadata predict anxiety? (No access to content of calls, but…)

Featured IW Project • Yes! 74% accuracy on binary classification • Most predictive features: • Did they send texts between 8 pm and midnight? • Number of frequent contacts (5+ times per week).

What can you do now to prepare? • If you already know that you want to do IW, learn a domain! • We expect one class in the data domain on your record. • Your advisor / the domain dictate the form of your work. • If you have an advisor from industry, the Projects Director takes a more active role in supervising. It’s to help you!

Master Design Workshop • Part of the requirement for the CU(s) • Co-located with CIS 545 office hours: Tuesdays 5 -7 pm in Levine 512 • Research skills • Administrative matters • Present your proposal in ~3 minutes to enroll in CU(s). • Get feedback from peers while you work / write.

IW Presentations • Part of the requirement for the CU(s) • Usually during reading days (early December and May) • Give a talk or present a poster. Decide with your advisor. • Communicate your results and showcase your great work!

Your Demographics 46% Female: 54% Male

DATS Student Composition

Where are Submat/Transfers From?

Our Alumni

Student Resources http: //www. cis. upenn. edu/current-students/index. php 1. General Penn Resources • Campus Express • Penn Card • Pennkey Setup (http: //www. upenn. edu/computing/pennkey/) 2. Internal resources • International Student Scholar Services 3. Academic and Research • SEAS graduate Handbook (https: //grad. seas. upenn. edu/student-handbook/)

Computing Resources and Advising • There are computing labs, but most of you have your own laptops. For help with computer-related problems, email cets@seas. upenn. edu • Day-to-day advising/questions: Ammarah Aftab 215 -5732431 or email aammarah@seas. upenn. edu • Curricular advising/Advisor sign-off: Clayton Greenberg, cgreenbe@seas. upenn. edu

DATS Mentorship Program Mission The DATS Mentoring Program connects second year DATS students with first year DATS students. Mentor Roles • Introducing Mentees to the Data Science Program at the University of Pennsylvania • Providing Mentees with clarity on career, academic, and personal plans • Helping mentees get the most out of the DATS experience at Penn and on-campus professional development opportunities • Initiating activates and discussions with mentees regarding career plans, educational and work experience, perspectives on work, interest, career values, skills, or talents • Offering advice and suggestions on course selection and the DATS practicum • Encouraging mentees when/if they encounter any academic or career issues while offering constructive feedback and following up

Penn Data Science Group (PDSG) is a student group, founded in late 2016 ● Projects ● Kaggle Team ● Journal Club ● Education ● Recruitment Events Slack Channel : pdsg. slack. com Website : penndsg. com Roshan Santhosh roshansk@seas. upenn. edu

PDSG Upcoming Projects

Upcoming Events DATS Meet Up 2 nd Week of every month Time and Location: TBD

Contact Information If you have more questions please call or email: 215 -573 -2431 aammarah@seas. upenn. edu

Q & A