Industry and Government Careers

Learning about Nonacademic Careers

Preparing for Nonacademic Careers

  • Updating your résumé. See the Graduate College Résumé Advice and Samples. The sample résumés by Michaels and Russo show how to extract transferrable skills from your teaching experience.
  • Developing your skills – courses on campus
    • STAT 542 Statistical Learning (highly recommended). Theory and proof of popular machine learning algorithms, with practical implementation homework. The end-of-semester project is good for your CV.
    • Machine learning courses at University of Illinois
    • Other courses:
      STAT 425 Applied Regression and Design
      STAT 440 Statistical Data Management
      STAT 448 Advanced Data Analysis
      CS 446 Machine Learning
      CS 512 Data Mining
      CS 598 Machine Learning for Signal Processing (topics course)

      For students who need numerical methods:
      CS 101 – Intro Computing: Engrg & Sci (tools course, scientific computing, C, Matlab, Unix/Linux)
      CS 357 – Numerical Methods I (theoretical, Python, Mathematica, Matlab, course for large scale programming)
      CS 450 – Numerical Analysis (theoretical)
      CS 555 Numerical Methods for PDEs

      For students who need programming exposure and not numerical methods:
      CS 125 – Intro to Computer Science (Java, object oriented programming)
      CS 173 – Discrete Structures (prereq for CS 225)
      CS 225 – Data Structures (C++, object oriented programming)
  • Developing your skills – online training
    • Udacity: “Programming Foundations with Python,” “Design of Computer Programs” These free, self-paced courses are extremely well-structured and interesting. Highly recommended!
    • Free courses are offered through Coursera, EdX, Udacity, and directly from highly ranked universities; use a google search to find listings of MOOCs. You can find courses on coding, algorithms, machine learning (e.g. the course by Stanford's Andrew Ng is highly recommended), and data science.
    • Math/coding problems to train on at ProjectEuler.net. Form a group with other graduate students to tackle some of the problems!
    • Lynda.com, which is free to University of Illinois students, offers online courses. Search its playlists under "developer" to find series of courses in topics such as "Learn to Program in C++," "Learn to Program in JavaScript," "Learn to Program in Python" and others.
    • Coursera now offers "specializations" -- students must pay a fee to earn the specialization certificate; however you can gain the same knowledge by taking the recommended courses for free. Our own university, for example, has a specialization in Data Mining, and Johns Hopkins has one in Data Science.
  • How to become a data scientist


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