EMSE 6574: Programming for Analytics

Instructors:

Joel Klein   |    jdk514.gwu.edu

LAs: Suraj Shah & Kyle Rood

Course Outline and Objectives


Introduction to programming for data analytics using the Python programming language. Topics covered include introduction to the Python programming language, structured program design in Python, data structures for analytics in Python, visualization/plotting, file I/O, basic data analytics methods, data acquisition from real world sources, database storage and retrieval, working with Python libraries including NumPy, SciPy, and Pandas. This course will prepare students for higher level courses in data analytics.

Learning Outcomes:
By the end of the course, students will be able to:
  • Design and implement Python programs for challenging problems involving real data
  • sources.
  • Learn computational problem solving, in the context of data analytics applications and learn
  • about algorithm and data complexity.
  • Experience object oriented programming.
  • Experience program testing and debugging in Python.
  • Understand and use various libraries for data manipulation, scientific computing and Visualization (including, but not limited to – NumPy, pandas, Matplotlib).
  •  Learn how to take a data source and create visual and statistical insights
  •  Use and process real datasets from social networks, such as Twitter, Facebook and more.

    Prerequisites and Texts


    Prerequisites:
    • Introductory course in programming
    • Introductory course in Probability and statistics.
    Primary TextBooks/Online Material:  

    Syllabus:

    Syllabus

    Lectures/Lessons

    Lecture Notes and Assignments