ResourcesGeneral FAQs
What are the benefits of pursuing the MLDS minor?
The MLDS minor provides a general foundation in data science and the opportunity to build skills in one or more subfields of the discipline. Students complete the program empowered to develop comprehensive data science pipelines, using computational data analysis for the estimation, prediction, design, and control of engineering systems.
What is the difference between the data science track in the MLDS minor and the Weinberg data science minor?
The MLDS Data Science track was designed to work within the McCormick curriculum, and to leverage the skills you acquire as an engineer. As we understand it, the Weinberg Data Science minor focuses on teaching everyone to communicate with and about data. The Data Science track within the MLDS minor specifically focuses on acquiring, cleaning, wrangling, and analyzing data, and leveraging the resulting insights towards better decision making.
Which programming language(s) will be taught?
The main programming language will be Python; it is the most popular language when it comes to Data Engineering tools. However, you'll focus more on tools than on programming languages. For example, in DATA_ENG 200, you'll learn some basic shell programming. You'll learn to use API, web scraping, cloud computing, and Tableau, at a minimum.
How are the classes formatted? Are DATA_ENG 200 and DATA_ENG 300 project-based?
Somewhat, but not entirely. That is, you will do hands-on projects with data, but it's not 100% project-based (like a capstone would be).
What classes do you recommend we take to be prepared for DATA_ENG 200 and DATA_ENG 300?
DATA_ENG 200 only requires that you have completed COMP_SCI 150 or COMP_SCI 211. It does require you to do a fair bit of programming. DATA_ENG 300 requires that you complete 200, as well as one choice from each of the core require areas (Statistics, Machine Learning, Programming, Algorithms). DATA_ENG 200 assumes that you already know Python from prerequisites. If you only take COMP_SCI 150 and do not know Python, we recommend you get familiar with it.
