QBS 101 Foundations of Programming for Data Scientists
This course is designed for graduate students with little to no prior programming experience who are eager to understand computational approaches to solving problems. This course will equip you with the foundational skills needed to excel in computational data science.
Course Highlights:
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Foundations of Programming: Learn the essential concepts of programming, including variables, expressions, flow control, basic algorithms, and data frames.
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Computational Data Science: Get comfortable with Python, Bash scripting, and High-Performance Computing (HPC) environments.
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Hands-On Learning: Engage in live code examples and in-class exercises that bring ideas to life without getting bogged down by computer idiosyncrasies.
Practical Learning:
This course emphasizes hands-on learning through live coding examples and interactive in-class exercises. You'll gain practical experience with:
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Python: Basics of programming, using notebook environments (Jupyter Notebooks).
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Bash Scripting: Command line input, file input/output, and mixing languages with Python.
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High-Performance Computing (HPC): Introduction to Dartmouth's HPC environments like Andes, Polaris, and Discovery.
Course Experience:
Engage with the material in a dynamic classroom setting where theoretical concepts are brought to life through practical application. Each week includes:
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Live coding sessions.
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In-class exercises that reinforce your learning.
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Mock Tech Interviews (MTI) designed to prepare you for industry and academic job and internship processes, focusing on coding and data science challenges.
Requirements:
To fully benefit from this course, it is recommended that you bring a laptop or tablet with a full keyboard to each lecture. This will allow you to follow along with the coding exercises and actively participate in the hands-on components of the class.
(1 unit)
Instructor
Dr. Christian Darabos
Prerequisite
None