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Designed for the not-yet-experienced programmer, this course will provide you with a structured foundation for developing complex programs in the fields of computer science or data science. If you are a self-taught programmer with scattered bits of understanding, or a complete novice, this is the course for you. Here, you will gain a thorough understanding of how to write programs to solve problems, through structured, scaffolded, hands-on exercises with many examples and opportunities to practice. You will learn the foundational concepts of computer science by developing programs in the python programming language (one of the most commonly used languages). We will also use many of the most common python packages -- why reinvent the wheel when you can use well-tested, flexible, pre-built solutions? While these packages can save significant time, it is also important to understand how they do their magic, and if your particular problem is the right fit to be solved by these potential tools. You will encounter the following python packages: numpy, scipy, matplotlib, pandas, seaborn, re (for regular expressions), textblob, nltk, and others. In the process of learning how to program, we will explore different topics at the introductory level, including natural language processing and data analytics. By the end of this course, you will be confident in your ability to solve a problem using the python programming language -- and how to verify that your solution is accurate.