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Data science and machine learning are exciting and popular disciplines. While different fields, they work best in sync to help change the way humans think, behave, and interact. In fact, some of the most popular data science methods stem from machine learning. Through this course, students will be introduced to the foundations of both science areas and explore available career opportunities. Beginning with an overview of the landscape and real-world applications, students will learn how data science and machine learning impact the world in which we live, every day. Further, students will gain hands-on experience with introductory coding using Python and become versed in popular machine learning algorithms. By the end of the course, students will use their benchmark knowledge to analyze and present data ethically and effectively. Finally, students will leave the course prepared for more advanced practice in data science and machine learning. 

Please note, this course is for students with little-to-no previous experience with coding/programming. Students with more advanced knowledge should consider Data Science and Machine Learning II. 

The power of data science and machine learning can change the world. From voice activation to video game programming to advancements in medical science - the possibilities for activation are endless. Through this advanced course, students will leverage their foundational knowledge of Python to develop a more sophisticated programming skill set. Further, students will use a variety of mathematical techniques (statistics, linear algebra, and probability) to analyze data and create impactful visualizations. By course completion, students will become well-versed in a range of strategies and techniques in both data science and machine learning and become data-driven decision makers. Further, students will be able to apply communication skills and fairness frameworks to identified solutions, making them invaluable assets to any future data science/machine learning classroom, or future employer. 

Note: This course is for students with prior programming experience (in particular, Python) and/or previous coursework in Data Science and Machine Learning. Further, some background in statistics and linear algebra is helpful. Students with little-to-no prior experience in these areas should explore our Data Science and Machine Learning I course.