Pre-College Instructor, Data Science and Machine Learning 1
Found in: Resume Library US A2 - 1 week ago
Columbia University’s Pre-College Programs for High School Students is seeking qualified candidates to develop and teach on-campus (i.e., in person) courses during Summer ’24.
Please Note: Course(s) and course availability is subject to change. Dates and class times are tentative and subject to change.
Sessions:
Summer A: June 24th - July 12th (Classes do not meet on July 4th)
Summer B: July 16th - August 2nd
Class Times:
9:10-11am & 1:10-3pm OR
11:10am-1pm & 3:10-5pm
Course description:
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.
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.
Responsibilities:
Develop course content, syllabus, lesson plans, and assigned work
Lead and attend all in-person class sessions
Establish and maintain a dynamic in-class environment tailored for our high school population
Evaluate student work and write a holistic evaluation of each participant after the course ends
Monitor and address student concerns and inquiries (you will have around 20-24 students)
Attend and complete all required online trainings
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