TBD
3 Months, Online
6-8 hours per week
USD 1,400
Artificial Intelligence (AI) is being used extensively to solve real-world complex problems. From driving automobiles to providing virtual assistance, use of artificial intelligence in our day to day lives are projected to increase manifold in the coming years. In fact, as per a survey conducted by PwC, business leaders said they believe AI is going to be fundamental in the future. In fact, 72% termed it a "business advantage."
At Columbia Engineering, we are fascinated by the possibilities of data-driven technologies. We have created the Applied Artificial Intelligence course, in partnership with EMERITUS, to help students across the world understand how this data-centric approach can be applied to your daily lives.
DOWNLOAD BROCHUREPREREQUISITES:
● This course requires an undergraduate knowledge of linear algebra (vectors, matrices, derivatives), calculus, and basic probability theory.
● All assignments/application projects will be done using the Python programming language. You should have an intermediate knowledge of Python or you should have completed the Emeritus Python for Data Science course prior to joining this course.
Ansaf received her PhD in Computer Science from the University of Orleans, France. She was an Associate Research Scientist at the Columbia University’s Center for Computational Learning Systems and served as an adjunct professor with the Computer Science department and the Data Science Institute. Ansaf’s research interests lie in machine learning and artificial intelligence. She has done research on frequent patterns mining, rule learning, and action recommendation and has worked on projects including geographic information systems and machine learning for the power grid. Her current research interest includes crowd sourcing, medical informatics and education.
Upon successful completion of the course, participants will receive a verified digital certificate from EMERITUS in collaboration with Columbia Engineering Executive Education.
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David holds a B.S. in Finance, Information Systems and Statistics from the University of Florida, has served as an AI Fellow, and is finishing his PhD in Advanced Technology Research Methods at Capitol Technology University.
David is currently authoring "Applied Artificial Intelligence: Getting Started with AI in Python" for Packt Publishing, and he is the host of the "HumAIn Podcast", a speaker series that explores practical ways to bridge the gap between humans and machines in the Age of Accelerated learning.