The Introduction to Python covers the basic Python programming.
job support and financing available
Individual data science Classes
The class will introduce you to a wide range of machine learning tools in Python. The main focus is on the concepts, methods, and applications of the general predictive modeling and unsupervised learning and how they are implemented in the Python language environment. The goal is to understand how to use these tools to solve real world problems. After this course you will be able to carry out your experiments with the public available algorithms or develop your own algorithm.
Students will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python
Luke holds a PhD in Mathematics at Stony Brook University, specialized in partial differential equations. As a lifelong learner of mathematics, he is extremely efficient in quantitative analysis and also skilled at communicating abstract concepts. With proficiency in R and Python, Luke is primed to be a major asset to any analytic force. Being extremely passionate to share the insight of the data from variety of industries, Luke looks forward to meeting talented students from all kinds of background here in NYC Data Science Academy.
Aiko grew up in Taiwan where he studied Mathematics and Physics in college. He then moved to the United States to obtain his PhD in Mathematics at Harvard. After finishing his degree, Aiko conducted research and taught at M.I.T and U.C Berkeley for nine years before moving into the world of finance. He worked in the hedge fund industry on quantitative trading for a decade before diving into Data Science full time. Aiko enjoys programming and using machine learning algorithms for industrial research. When at home he enjoys reading books on a really, really wide variety of topics.
The class will introduce you to a wide range of machine learning tools in Python.