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Introduction to Cyber Attacks
This course provides learners with a baseline understanding of common cyber security threats, vulnerabilities, and risks.
19 h
Guided Tour of Machine Learning in Finance
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course.
24 h
Introduction to Networking
This is a self-paced course from NYU that provides an Introduction to Networking
1176 h
Fundamentals of Machine Learning in Finance
The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life.
18 h
Cyber Attack Countermeasures
This course introduces the basics of cyber defense starting with foundational models such as Bell-LaPadula and information flow frameworks.
19 h
Real-Time Cyber Threat Detection and Mitigation
This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites.
15 h
Overview of Advanced Methods of Reinforcement Learning in Finance
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance.
13 h
Information Visualization: Foundations
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization.
12 h
Information Visualization: Programming with D3.js
In this course you will learn how to use D3.js to create powerful visualizations for web.
18 h
Engineering Health: Introduction to Yoga and Physiology
Learn Engineering Health: Introduction to Yoga and Physiology from New York University Tandon School of Engineering. This course gives you access to an exploration of physiological systems from the perspective of overall health and wellness.
27 h
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