The virtual course "Fundamentals of machine learning in finance - Virtual Course - Coursera", is a course with different contents and offers video classes of Approx. 18 hours to complete. Explore its essential features, and click the orange button for detailed information on the Coursera e-Learning platform.
The course aims to help students to be able to solve practical ML amenable problems they may encounter in real life including: (1) understanding where the problem one is facing lies in an overview of available ML methods , (2) understanding which particular ML approaches would be most appropriate to solve the problem, and (3) the ability to successfully implement a solution and evaluate its performance. A student with some or no prior knowledge of Machine Learning (ML) will be familiar with the main algorithms for supervised and unsupervised learning, and reinforcement learning, and will be able to use open source ML Python packages to design, test, and implement ML algorithms. In finance. Fundamentals of Machine Learning in Finance will provide a more detailed look at supervised, unsupervised, and reinforcement learning. and finish in a project on using unsupervised learning to implement a simple portfolio trading strategy. The course is designed for three categories of students: Professionals working in financial institutions such as banks, asset management firms, or hedge funds Individuals interested in ML applications for personal day trading Current full-time students seeking a Bachelor's 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 required to complete assignments in this course.
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