ML & Reinforcement Learning in Finance Specialization
Reinforce Your Career: The Role of Machine Learning in Finance. Enhance your understanding of the algorithms and instruments required to forecast financial markets.
Description for ML & Reinforcement Learning in Finance Specialization
Features of Course
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by New York University
Duration: 2 months at 10 hours a week
Schedule: Flexible
Pricing for ML & Reinforcement Learning in Finance Specialization
Use Cases for ML & Reinforcement Learning in Finance Specialization
FAQs for ML & Reinforcement Learning in Finance Specialization
Reviews for ML & Reinforcement Learning in Finance Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML & Reinforcement Learning in Finance Specialization
Finbots, an AI-powered credit modeling solution, empowers financial institutions with rapid and precise credit risk management, enhancing lending decisions and reducing risk through its comprehensive platform and AI algorithms.
In less than six months, acquire skills that are in high demand, including machine learning, regression models, Python, and statistical analysis.
Learn to identify suitable applications for machine learning, integrate human-centered design principles for privacy and ethical considerations in AI product development, and lead machine learning projects following data science methodology and industry standards.
Learn Python, analyze and visualize data, and apply your skills to data science and machine learning with a practical assignment to acquire hands-on skills for a career in data science.
Featured Tools
Learn to leverage Google Cloud's data-to-AI tools, generative AI capabilities, and Vertex AI for comprehensive ML model development.
Optimize and interpret machine learning functions using gradients, derivatives, and gradient descent in neural networks.
Gain hands-on experience and comprehensive knowledge of GenAI, emphasizing critical thinking and leveraging AI to enhance idea development and prepare for the future of work.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Understand the benefits, functioning, use cases, and applications of Amazon Bedrock in generative AI.