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
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.
The goal of this course is to provide professionals with the necessary data science abilities in MATLAB so that they can carry out practical activities in businesses that rely heavily on data without having to learn extensive programming.
Using the complete machine learning pipeline in computer vision, this course teaches students how to use MATLAB for object detection and classification in images.
This introductory course examines machine learning applications in finance, culminating in a capstone project focused on predicting bank closures.
Gain a comprehensive understanding of NLP, machine learning, deep learning (including TensorFlow, CNNs, RNNs, and LSTMs), and deep learning to facilitate the development of models and data analysis.
Obtain proficiency in the extension of the TensorFlow framework, the deployment of models to the Cloud ML Engine, and the repeatable evaluation of predictive models.
Featured Tools
Explore innovative AI technologies through practical applications, thereby fostering industry-specific applications and innovation.
The topics of this AI course include the optimization of policies in reinforcement learning, the utilization of dimensionality reduction in unsupervised learning, and the classification and definition of constraints in supervised learning.
Investigate the objectives and advantages of Google's Big Data and Machine Learning products, including the use of BigQuery for interactive analysis, Cloud SQL, and Dataproc for migrating MySQL and Hadoop applications, and the selection of a variety of data processing tools on Google Cloud.
Accelerate your career in data analytics. In this certificate program, you will acquire skills that are in high demand at your own tempo, regardless of your degree or experience.
This course will provide you with an understanding of the technical underpinnings and essential terminology associated with generative artificial intelligence (AI).