Using Machine Learning in Trading and Finance
With an emphasis on quantitative, pairs, and momentum trading, this course prepares students to create and backtest sophisticated trading strategies utilizing machine learning.
Description for Using Machine Learning in Trading and Finance
Fundamentals of Trading Strategies: Examines essential elements of trading strategies, ranging from basic to intricate models.
Diverse Trading Techniques: Includes quantitative, pairs trading, and momentum trading strategies, providing a comprehensive approach to machine learning in finance.
Model Building and Backtesting: Directs learners in constructing machine learning models for trading utilizing Keras and TensorFlow, and imparts knowledge on backtesting pair trading and momentum-driven models.
Prerequisites: Requires proficient Python skills, knowledge of machine learning libraries (Scikit-Learn, StatsModels, Pandas), SQL proficiency, and a comprehensive understanding of statistics and financial markets.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by New York Institute of Finance & Google CloudDuration: 18 hours (approximately)
Schedule: Flexible
Pricing for Using Machine Learning in Trading and Finance
Use Cases for Using Machine Learning in Trading and Finance
FAQs for Using Machine Learning in Trading and Finance
Reviews for Using Machine Learning in Trading and Finance
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Using Machine Learning in Trading and Finance
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
This training provides professionals with knowledge and practical advice on AI ethics, compliance issues, and risk management.
Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.
Develop expertise in the exposure and deployment of large language models via application programming interfaces (APIs), configure server environments, and incorporate natural language processing (NLP) functionalities into applications.
Learn proficiency in the construction, deployment, and safeguarding of large language models at scale, utilizing Rust, Amazon Web Services (AWS), and established DevOps best practices.
This course is dedicated to the setting up of GPU-based environments, the deployment of local large language models (LLMs), and their integration into Python applications utilizing open-source tools.
In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.
Gain an extensive understanding of TinyML applications, fundamental principles, and the ethical development of artificial intelligence.
Learn the skills necessary to operate, optimize, and implement large language models through practical experience with state-of-the-art LLM architectures and open-source resources.
Learn how to use AI technologies for personal development and active learning, embrace continuous learning, and cultivate a growth mindset.
Featured Tools
Explore the world of AI-powered language processing by acquiring the skills necessary to construct chatbots, analyze sentiment, and incorporate AI insights into practical applications.
In order to balance or improve the integration of AI in education, this course examines conversational AI technologies and provides evaluation designs.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
Explore the topic of AI-powered personalization by acquiring the skills necessary to utilize LangChain and ChatGPT.
Preparing students for a future in artificial intelligence security, this course offers AI hacking, vulnerability discovery, and attack mitigating techniques.
Compare & Review AI Tool Directory AI Course Marketplace
