Artificial Intelligence in Finance

Course Content:

Introduction to Artificial Intelligence in Finance:
Definition of artificial intelligence and its impact on the financial sector.
Main applications of AI in finance, including risk analysis, algorithmic trading and investment management.

Fundamentals of AI and Machine Learning:
Basic concepts of AI and machine learning, including supervised, unsupervised and reinforcement learning algorithms.
Key tools and techniques used in AI, such as neural networks, decision trees and clustering techniques.

Predictive Analytics in Finance:
Development and application of predictive models to forecast asset prices, identify investment opportunities and manage risks.
Use of advanced techniques such as time series analysis, recurrent neural networks (RNN) and autoregression models.

Trading Automation and Investment Algorithms:
Implementation of automated trading algorithms for trade execution and optimization of investment strategies.
Analysis of quantitative trading techniques and the use of AI to improve real-time decision making.

Risk Analysis and Portfolio Management:
Application of AI for the assessment and management of financial risks, including credit analysis, market risks and operational risks.
Development of portfolio management models using optimization and forecasting techniques to maximize risk-adjusted return.

Fraud Detection and Financial Security:
Implementation of AI systems for the detection of fraud and anomalies in financial transactions.
Use of machine learning techniques to identify suspicious patterns and protect against cyber threats.

Natural Language Processing (NLP) in Finance:
Application of natural language processing techniques for the analysis of unstructured data, such as financial reports, news and social networks.
Use of NLP for key information extraction and sentiment analysis affecting financial markets.

Regulation and Compliance in Financial AI:
Understanding of regulations and regulations affecting the use of AI in finance, including data protection and privacy.
Developing strategies to ensure compliance and transparency in the use of AI in financial applications.

Development of AI Projects in Finance:
Creation and management of specific AI projects for the financial sector, from conception to implementation.
Analysis of case studies and real projects in the financial field to apply acquired knowledge.

Final Project:
Participants will develop a comprehensive project using AI to solve a real or simulated financial problem, applying the techniques and tools learned during the course.
The project will be presented to a panel of experts for feedback and recommendations.

Additional Benefits:

Certification in Artificial Intelligence in Finance:
Upon completion of the course, you will receive an industry-recognized certification that validates your ability to apply AI in the financial context.

Access to Exclusive Tools and Resources:
You’ll get access to AI platforms and specialized software, financial databases and additional educational resources to enrich your learning.

Mentoring and Networking:
During the course, you will have the opportunity to interact with expert mentors in AI and finance, as well as participate in networking events with other industry professionals.

Course Duration: 6 months

Modality: 100% online, with live sessions and access to recorded content.