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Columbus, United States · Study online with LSBA

Aprendizaje Automático Para Finanzas

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Overview

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Learning outcomes

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Course content

1

Fundamentos De Aprendizaje Automático En Finanzas

2

Modelos Predictivos De Riesgo De Crédito

3

Análisis De Series Temporales Financieras

4

Algoritmos De Trading Algorítmico

5

Interpretabilidad Y Ética En Modelos Financieros

Career Path

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Key facts

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Why this course

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Everything you need to know before you start

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We offer immediate access to our course materials through our open enrollment system. This means:

  • The course starts as soon as you pay the course fee, instantly
  • No waiting periods or fixed start dates
  • Instant access to all course materials upon payment
  • Flexibility to begin at your convenience

This self-paced approach allows you to begin your professional development journey immediately, fitting your learning around your existing commitments.

We offer two flexible learning paths to suit your schedule:

  • Fast Track: Complete in 1 month with 3-4 hours of study per week
  • Standard Mode: Complete in 2 months with 2-3 hours of study per week

You can progress at your own pace and access the materials 24/7.

There are no formal entry requirements for this course. You just need:

  • A good command of English language
  • Access to a computer/laptop with internet
  • Basic computer skills
  • Dedication to complete the course
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Assessment is done through:

  • Multiple-choice questions at the end of each unit
  • You need to score at least 60% to pass each unit
  • You can retake quizzes if needed
  • All assessments are online

Upon successful completion, you will receive:

  • A digital certificate from London School of Business and Administration
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
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Why people choose us for their career

Trusted by professionals worldwide

Verified outcomes from learners who finished the course and put it to work.

4.8
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United States
MC
Michael Carter
US · Course completed

The professional structure of Aprendizaje Automático Para Finanzas matched my learning goals perfectly. The modules on time‑series forecasting allowed me to build a Python model that predicts daily stock price movements with an R‑squared of 0.78, which I immediately applied to my personal portfolio. The course materials—especially the annotated Jupyter notebooks and the case studies on credit‑risk scoring—were up‑to‑date and directly relevant to current market practices. I finished the course feeling confident to present a data‑driven risk‑assessment report to my finance team, and I would highly recommend it to anyone seeking rigorous, applicable ML skills in finance.

LS
Lucas Silva
BR · Course completed

Adorei o curso! O jeito descontraído do professor fez tudo ficar bem fácil de entender. Aprendi a usar o Scikit‑learn para criar modelos de classificação de crédito e já consegui melhorar a taxa de aprovação dos clientes no meu estágio. Os slides são bem organizados e os exercícios práticos com dados reais do mercado brasileiro foram o ponto alto. Saí do curso com um notebook pronto para analisar risco de investimento e me sinto muito mais preparado para o próximo desafio profissional.

FW
Felix Wagner
DE · Course completed

Wow! This course blew me away with its enthusiasm and depth. The lesson on neural networks for option pricing gave me the exact code to implement a LSTM model that now predicts implied volatility with impressive accuracy. The video lectures are clear, and the supplementary PDFs contain the latest research papers in Spanish and English, which helped me stay on the cutting edge. After finishing, I was able to present a prototype of an automated trading strategy to my university project group, and everyone was amazed. Absolutely thrilled with the learning experience!

RK
Rahul Kapoor
IN · Course completed

The detailed approach of Aprendizaje Automático Para Finanzas left no stone unturned. Each chapter begins with a thorough theoretical overview—such as the bias‑variance trade‑off in financial regression—followed by step‑by‑step coding labs. I particularly valued the segment on portfolio optimization using reinforcement learning; the provided R script allowed me to back‑test a strategy that outperformed the benchmark by 3.5% over a year. The course materials are impeccably curated, with real‑world datasets from Bloomberg and clear explanations of every algorithm. My overall experience was exceptional, and I now feel equipped to lead ML‑driven finance projects at my firm.

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Skills gained

Risk Modeling
Portfolio Optimization
Time Series
Predictive Analytics
These skills will be developed throughout the course


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Taught in English

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Recently updated!

May 2026