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Certificado Profesional En Minería De Datos (Avanzado) (Advanced)

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Overview

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Learning outcomes

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Course content

1

Introducción A La Minería De Datos

2

Preprocesamiento De Datos

3

Análisis Exploratorio De Datos

4

Técnicas De Minería De Datos

5

Árboles De Decisión

6

Redes Neuronales Artificiales

7

Algoritmos Genéticos

8

Minería De Textos

9

Visualización De Datos

10

Análisis De Clustering

11

Análisis De Regresión

12

Análisis De Series De Tiempo

13

Minería De Datos No Estructurados

14

Minería De Datos Estructurados

15

Aplicaciones De Minería De Datos

16

Integración De Datos

17

Calidad De Datos

18

Gestión De Datos

19

Análisis De Supervivencia

20

Análisis De Componentes Principales

Career Path

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Key facts

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Why this course

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People also ask

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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.

4.5
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

I recently completed the Certificado Profesional En Minería De Datos (Avanzado) course at Stanmore School of Business, and I'm blown away by the quality of the content. As a data analyst in the United States, I was looking to upgrade my skills in data mining, and this course exceeded my expectations. The course materials were engaging, relevant, and perfectly paced. I particularly appreciated the hands-on exercises and real-world examples that helped me grasp complex concepts like clustering and decision trees. The instructors were knowledgeable and responsive, and the online platform was user-friendly. I've already applied the skills I learned to a project at work, and the results have been impressive. I highly recommend this course to anyone looking to advance their career in data science.

LH
Leila Hassan
EG · Course completed

I took the Certificado Profesional En Minería De Datos (Avanzado) course to improve my data analysis skills, and I'm really satisfied with the outcome. The course covered a wide range of topics, from data preprocessing to machine learning, and the instructors did a great job of explaining the concepts in a clear and concise manner. I liked that the course included plenty of practical examples and case studies, which made it easier to understand the theoretical concepts. One thing that I found particularly useful was the section on data visualization - I learned how to create interactive dashboards using Tableau, which has been a game-changer for my work. The course materials were well-organized, and the discussion forums were active and helpful. Overall, I think this course is a great investment for anyone looking to boost their career in data science.

KN
Kaito Nakamura
JP · Course completed

Wow, just wow! The Certificado Profesional En Minería De Datos (Avanzado) course at Stanmore School of Business was an incredible experience. I was a bit skeptical at first, but the course totally exceeded my expectations. The instructors were super knowledgeable and passionate about the subject, and the course materials were top-notch. I loved the interactive exercises and quizzes - they really helped me stay engaged and motivated throughout the course. One of the most valuable things I learned was how to work with large datasets using Python and Pandas - it's been a total game-changer for my work. The course also covered some really advanced topics, like deep learning and natural language processing, which I found fascinating. I've already recommended this course to my friends and colleagues - it's a must-take for anyone serious about data science.

AS
Ana Silva
BR · Course completed

I completed the Certificado Profesional En Minería De Datos (Avanzado) course at Stanmore School of Business, and I'm really happy with the results. As a marketing analyst in Brazil, I was looking to improve my skills in data analysis and machine learning, and this course helped me achieve my goals. The course materials were comprehensive and well-structured, and the instructors were helpful and responsive. I appreciated the focus on practical applications - the course included plenty of real-world examples and case studies, which made it easier to understand the theoretical concepts. One thing that I found particularly useful was the section on predictive modeling - I learned how to build and deploy predictive models using R and Python, which has been really valuable for my work. The course also covered some really interesting topics, like text mining and social media analytics, which I found fascinating. Overall, I think this course is a great choice for anyone looking to advance their career in data science.





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Recently updated!

May 2026