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Aprendizado De Máquina

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Overview

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Learning outcomes

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Course content

1

Introdução Ao Aprendizado De Máquina

2

Técnicas De Previsão

3

Redes Neurais Artificiais

4

Aprendizado De Máquina Não Supervisionado

5

Técnicas De Mineração De Dados

Career Path

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Key facts

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Why this course

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People also ask

Everything you need to know before you start

Straight answers — no waiting on a reply. Most learners are enrolled within 60 seconds of finding what they need below.

60 sec
From enrol to start
24/7
Course access
Self-paced
Learn on your time
Certificate
Included in fee

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
Ready when you are
Most learners finish reading the FAQs and enrol in the same minute.
Self-paced · Certificate included · 24/7 access · 60-second start.
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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
Open enrolment · Start today

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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'm blown away by the 'Aprendizado De Máquina' course at Stanmore School of Business! As a data scientist in the US, I was looking to upskill in machine learning, and this course exceeded my expectations. The content was incredibly comprehensive, covering everything from supervised and unsupervised learning to deep learning and neural networks. I particularly appreciated the practical examples and case studies, which helped me understand how to apply these concepts to real-world problems. The course materials were top-notch, with video lectures, quizzes, and assignments that kept me engaged throughout. I achieved my learning goals and gained valuable skills that I've already applied in my job. The instructors were knowledgeable and responsive, and the online community was supportive and active. I highly recommend this course to anyone looking to boost their machine learning skills!

LH
Leila Hassan
EG · Course completed

I recently completed the 'Aprendizado De Máquina' course at Stanmore School of Business, and I must say it was a great experience! As a software engineer in Egypt, I was interested in learning more about machine learning and its applications. The course content was well-structured and easy to follow, with a good balance of theory and practice. I appreciated the examples and exercises, which helped me understand the concepts better. The course materials were relevant and up-to-date, and the instructors were helpful and responsive. One thing that I found particularly useful was the section on natural language processing, which I've been able to apply in my work. Overall, I'm satisfied with the course and would recommend it to others who want to learn about machine learning.

KN
Kaito Nakamura
JP · Course completed

Wow, what an amazing course! I'm so glad I took the 'Aprendizado De Máquina' course at Stanmore School of Business. As a student in Japan, I was looking for a comprehensive introduction to machine learning, and this course delivered. The content was incredibly detailed and covered everything from the basics to advanced topics like reinforcement learning and computer vision. I loved the interactive quizzes and assignments, which made learning fun and engaging. The course materials were superb, with video lectures, slides, and readings that were all relevant and useful. I gained a deep understanding of machine learning concepts and was able to apply them to projects and assignments. The instructors were knowledgeable and enthusiastic, and the online community was supportive and motivating. I'm so happy with the course and would highly recommend it to anyone interested in machine learning!

CS
Catarina Silva
BR · Course completed

I had a great experience with the 'Aprendizado De Máquina' course at Stanmore School of Business! As a data analyst in Brazil, I was looking to improve my skills in machine learning, and this course helped me achieve my goals. The content was well-organized and easy to follow, with a good mix of theory and practice. I appreciated the examples and case studies, which helped me understand how to apply machine learning concepts to real-world problems. The course materials were relevant and up-to-date, and the instructors were helpful and responsive. One thing that I found particularly useful was the section on clustering and dimensionality reduction, which I've been able to apply in my work. Overall, I'm satisfied with the course and would recommend it to others who want to learn about machine learning. The only thing I would suggest is adding more exercises and projects to help students practice and reinforce their learning.





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Recently updated!

May 2026