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London, United Kingdom · Study online with LearnUNI

Applied Machine Learning

Postgraduate Certificate in Applied Machine Learning: 12-month course; gain practical skills in ML algorithms, data analysis, deep learning
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2 months to complete
at 2-3 hours a week

Overview

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Learning outcomes

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Course content

1

Machine Learning Fundamentals

2

Data Preprocessing Techniques

3

Model Evaluation Metrics

4

Deep Learning Applications

5

Natural Language Processing

Career Path

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Key facts

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Why this course

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People also ask

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

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.

During your course, you will have access to:

  • 24/7 access to course materials and resources
  • Technical support for platform-related issues
  • Email support for course-related questions
  • Clear course structure and learning materials

Please note that this is a self-paced course, and while we provide the learning materials and basic support, there is no regular feedback on assignments or projects.

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 LearnUNI
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee

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

  • The course starts as soon as you pay 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.

Our course is designed as a comprehensive self-study program that offers:

  • Structured learning materials accessible 24/7
  • Comprehensive course content for self-paced study
  • Flexible learning schedule to fit your lifestyle
  • Access to all necessary resources and materials

This self-directed learning approach allows you to progress at your own pace, making it ideal for busy professionals who need flexibility in their learning schedule. While there are no live classes or practical sessions, the course materials are designed to provide a thorough understanding of the subject matter through self-study.

This course provides knowledge and understanding in the subject area, which can be valuable for:

  • Enhancing your understanding of the field
  • Adding to your professional development portfolio
  • Demonstrating your commitment to learning
  • Building foundational knowledge in the subject
  • Supporting your existing career path

Please note that while this course provides valuable knowledge, it does not guarantee specific career outcomes or job placements. The value of the course will depend on how you apply the knowledge gained in your professional context.

This program is designed to provide valuable insight and information that can be directly applied to your job role. However, it is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. Additionally, it should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/body.

What you will gain from this course:

  • Knowledge and understanding of the subject matter
  • A certificate of completion to showcase your commitment to learning
  • Self-paced learning experience
  • Access to comprehensive course materials
  • Understanding of key concepts and principles in the field

While this course provides valuable learning opportunities, it should be viewed as complementary to, rather than a replacement for, formal academic qualifications.

Our course offers a focused learning experience with:

  • Comprehensive course materials covering essential topics
  • Flexible learning schedule to fit your needs
  • Self-paced learning environment
  • Access to course content for the duration of your enrollment
  • Certificate of completion upon finishing the course

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 Applied Machine Learning course at Stanmore School of Business! As a data scientist in the US, I was looking to upskill and this course delivered. The instructor's explanations of supervised and unsupervised learning algorithms were crystal clear, and the assignments helped me gain practical experience with popular libraries like scikit-learn and TensorFlow. I appreciated how the course materials were tailored to real-world applications, making it easy to see the relevance to my work. The quality of the course was top-notch, and I'm so satisfied with what I learned - I've already applied my new skills to a project at work and seen significant improvements in our predictive models!

LH
Leila Hassan
EG · Course completed

I found the Applied Machine Learning course to be quite informative and helpful in achieving my learning goals. The course covered a wide range of topics, from the basics of machine learning to more advanced subjects like deep learning and natural language processing. I appreciated the variety of examples and case studies used to illustrate key concepts, which made the material more engaging and easier to understand. The course materials were of good quality, although I felt that some of the assignments could have been more challenging. Overall, I'm satisfied with what I learned and feel more confident in my ability to apply machine learning techniques to real-world problems.

CS
Catarina Silva
BR · Course completed

Wow, just wow! The Applied Machine Learning course at Stanmore School of Business exceeded my expectations in every way! The instructor was knowledgeable, enthusiastic, and always available to answer questions. The course content was incredibly comprehensive, covering everything from data preprocessing to model deployment. I loved the hands-on approach, with plenty of opportunities to practice and apply what I learned. The assignments were challenging but rewarding, and I appreciated the feedback from the instructor and peers. I gained so much practical knowledge and skills from this course, and I'm excited to apply them to my work in the field. The course materials were excellent, and I appreciated the emphasis on ethical considerations in machine learning - it's so important to think about the impact of our work on society.

KN
Kaito Nakamura
JP · Course completed

I recently completed the Applied Machine Learning course at Stanmore School of Business, and I must say it was a valuable learning experience. The course provided a thorough introduction to machine learning, including the fundamentals of programming languages like Python and R. I appreciated the detailed explanations of key concepts, such as regression, classification, and clustering, as well as the examples of how to implement them using popular libraries. The course materials were well-organized and easy to follow, although I felt that some of the topics could have been explored in more depth. Overall, I'm satisfied with what I learned, and I feel more confident in my ability to apply machine learning techniques to solve complex problems. One area for improvement could be more discussion of recent advancements in the field, such as Explainable AI and Transfer Learning.





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Taught in English

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Recently updated!

April 2026