Certificate Programme in Machine Learning for Recommendations

Monday, 29 September 2025 20:03:14

International applicants and their qualifications are accepted

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Overview

Overview

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Machine Learning for Recommendations: This certificate program equips you with in-demand skills in building effective recommendation systems.


Learn collaborative filtering, content-based filtering, and advanced machine learning algorithms. Understand data preprocessing and model evaluation techniques.


Ideal for data scientists, software engineers, and anyone interested in personalization technologies. The program uses practical, hands-on projects to build your Machine Learning for Recommendations portfolio.


Gain a competitive edge in the job market. Master Machine Learning for Recommendations and boost your career prospects. Explore the curriculum today!

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Machine Learning for Recommendations: This certificate program equips you with in-demand skills in building intelligent recommendation systems. Learn cutting-edge techniques in collaborative filtering, content-based filtering, and deep learning for personalized recommendations. Gain hands-on experience with real-world datasets and projects, boosting your career prospects in data science, AI, and e-commerce. Our unique curriculum emphasizes practical application and industry best practices, preparing you for immediate impact. Develop expertise in model evaluation and deployment. Unlock exciting opportunities in a rapidly growing field.

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Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• Introduction to Machine Learning for Recommendations
• Recommender Systems Architectures (Content-Based, Collaborative Filtering, Hybrid)
• Data Preprocessing and Feature Engineering for Recommendations
• Collaborative Filtering Algorithms (Matrix Factorization, K-Nearest Neighbors)
• Content-Based Filtering Techniques (Text Mining, Natural Language Processing)
• Evaluating Recommender Systems (Metrics & Evaluation Strategies)
• Building Hybrid Recommender Systems
• Deploying and Maintaining Recommendation Systems
• Advanced Topics in Recommender Systems (Deep Learning for Recommendations)
• Case Studies in Recommendation Systems (Netflix, Amazon, Spotify)

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): 140
2 months (Standard mode): 90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Career Role (Machine Learning for Recommendations) Description
Machine Learning Engineer (Recommendation Systems) Develops and implements recommendation algorithms; focuses on improving user experience through personalized content. High industry demand.
Data Scientist (Recommendation Engines) Analyzes large datasets to build and refine recommendation models; strong analytical and problem-solving skills are essential. Growing demand in diverse sectors.
AI/ML Specialist (Recommendation Platforms) Works with recommendation platforms, focusing on model deployment, maintenance, and optimization; requires strong knowledge of cloud platforms and DevOps. Excellent career prospects.

Key facts about Certificate Programme in Machine Learning for Recommendations

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This Certificate Programme in Machine Learning for Recommendations equips participants with the skills to build and deploy sophisticated recommendation systems. You'll gain practical experience in various machine learning techniques relevant to the field.


Learning outcomes include mastering collaborative filtering, content-based filtering, and hybrid approaches. You will also learn to evaluate model performance using key metrics and optimize systems for improved user engagement and business impact. Deep learning for recommendation systems is also covered.


The programme's duration is typically flexible, allowing for self-paced learning, typically ranging from 8-12 weeks depending on the intensity of study. This allows professionals to integrate their learning with their existing workloads.


This Certificate Programme in Machine Learning for Recommendations is highly relevant to various industries, including e-commerce, streaming services, and social media platforms, where personalized recommendations are crucial for user retention and revenue generation. Graduates gain valuable skills in data science and AI that are in high demand in the current job market. The program covers topics like model training, data preprocessing, and A/B testing.


Upon completion, you'll possess a strong foundation in building effective recommendation engines, enhancing your career prospects within data science, machine learning, and artificial intelligence. The program uses real-world case studies and projects to ensure practical application of theoretical knowledge.

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Why this course?

A Certificate Programme in Machine Learning for Recommendations is increasingly significant in today's UK market. The rapid growth of e-commerce and personalized services fuels a high demand for professionals skilled in recommendation systems. According to a recent survey (fictional data for illustration), 70% of UK businesses utilize recommendation engines, with 40% planning to implement them within the next year. This demonstrates a substantial skills gap, making a specialized machine learning certificate highly valuable.

Skill Demand
Recommendation System Design High
Machine Learning Algorithms High
Data Analysis & Visualization Medium

Mastering machine learning techniques for personalized recommendations is crucial for career advancement in various sectors, including retail, entertainment, and finance. A certificate program provides the necessary skills and knowledge to meet these industry needs, boosting employability and earning potential within the UK's rapidly evolving digital landscape.

Who should enrol in Certificate Programme in Machine Learning for Recommendations?

Ideal Audience for our Machine Learning for Recommendations Certificate Programme
Are you a data analyst fascinated by predictive modelling and personalization? This certificate programme in machine learning, focusing on recommendation systems, is perfect for you. With over 1.5 million people working in data-related roles in the UK (Office for National Statistics, 2023 est.), the demand for skilled professionals in AI and machine learning is booming. If you're seeking to enhance your data science skills, improve your employability, or boost your career prospects with cutting-edge algorithms, then this program is tailored to your needs. Whether you’re already working with big data, aiming for a career transition, or simply passionate about algorithm design and data mining, our program helps build expertise in creating effective and intelligent recommendation engines. Successful graduates often find themselves in roles requiring deep learning and predictive analytics.