Course information

Recommendation System Training Course Outline

Module 1: Introduction to Recommender Systems

  • What is Recommender System?
  • Types of Recommender Systems
  • How Recommender System Works?
  • Challenges of Recommender System

Module 2: Collaborative Recommendation Approaches

  • Memory Based Approaches
  • Model-Based Approach
  • Python Implementation

Module 3: Content Based Recommendation

  • What is Content-Based Recommendation System?
  • User Profile
  • Item Profile
  • Utility Matrix

Module 4: Hybrid Recommendation

  • Hybridisation Recommendation System
  • Monolithic Hybridisation Design
  • Parallelised Hybridisation Design
  • Pipeline Hybridisation Design

Module 5: Evaluating Recommender Systems

  • Evaluation Methods
    • Experimental (Online Experiments)
    • Non-Experimental (Offline Experiments)
    • Simulation Experiments
  • Common Metrices

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Who should attend this Recommendation System Training Course?

The Recommendation System Course is tailored for individuals working in the data science and analytics field to help them understand and implement recommendation algorithms effectively. The following are some professionals for whom this course can be beneficial:

  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • Software Developers
  • Product Managers
  • Business Analysts
  • UX/UI Designers

Prerequisites of the Recommendation System Training Course

There are no formal prerequisites for this Recommendation System Course.

Recommendation System Training Course Overview

Recommendation systems are integral to many online platforms, providing personalised suggestions to users and enhancing their experience. By analysing user data and behaviour, recommendation systems help businesses increase engagement and drive sales through tailored content delivery.

Proficiency in building and optimising recommendation systems is crucial for Data Scientists, Machine Learning Engineers, and other professionals involved in data analysis and product development. Mastering recommendation algorithms and techniques enables these professionals to create systems that understand user preferences, predict user behaviour, and provide relevant recommendations.

This intensive 1-day course equips delegates with fundamental concepts and practical skills in developing recommendation systems. Through hands-on workshops and expert-led sessions, delegates gain a comprehensive understanding of collaborative filtering, content-based filtering, and hybrid recommendation approaches. Delegates learn to implement recommendation algorithms, evaluate their performance, and optimise them for diverse real-world applications.

Course Objectives

  • To understand the foundational principles of recommendation systems and their importance
  • To explore various recommendation techniques, including collaborative filtering and content-based filtering
  • To apply machine learning algorithms in developing recommendation systems
  • To analyse and interpret recommendation system outputs for improved user experience
  • To optimise recommendation algorithms for better accuracy and performance
  • To comprehend ethical considerations in deploying recommendation systems

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise recommendation systems, making them invaluable assets in their professional fields.

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What’s included in this Recommendation System Training Course?

  • World-Class Training Sessions from Experienced Instructors 
  • Recommendation System Certificate 
  • Digital Delegate Pack

Why choose us

Our Edmonton venue

Includes..

Free Wi-Fi

To make sure you’re always connected we offer completely free and easy to access wi-fi.

Air conditioned

To keep you comfortable during your course we offer a fully air conditioned environment.

Full IT support

IT support is on hand to sort out any unforseen issues that may arise.

Video equipment

This location has full video conferencing equipment.

Edmonton is the capital city of the province of Alberta in Canada. It’s the second largest city in Alberta and the fifth in Canada, with a population of around 850,000 people. Edmonton is known as ‘Canada’s Festival City’ for the fact is hosts a large amount of festivals over the year. Edmonton is the centre of a number of large oil sands projects and diamond mining activities occurring in the northwest territories of Canada. There are two English school boards in Edmonton and one French school board which govern the public schools. There are also a large amount of private schools, not governed by any board, and many parents choose to home-school their children. Schools in Edmonton are funded by property taxes and a large number of provincial grants but also provide resources and support for those who home-school or are home-schooled. There are six universities in Edmonton; Concordia University College of Alberta, MacEwan University, The King's University College, NorQuest College, Northern Alberta Institute of Technology (NAIT) and the University of Alberta, providing a large amount of degrees and programs for students. The largest is the University of Alberta and educates up for 40,000 students on around 400 programs. The second in the MacEwan University which caters to around 40,000 students, 14,000 of these being full-time. This university provides degrees, diplomas and certificates in a wide number of programs. Miscellaneous educational institutions include Taylor University College and Seminary and the Yellowhead Tribal College, which is a First Nations college.

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Address

Intelligent Office
Scotia Place
Tower 1,
10060 Jasper Avenue
Suite 2020 (20th Floor)
Edmonton
Alberta
T5J 3R8

T: +1 6474932992

Ways to take this course

Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Recommendation System Training in Edmonton. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

Unlock your potential with The Knowledge Academy's Recommendation System Training in Edmonton, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.

Streamline large-scale training requirements with The Knowledge Academy's In-house/Onsite at your business premises. Experience expert-led classroom learning from the comfort of your workplace and engage professional development.

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Tailored learning experience

Leverage benefits offered from a certification that fits your unique business or project needs

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Maximise your training budget

Cut unnecessary costs and focus your entire budget on what really matters, the training.

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Team building opportunity

Our offers a unique chance for your team to bond and engage in discussions, enriching the learning experience beyond traditional classroom settings

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Monitor employees progress

The course know-how will help you track and evaluate your employees' progression and performance with relative ease

What our customers are saying

Recommendation System Training in Edmonton FAQs

Please arrive at the venue at 8:45am.
The training fees for Recommendation System Trainingin Edmonton starts from CAD3395
The Knowledge Academy is the Leading global training provider for Recommendation System Training.
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Why choose us

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Best price in the industry

You won't find better value in the marketplace. If you do find a lower price, we will beat it.

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Many delivery methods

Flexible delivery methods are available depending on your learning style.

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High quality resources

Resources are included for a comprehensive learning experience.

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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water

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