Recommendation System Training in Virtual

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

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. However, a basic understanding of Python programming and Machine Learning concepts can be beneficial for delegates.

Recommendation System Training Course Overview

The Recommendation System Course provides an introduction to the principles and techniques used to build Recommendation Systems for personalised user experiences. It covers collaborative filtering, content-based recommendation, hybrid recommendation methods, and evaluation techniques.

Delegates will gain knowledge of Recommendation System concepts while developing skills in creating user and item profiles, implementing recommendation models using Python, designing hybrid approaches, and evaluating system performance.

This 1-Day course by The Knowledge Academy enables delegates to apply Recommendation System techniques, assess recommendation performance, and support the development of personalised, data-driven solutions across a range of applications.

Recommendation System Training 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.

What’s Included in this Recommendation System Training Course?

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