Search result for Courses taught by Joseph A Konstan
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Recommender Systems: Evaluation and Metrics
by Michael D. Ekstrand , Joseph A Konstan- 4.4
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Approx. 7 hours to complete
In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals....
Recommender Systems Capstone
by Michael D. Ekstrand , Joseph A Konstan- 0.0
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Approx. 3 hours to complete
This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance....
Introduction to UI Design
by Loren Terveen , Haiyi Zhu , Lana Yarosh , Dr. Brent Hecht , Joseph A Konstan- 4.7
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Approx. 14 hours to complete
In this course, you will gain an understanding of the critical importance of user interface design. You will also learn industry-standard methods for how to approach the design of a user interface and key theories and frameworks that underlie the design of most interfaces you use today. You will then gain a high-level understanding of the user-interface design process....
User Research and Design
by Loren Terveen , Haiyi Zhu , Lana Yarosh , Dr. Brent Hecht , Joseph A Konstan- 4.6
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Approx. 8 hours to complete
In this course you will learn and practice techniques of user research and early UI design exploration. First, you will learn and practice several techniques for user research, including in-person research and survey and log-analysis techniques. Then, you will learn to analyze and deliver user research in forms that support UI design, including personas, use cases, tasks, and scenarios....
Prototyping and Design
by Loren Terveen , Haiyi Zhu , Lana Yarosh , Dr. Brent Hecht , Joseph A Konstan- 4.6
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Approx. 11 hours to complete
In this course you will learn how to design and prototype user interfaces to address the users and tasks identified in user research. Preface Introduction to Prototyping and Design Course Introduction Interface Prototyping Techniques Prototyping: What, Why, and How Low-Fidelity Prototyping Paper Prototype Example Wireframing and Tool-Based Prototyping Physical Low Fidelity Prototyping...
Evaluating User Interfaces
by Loren Terveen , Haiyi Zhu , Lana Yarosh , Dr. Brent Hecht , Joseph A Konstan- 4.7
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Approx. 12 hours to complete
In this course you will learn and practice several techniques for user interface evaluation. First we start with techniques that can be applied alone or in a design team, including action analysis, walkthroughs, and heuristic evaluation. Preface Introduction to Evaluating User Interfaces and Evaluation in the UI Design Process Evaluating User Interfaces: An Introduction...
Introduction to Recommender Systems: Non-Personalized and Content-Based
by Joseph A Konstan , Michael D. Ekstrand- 4.5
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Approx. 23 hours to complete
This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. Preface Intro to Recommender Systems...
Nearest Neighbor Collaborative Filtering
by Joseph A Konstan , Michael D. Ekstrand- 4.3
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Approx. 15 hours to complete
In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. Preface Course Introduction Course Structure Outline...
Matrix Factorization and Advanced Techniques
by Michael D. Ekstrand , Joseph A Konstan- 4.3
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Approx. 16 hours to complete
In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. Preface Matrix Factorization and Advanced Techniques...
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