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Learn the theory, tools and algorithms of sparse representations

Professional Certificate in
Sparse Representations in Signal and Image Processing
IsraelX and Technion

What you will learn

  • Fundamental theoretical contributions of sparse representation theory.
  • The importance of models in data processing.
  • Dictionary learning algorithms and their role in using this mode.
  • How to deploy sparse representations to signal and image processing tasks.
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Modeling data is the way we – scientists – believe that information should be explained and handled. Indeed, models play a central role in practically every task in signal and image processing. Sparse representation theory puts forward an emerging, highly effective, and universal such model. Its core idea is the description of the data as a linear combination of few building blocks – atoms – taken from a pre-defined dictionary of such fundamental elements.

This Professional Certificate program will introduce you to the field of sparse representations, starting with its theoretical foundations, and systematically present its key achievements. We will touch on theory, numerical algorithms, and applications in image processing.

The tools and algorithms presented in this program are state-of-the art in these fields, and relevant to many applications and needs, covering signal/image restoration, segmentation, sampling, compression, recognition, anomaly detection, separation, and more. 

This program is relevant to algorithm developers in machine learning and data mining. The tools learned will help developers be more effective in revealing hidden structures of given data, which is valuable for classification, clustering, stock market prediction, and more.

Expert instruction
2 skill-building courses
3 months
5 - 6 hours per week
For the full program experience

Courses in this program

  1. IsraelX and Technion's Sparse Representations in Signal and Image Processing Professional Certificate

  2. 5–6 hours per week, for 5 weeks

    Learn about the field of sparse representations by understanding its fundamental theoretical and algorithmic foundations.

  3. Started Apr 23, 2020
    5–6 hours per week, for 5 weeks

    Learn about the deployment of the sparse representation model to signal and image processing.

    • Career prospects for people with similar training include algorithm developers in signal and image processing, machine learning and data mining.
    • The average base salary for Data Scientists is $117K per year (Forbes).
    • According to a report from Glassdoor, Data Scientists lead the pack for best jobs in America; According to the Harvard Business Review, Data Scientist is “the hot job of the decade”.

Meet your instructors

from IsraelX, Technion
Yaniv Romano
PhD student in the Electrical Engineering Department, Technion
Israel Institute of Technology
Alona Golts
Michael Elad
Professor of Computer Science, Technion
Israel Institute of Technology

Experts from IsraelX, Technion committed to teaching online learning

Program endorsements

Google strongly supports the Sparse Representations Professional Certificate program. The topic is timely and important as it relates to many technical areas including imaging, computer vision, statistical science, and machine learning ­­ all of which are subject matter critically important to our work. We believe Professor Elad is uniquely qualified to teach this topic and we are excited by the possibility of the course being available worldwide. We look forward to finding many more opportunities to collaborate with Prof. Elad and his team in the future

Margaret Johnson , VP Education and University Program, Google, Inc.

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