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  • Signal Processing

Signal Processing Courses

Signal processing courses can help you learn about Fourier transforms, filtering techniques, and signal modulation. You can build skills in analyzing audio and visual signals, implementing algorithms for noise reduction, and working with time-frequency analysis. Many courses introduce tools like MATLAB and Python libraries, that support simulating signal processing techniques and analyzing real-world data.


Popular Signal Processing Courses and Certifications


  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Digital Signal Processing

    Skills you'll gain: Digital Signal Processing, Digital Communications, Communication Systems, Image Analysis, Telecommunications, Electrical and Computer Engineering, Electrical Engineering, Embedded Systems, Electronic Systems, Engineering Analysis, Electronics, Programming Principles, Numerical Analysis, Algorithms, Linear Algebra, Mathematical Modeling, Time Series Analysis and Forecasting, Data Mapping, Real Time Data, Computer Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    797 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Digital Signal Processing 1: Basic Concepts and Algorithms

    Skills you'll gain: Digital Signal Processing, Electrical Engineering, Communication Systems, Programming Principles, Electronics, Telecommunications, Algorithms, Linear Algebra, Time Series Analysis and Forecasting, Mathematical Modeling

    4.5
    Rating, 4.5 out of 5 stars
    ·
    636 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Digital Signal Processing 2: Filtering

    Skills you'll gain: Digital Signal Processing, Digital Communications, Communication Systems, Electrical and Computer Engineering, Telecommunications, Electronics, Engineering Analysis, Numerical Analysis, Data Mapping, Real Time Data, Computer Programming

    4.7
    Rating, 4.7 out of 5 stars
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    195 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    U

    Universitat Pompeu Fabra of Barcelona

    Audio Signal Processing for Music Applications

    Skills you'll gain: Digital Signal Processing, Music, Open Source Technology, Python Programming, Time Series Analysis and Forecasting, NumPy, Mathematical Modeling, Advanced Mathematics

    4.8
    Rating, 4.8 out of 5 stars
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    294 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Digital Signal Processing 3: Analog vs Digital

    Skills you'll gain: Digital Signal Processing, Digital Communications, Electrical and Computer Engineering, Electronic Systems, Electronics, Numerical Analysis, Telecommunications, Linear Algebra, Mathematical Modeling, Time Series Analysis and Forecasting

    4.8
    Rating, 4.8 out of 5 stars
    ·
    91 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    É

    École Polytechnique Fédérale de Lausanne

    Digital Signal Processing 4: Applications

    Skills you'll gain: Digital Signal Processing, Digital Communications, Communication Systems, Image Analysis, Telecommunications, Electrical Engineering, Electrical and Computer Engineering, Embedded Systems, Electronics, Algorithms

    4.7
    Rating, 4.7 out of 5 stars
    ·
    83 reviews

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
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    J

    Johns Hopkins University

    GPU Programming

    Skills you'll gain: Artificial Neural Networks, Image Analysis, Event-Driven Programming, Scalability, Deep Learning, C and C++, Performance Tuning, Convolutional Neural Networks, Data-oriented programming, C++ (Programming Language), Digital Signal Processing, Linear Algebra, Distributed Computing, Computer Graphics, System Programming, Numerical Analysis, Programming Principles, Computer Architecture, Program Development, Machine Learning

    Build toward a degree

    2.8
    Rating, 2.8 out of 5 stars
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    187 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    M

    MathWorks

    Introduction to Image Processing

    Skills you'll gain: Image Analysis, Matlab, Computer Vision, Spatial Data Analysis, Digital Signal Processing, Geospatial Information and Technology, Quantitative Research, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
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    202 reviews

    Beginner · Course · 1 - 4 Weeks

  • I

    IBM

    Introduction to Computer Vision and Image Processing

    Skills you'll gain: Computer Vision, Convolutional Neural Networks, Transfer Learning, Model Evaluation, Machine Learning Methods, Classification Algorithms, Machine Learning Algorithms, Visualization (Computer Graphics), Deep Learning, Feature Engineering, Network Architecture

    4.3
    Rating, 4.3 out of 5 stars
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    1.4K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    M

    MathWorks

    MathWorks Computer Vision Engineer

    Skills you'll gain: Computer Vision, Model Evaluation, Image Analysis, Model Deployment, Anomaly Detection, Convolutional Neural Networks, Transfer Learning, Deep Learning, Machine Learning Methods, Image Quality, Data Preprocessing, Artificial Neural Networks, Matlab, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Traffic Flow Optimization, Data Visualization

    4.7
    Rating, 4.7 out of 5 stars
    ·
    350 reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Modern AI Models for Vision and Multimodal Understanding

    Skills you'll gain: Vision Transformer (ViT), Recurrent Neural Networks (RNNs), Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Embeddings, Digital Signal Processing, Transfer Learning

    Build toward a degree

    4.3
    Rating, 4.3 out of 5 stars
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    6 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    M

    MathWorks

    Medical Image Processing

    Skills you'll gain: Medical Imaging, Magnetic Resonance Imaging, Image Analysis, X-Ray Computed Tomography, Data Import/Export, Biomedical Engineering, Matlab, Scientific Visualization, Deep Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    25 reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

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In summary, here are 10 of our most popular signal processing courses

  • Digital Signal Processing: École Polytechnique Fédérale de Lausanne
  • Digital Signal Processing 1: Basic Concepts and Algorithms: École Polytechnique Fédérale de Lausanne
  • Digital Signal Processing 2: Filtering: École Polytechnique Fédérale de Lausanne
  • Audio Signal Processing for Music Applications: Universitat Pompeu Fabra of Barcelona
  • Digital Signal Processing 3: Analog vs Digital: École Polytechnique Fédérale de Lausanne
  • Digital Signal Processing 4: Applications: École Polytechnique Fédérale de Lausanne
  • GPU Programming: Johns Hopkins University
  • Introduction to Image Processing: MathWorks
  • Introduction to Computer Vision and Image Processing: IBM
  • MathWorks Computer Vision Engineer: MathWorks

Skills you can learn in Algorithms

Graphs (22)
Mathematical Optimization (21)
Computer Program (20)
Data Structure (19)
Problem Solving (19)
Algebra (12)
Computer Vision (10)
Discrete Mathematics (10)
Graph Theory (10)
Image Processing (10)
Linear Algebra (10)
Reinforcement Learning (10)

Frequently Asked Questions about Signal Processing

Signal processing is the analysis, interpretation, and manipulation of signals. Signals can be anything from audio and video to sensor data and images. It plays a crucial role in various fields, including telecommunications, audio engineering, and biomedical engineering. Understanding signal processing is essential because it enables the extraction of meaningful information from raw data, improving communication systems, enhancing audio quality, and enabling advanced technologies like image recognition and machine learning.‎

A variety of job opportunities exist in the field of signal processing. Positions can range from signal processing engineers and audio engineers to data scientists and research scientists. Industries such as telecommunications, healthcare, and entertainment often seek professionals skilled in signal processing to develop algorithms, improve system performance, and analyze complex data. With the rise of AI and machine learning, roles that require signal processing expertise are increasingly in demand.‎

To succeed in signal processing, you should develop a strong foundation in mathematics, particularly in linear algebra and calculus. Familiarity with programming languages such as Python or MATLAB is also beneficial, as these tools are commonly used for implementing signal processing algorithms. Additionally, understanding concepts like Fourier transforms, filtering techniques, and statistical analysis will enhance your skill set and prepare you for practical applications in the field.‎

Some of the best online courses for signal processing include the Digital Signal Processing Specialization, which covers fundamental concepts and applications. Other notable courses are Digital Signal Processing 1: Basic Concepts and Algorithms and Audio Signal Processing for Music Applications, which focus on specific aspects of the field. These courses provide a comprehensive understanding of both theoretical and practical elements of signal processing.‎

Yes. You can start learning signal processing on Coursera for free in two ways:

  1. Preview the first module of many signal processing courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in signal processing, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn signal processing, start by exploring online courses that cover the basics and gradually progress to more advanced topics. Engage with practical exercises and projects to apply what you've learned. Joining online forums or study groups can also enhance your understanding through collaboration. Consistent practice and real-world application of concepts will help solidify your knowledge and skills in signal processing.‎

Typical topics covered in signal processing courses include signal representation, Fourier analysis, filtering techniques, and time-frequency analysis. Courses may also explore applications in audio and image processing, as well as advanced topics like adaptive filtering and machine learning integration. This comprehensive curriculum equips you with the necessary tools to analyze and manipulate signals effectively.‎

For training and upskilling employees in signal processing, the Digital Signal Processing Specialization is an excellent choice. It provides a structured learning path that covers essential concepts and applications. Additionally, courses like Digital Signal Processing 2: Filtering and Digital Signal Processing 4: Applications can help employees gain practical skills relevant to their roles, enhancing their contributions to the organization.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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