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    • Signal Processing

    Signal Processing Courses Online

    Master signal processing for analyzing and manipulating signals. Learn about filtering, Fourier transforms, and real-time signal processing.

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    Explore the Signal Processing Course Catalog

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • B

      Berklee

      Electronic Music Production

      Skills you'll gain: Musical Composition, File Management, Music Performance, Music, Media Production, Music Theory, Instrumental Music, Performing Arts, Creativity, Peer Review, Automation, Electronic Media, Design Software, Editing, Patch Management, Software Installation, System Requirements

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.3K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Relational Databases, Tableau Software, Stored Procedure, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Dimensionality Reduction, Regression Analysis, Statistical Inference, Machine Learning Algorithms, Data Processing, Machine Learning, Data Access, Anomaly Detection, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Applied Machine Learning, Data Cleansing, Data Manipulation, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Using Databases with Python

      Skills you'll gain: Relational Databases, Database Design, SQL, Databases, Web Scraping, Data Modeling, Database Management, Data Visualization Software, Object-Relational Mapping, Object Oriented Programming (OOP), Data Processing, Python Programming, Application Programming Interface (API)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      21K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Data Engineering, Big Data, and Machine Learning on GCP

      Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Lakes, MLOps (Machine Learning Operations), Dashboard, Data Warehousing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data, Data Integration, Data Migration, Data Processing, Data Visualization Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Principles of fMRI 1

      Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Data Analysis, Research Design, Image Analysis, Neurology, Science and Research, Statistical Analysis, Statistical Modeling, Data Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      837 reviews

      Beginner · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Generative AI with Large Language Models

      Skills you'll gain: Generative AI, Large Language Modeling, OpenAI, ChatGPT, Prompt Engineering, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Tensorflow, Applied Machine Learning, Scalability, Natural Language Processing, Application Deployment, Reinforcement Learning, Performance Tuning, Performance Metric

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Generative AI, Data Wrangling, Large Language Modeling, Unit Testing, Supervised Learning, Feature Engineering, Keras (Neural Network Library), Deep Learning, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Artificial Intelligence, Data Import/Export, Data Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      85K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Deep Learning with PyTorch, Keras and Tensorflow

      Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Image Analysis, Data Manipulation, Tensorflow, Verification And Validation, Generative AI, Artificial Neural Networks, Data Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Artificial Intelligence, Scientific Visualization, Time Series Analysis and Forecasting, Predictive Modeling, Natural Language Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    Signal Processing learners also search

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    1…789…151

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

    • Meta Data Analyst: Meta
    • Electronic Music Production: Berklee
    • IBM Business Intelligence (BI) Analyst: IBM
    • IBM Introduction to Machine Learning: IBM
    • Using Databases with Python: University of Michigan
    • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
    • Introduction to Machine Learning: Duke University
    • Applied Data Science with Python: University of Michigan
    • Principles of fMRI 1: Johns Hopkins University
    • Generative AI with Large Language Models: DeepLearning.AI

    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

    In the electrical engineering and machine learning industry, signal processing is the engine that models, processes, transmits, and analyzes voice, video, and audio data. Signal processing transfers and processes information as signals to represent data of physical events. Signal processing is at the core of today's modern technologies, involving voice, data, and video transmission. It’s the science that can foster communication between audio processing and data transmission.

    Signal processing has advanced rapidly in the digital revolution and many now refer to this field as digital signal processing (DSP). Digital signal processing is the process and mathematics involved in manipulating information in such a way as to modify or improve the information in some manner. This information signal could be a snippet of voice, audio, or video.‎

    Signal processing techniques are used in many of our analog and digital interactions today, and that makes it valuable to know. If you have a strong interest in understanding the connections of electronic data and the powering of our modern electronic devices, then learning about signal processing can help you expand your interests and curiosity. For example, signal processing is the science and technology behind what makes it possible for two people to speak on mobile phones using their voice.

    Signal processing lies at the heart of analog-to-digital conversion practices. This would include encoding signals from speech enhancement and speech encoding to speech decoding and speech enhancement speech on the digital-to-analog playback side. Experts in the field rely on signal processing as the tool of choice every step of the way.‎

    Some of the careers that you may be able to find work in as a result of learning signal processing or digital signal processing may include opportunities in chip design, antenna engineering, machine learning, artificial intelligence, RF design, telecoms, and instrumentation systems.

    Understanding the foundational elements of signal processing can propel you forward into a career for the future, like big data, machine learning, and augmented reality. As the world becomes more digital, signals continue to be processed in a digital manner in many of today's modern products.‎

    Taking online courses about signal processing can create a whole new way of thinking around the devices in use today. The signal processing industry is getting bigger every day. As it grows, it lays out new opportunities for learning in specific areas. Your knowledge of signal processing will enlighten you about the ways that voice, video, and data are captured, transmitted, and received by others. If you are seeking to move into the larger electrical engineering field with insights into signal processing, you will likely learn how data design and machine learning come together in new and wondrous ways.‎

    Online Signal Processing courses offer a convenient and flexible way to enhance your knowledge or learn new Signal Processing skills. Choose from a wide range of Signal Processing courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Signal Processing, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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