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    • Computational Linguistics

    Computational Linguistics Courses Online

    Explore computational linguistics for natural language processing. Learn to develop algorithms for language analysis and machine translation.

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    Explore the Computational Linguistics Course Catalog

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      S

      Simplilearn

      Advanced Prompt Engineering Course

      Skills you'll gain: Prompt Engineering, Generative AI, Large Language Modeling, OpenAI, Data Synthesis

      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
      P

      Packt

      Natural Language Processing - Probability Models in Python

      Skills you'll gain: Natural Language Processing, Text Mining, Scikit Learn (Machine Learning Library), Dimensionality Reduction, Statistical Machine Learning, Unsupervised Learning, Python Programming, Bayesian Statistics, NumPy, Supervised Learning, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Natural Language Processing - Deep Learning Models in Python

      Skills you'll gain: Tensorflow, Deep Learning, Natural Language Processing, Artificial Neural Networks, Python Programming, Text Mining, Machine Learning Methods

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      NLP – Machine Learning Models in Python

      Skills you'll gain: Dimensionality Reduction, Natural Language Processing, Text Mining, Applied Machine Learning, Statistical Machine Learning, Machine Learning Algorithms, Supervised Learning, Unsupervised Learning, Python Programming, Scikit Learn (Machine Learning Library), Machine Learning, Predictive Modeling, Linear Algebra, Algorithms

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Coding for Everyone: C and C++

      Skills you'll gain: C++ (Programming Language), Debugging, C (Programming Language), Object Oriented Programming (OOP), Software Design Patterns, Code Review, Data Structures, Computer Programming, Algorithms, Command-Line Interface, Programming Principles, Program Development, Computer Science, Computational Thinking, Integrated Development Environments, Graph Theory, Artificial Intelligence, Software Technical Review, File Systems, Game Design

      4.5
      Rating, 4.5 out of 5 stars
      ·
      9.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      ChatGPT Advanced Data Analysis

      Skills you'll gain: Prompt Engineering, Data Presentation, ChatGPT, Document Management, Artificial Intelligence, Microsoft Excel, Problem Solving, Data Analysis, Generative AI, Information Management, File Management, Creativity, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      786 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      P

      Peking University

      程序设计与算法

      Skills you'll gain: Data Structures, Algorithms, C++ (Programming Language), Object Oriented Programming (OOP), Object Oriented Design, Computational Thinking, Graph Theory, C (Programming Language), Programming Principles, Theoretical Computer Science, Program Development, Computer Science, Data Storage, Computer Architecture, Computer Programming, Database Systems, Software Design Patterns, Performance Tuning, Computational Logic, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      Stanford University

      Introduction to Logic

      Skills you'll gain: Logical Reasoning, Computational Logic, Deductive Reasoning, Computational Thinking, Business Logic, Functional Design, Programming Principles

      4.4
      Rating, 4.4 out of 5 stars
      ·
      647 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Introductory C Programming

      Skills you'll gain: Debugging, Maintainability, Programming Principles, Algorithms, Software Testing, Program Development, C (Programming Language), Pseudocode, Computational Thinking, Software Engineering, Simulations, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Operating Systems, Development Environment, User Interface (UI), Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Statistical Modeling, Bayesian Statistics, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Statistical Inference, Sampling (Statistics), Statistical Methods, Natural Language Processing, Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

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    In summary, here are 10 of our most popular computational linguistics courses

    • Algorithms: Stanford University
    • Advanced Prompt Engineering Course: Simplilearn
    • Generative AI with Large Language Models: DeepLearning.AI
    • Natural Language Processing - Probability Models in Python: Packt
    • Natural Language Processing - Deep Learning Models in Python: Packt
    • NLP – Machine Learning Models in Python: Packt
    • Coding for Everyone: C and C++: University of California, Santa Cruz
    • ChatGPT Advanced Data Analysis: Vanderbilt University
    • 程序设计与算法: Peking University
    • Introduction to Logic: Stanford University

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    Frequently Asked Questions about Computational Linguistics

    Computational linguistics is the study of computer modeling of human language. This scientific field develops computational models for linguistic patterns and structures. In today's world, applications of computational linguistics fall into two categories: using computers to explain linguistic phenomena and developing systems for computers to process language. Computational linguists work to make computers understand both written and spoken language, and they produce technologies that allow humans and computers to communicate with each other linguistically using speech or language systems like artificial intelligence, text-to-speech translators, and automated voice responses.‎

    Computational linguistics is a worthwhile field of study because we use computers increasingly in our modern world, and computers that understand and use human language can help us make the best use of technology. Because language is such a versatile means of communication, computers that can communicate using written or spoken language can become more effective. If you're interested in helping make interactions with machines easier, you'll enjoy the challenges of computational linguistics, and as technology continues to advance, you can develop newer and more sophisticated ways for computers to communicate.‎

    When you're interested in a career in computational linguistics, you'll find plenty of opportunities for work as a computational linguist or engineer. You can find jobs helping program the next generation of artificial intelligence, or you can work as a language engineer or machine learning engineer. Your computational linguistics skills can come in handy developing apps that aid in research, web searches, or translation. You might even be able to program video games that make better use of human speech or help someone who can't speak learn to communicate.‎

    Online courses on Coursera offer you opportunities to learn computational linguistics concepts and skills that are relevant to the real world, such as the philosophies behind language learning and how to program a computer to understand more than one human language or dialect. You might also learn about TensorFlow for NLP to discover the semantic similarities in texts, natural language processing with vector spaces, and sequence models in AI.‎

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

    When looking to enhance your workforce's skills in Computational Linguistics, 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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