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Text Classification Courses Online

Learn text classification for natural language processing. Understand how to categorize text data using machine learning models.

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Explore the Text Classification Course Catalog

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Pearson

    Introduction to Transformer Models for NLP

    Skills you'll gain: Prompt Engineering, PyTorch (Machine Learning Library), Natural Language Processing, MLOps (Machine Learning Operations), Large Language Modeling, Computer Vision, Image Analysis, Generative AI, Generative Model Architectures, Application Deployment, Artificial Neural Networks, Text Mining, Deep Learning, Cloud Hosting, Semantic Web, Restful API

    Intermediate · Specialization · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Natural Language Processing with Classification and Vector Spaces

    Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Text Mining, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Unstructured Data, Probability & Statistics

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

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera Project Network

    Fine Tune BERT for Text Classification with TensorFlow

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Natural Language Processing, Deep Learning, Data Pipelines

    4.6
    Rating, 4.6 out of 5 stars
    ·
    211 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    S

    Snowflake

    Snowflake Generative AI

    Skills you'll gain: Prompt Engineering, Generative AI, LLM Application, Data Engineering, Data Manipulation, Snowflake Schema, Large Language Modeling, Application Deployment, Data Lakes, Data Warehousing, Unstructured Data, Cloud Development, SQL, Natural Language Processing, Data Pipelines, Extract, Transform, Load, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Stored Procedure

    4.8
    Rating, 4.8 out of 5 stars
    ·
    193 reviews

    Beginner · Professional Certificate · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning

    Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms, Big Data

    4.6
    Rating, 4.6 out of 5 stars
    ·
    16K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    Edureka

    Mastering NLP: Tokenization, Sentiment Analysis & Neural MT

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Data Ethics, Responsible AI, Text Mining, PyTorch (Machine Learning Library), Artificial Neural Networks, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Processing, Artificial Intelligence, Scikit Learn (Machine Learning Library), Time Series Analysis and Forecasting, Machine Learning, Data Analysis, Unstructured Data, Data Cleansing, Applied Machine Learning, Unified Modeling Language

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Supervised Text Classification for Marketing Analytics

    Skills you'll gain: Supervised Learning, Deep Learning, Scikit Learn (Machine Learning Library), Machine Learning, Tensorflow, Text Mining, Predictive Modeling, Classification And Regression Tree (CART), Data Manipulation, Marketing Analytics, Python Programming, Feature Engineering, Google Cloud Platform, Data Processing, Artificial Neural Networks, Performance Metric

    Build toward a degree

    3.1
    Rating, 3.1 out of 5 stars
    ·
    14 reviews

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera Project Network

    Tweet Emotion Recognition with TensorFlow

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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    170 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • G

    Google Cloud

    Transformer Models and BERT Model

    Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Artificial Neural Networks

    4.1
    Rating, 4.1 out of 5 stars
    ·
    123 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Text Mining in Python

    Skills you'll gain: Text Mining, Natural Language Processing, Data Processing, Unstructured Data, Feature Engineering, Data Manipulation, Data Cleansing, Python Programming, Unsupervised Learning, Machine Learning Algorithms, Supervised Learning

    4.2
    Rating, 4.2 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera Project Network

    Product Reviews Text-based Search - OpenAI Text Embedding

    Skills you'll gain: Dimensionality Reduction, OpenAI, Application Development, Exploratory Data Analysis, Application Programming Interface (API), Text Mining, Python Programming, Data Analysis, Natural Language Processing, Data Manipulation

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    U

    University of California San Diego

    Linux Tools for Text Processing

    Skills you'll gain: Linux Commands, Linux, Unix Commands, Shell Script, Linux Administration, Data Processing, Text Mining, Command-Line Interface, Data Manipulation, Unix, Scripting, Automation, File Management

    Beginner · Course · 1 - 3 Months

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In summary, here are 10 of our most popular text classification courses

  • Introduction to Transformer Models for NLP: Pearson
  • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
  • Fine Tune BERT for Text Classification with TensorFlow: Coursera Project Network
  • Snowflake Generative AI: Snowflake
  • Machine Learning: University of Washington
  • Mastering NLP: Tokenization, Sentiment Analysis & Neural MT: Edureka
  • Supervised Text Classification for Marketing Analytics: University of Colorado Boulder
  • Tweet Emotion Recognition with TensorFlow: Coursera Project Network
  • Transformer Models and BERT Model: Google Cloud
  • Applied Text Mining in Python: University of Michigan

Frequently Asked Questions about Text Classification

Text classification is a process of categorizing text into organized sections or groups. Text classifiers use elements of Natural Language Processing (NLP) to structure textual data in fast, cost-effective, and scalable ways. Also known as text categorization or text tagging, this system of text classification is a useful way to analyze textual components and then organize the text according to tags based on its content. Text classification easily pulls insights from data and then uses that data to automate business processes.‎

It's valuable to learn about text classification because you can understand that unstructured text is everywhere in our online lives. We use unclassified text every day in our emails, chat conversations, and social media interactions. Businesses and others want to know the value that’s in this unstructured text, but it’s hard to extract value from this data unless it’s organized in a certain way. Text classification can organize text by topic, language, and sentiment to filter it by category and use.‎

Some of the typical careers that use text classification include jobs like a computational linguist, AI machine learning manager, NLP scientist, system design analyst, computer researcher, technical writer, and other similar data roles. Text classification is an emerging field connected to NLP, and job opportunities may come to those with a background in data science, artificial intelligence, and machine learning experience. Gaining a better understanding of text classification in these types of jobs may help you to grow in levels within your company or organization.‎

By taking online courses about text classification, you may learn certain basic protocols of how to analyze emails, spam, video content, and social media posts. You may also learn to recognize certain NLP tasks in your daily work and assess which techniques work best. Learning text classification from online courses could show you the various approaches to the subject—the rule-based approach to text classification, the machine learning approach, or a hybrid combination of both. Taking online courses can help you learn the fundamentals of text classification, which can benefit you with skills and knowledge to help you build your future opportunities in this emerging field.‎

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

When looking to enhance your workforce's skills in Text Classification, 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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