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Text Classification Courses

Text classification courses can help you learn techniques for categorizing text data, building machine learning models, and evaluating performance metrics. You can develop skills in natural language processing, feature extraction, and data preprocessing. Many courses introduce tools like Python libraries such as scikit-learn and TensorFlow, that support implementing algorithms and refining models.


Popular Text Classification Courses and Certifications


  • C

    Coursera

    Fine Tune BERT for Text Classification with TensorFlow

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    211 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Supervised Learning, Bayesian Statistics, Logistic Regression, Statistical Modeling, Artificial Intelligence, Data Preprocessing, Deep Learning, Data Mining, Decision Tree Learning, Computer Vision, Statistical Machine Learning

    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, Model Evaluation, Recurrent Neural Networks (RNNs), Classification Algorithms, Data Ethics, Responsible AI, Text Mining, Transfer Learning, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Processing, Embeddings, Machine Learning, Data Analysis, Data Cleansing

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Snowflake

    Snowflake Generative AI

    Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, Generative AI, LLM Application, Data Engineering, Data Manipulation, Snowflake Schema, Large Language Modeling, Model Deployment, Data Warehousing, Unstructured Data, Embeddings, 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)

    4.8
    Rating, 4.8 out of 5 stars
    ·
    228 reviews

    Beginner · Professional Certificate · 1 - 3 Months

  • 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, Machine Learning Algorithms, Transfer Learning, Text Mining, Model Evaluation, Data Manipulation, Marketing Analytics, Python Programming, Google Cloud Platform, Classification Algorithms, 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

  • 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, Embeddings, Dimensionality Reduction, Machine Learning Methods, Text Mining, Statistical Machine Learning, Classification Algorithms, Feature Engineering, Probability & Statistics

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

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • C

    Coursera

    Tweet Emotion Recognition with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Tensorflow, Python Programming, Natural Language Processing, Data Preprocessing, Applied Machine Learning, Text Mining, Machine Learning Algorithms, Deep Learning, Classification Algorithms, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    173 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • G

    Google Cloud

    Transformer Models and BERT Model

    Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Transfer Learning, Embeddings

    4.1
    Rating, 4.1 out of 5 stars
    ·
    125 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Product Reviews Text-based Search - OpenAI Text Embedding

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

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    A

    Arizona State University

    Classification and Planned Experiments

    Skills you'll gain: Experimentation, Research Design, Statistical Modeling, Statistical Methods, Applied Machine Learning, Supervised Learning, Logistic Regression, Predictive Modeling, Statistical Programming, Statistical Analysis, Statistical Inference, Simulation and Simulation Software, Probability & Statistics, Data Science, Data Visualization, Simulations, Data Analysis, Data Analysis Software

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
    ·
    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Natural Language Processing

    Skills you'll gain: Natural Language Processing, Supervised Learning, Transfer Learning, Recurrent Neural Networks (RNNs), Markov Model, Embeddings, Text Mining, Dimensionality Reduction, Machine Learning Methods, Statistical Machine Learning, Artificial Neural Networks, Classification Algorithms, Data Preprocessing, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Feature Engineering, Applied Machine Learning, Algorithms, Keras (Neural Network Library)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    6.2K reviews

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

Searches related to text classification

supervised text classification for marketing analytics
unsupervised text classification for marketing analytics
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1234…134

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

  • Fine Tune BERT for Text Classification with TensorFlow: Coursera
  • Machine Learning: University of Washington
  • Mastering NLP: Tokenization, Sentiment Analysis & Neural MT: Edureka
  • Snowflake Generative AI: Snowflake
  • Supervised Text Classification for Marketing Analytics: University of Colorado Boulder
  • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
  • Tweet Emotion Recognition with TensorFlow: Coursera
  • Transformer Models and BERT Model: Google Cloud
  • Product Reviews Text-based Search - OpenAI Text Embedding: Coursera
  • Classification and Planned Experiments: Arizona State University

Frequently Asked Questions about Text Classification

Text classification is the process of categorizing text into predefined groups based on its content. This technique is crucial in various applications, such as spam detection in emails, sentiment analysis in social media, and organizing large datasets for easier retrieval. By automating the classification of text, organizations can enhance efficiency, improve customer experiences, and derive insights from unstructured data.‎

Careers in text classification span multiple industries, including technology, marketing, and data science. Positions such as data analyst, machine learning engineer, and natural language processing (NLP) specialist often require expertise in text classification. Additionally, roles in customer service and content moderation may benefit from skills in this area, as companies seek to streamline processes and improve user engagement.‎

To excel in text classification, you should develop a range of skills, including programming (especially in Python or R), familiarity with machine learning algorithms, and a solid understanding of natural language processing techniques. Knowledge of data preprocessing, feature extraction, and model evaluation is also essential. These skills will empower you to build effective classification models and analyze their performance.‎

Some of the best online courses for text classification include Supervised Text Classification for Marketing Analytics and Natural Language Processing with Classification and Vector Spaces. These courses provide practical insights and hands-on experience, helping you to understand the nuances of text classification in real-world applications.‎

Yes. You can start learning text classification on Coursera for free in two ways:

  1. Preview the first module of many text classification 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 text classification, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn text classification, start by exploring online courses that cover the fundamentals of machine learning and natural language processing. Engage with hands-on projects to apply your knowledge practically. Additionally, participating in online forums and communities can provide support and resources as you progress in your learning journey.‎

Typical topics covered in text classification courses include data preprocessing, feature extraction techniques, various classification algorithms, and model evaluation metrics. You may also learn about advanced topics like deep learning for text classification and the application of NLP techniques to enhance model performance.‎

For training and upskilling employees in text classification, courses like Classification - Fundamentals & Practical Applications and Supervised Machine Learning: Regression and Classification are excellent choices. These courses provide practical skills and knowledge that can be directly applied in the workplace, fostering a more skilled workforce.‎

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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