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NLP Courses

NLP courses can help you learn text processing, sentiment analysis, language modeling, and chatbot development. You can build skills in data preprocessing, feature extraction, and evaluating model performance. Many courses introduce tools like Python libraries such as NLTK and spaCy, as well as frameworks like TensorFlow and PyTorch, that support implementing NLP techniques and developing applications that utilize artificial intelligence.


Popular NLP Courses and Certifications


  • 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

  • Status: Free Trial
    Free Trial
    I

    IBM

    Gen AI Foundational Models for NLP & Language Understanding

    Skills you'll gain: PyTorch (Machine Learning Library), Large Language Modeling, Embeddings, Generative AI, Natural Language Processing, Transfer Learning, Recurrent Neural Networks (RNNs), Data Ethics, Artificial Neural Networks, Classification Algorithms, Model Evaluation, Data Preprocessing, Feature Engineering

    4.5
    Rating, 4.5 out of 5 stars
    ·
    169 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Artificial Intelligence (AI)

    Skills you'll gain: Responsible AI, Generative AI, Natural Language Processing, Robotics, Business Logic, Risk Mitigation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    22K reviews

    Beginner · Course · 1 - 4 Weeks

  • 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
    E

    Edureka

    Machine Learning and NLP Basics

    Skills you'll gain: Tensorflow, Predictive Modeling, Machine Learning, Text Mining, Deep Learning, Natural Language Processing, Applied Machine Learning, Convolutional Neural Networks, Supervised Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, Classification Algorithms, Data Science, Data Preprocessing

    3.3
    Rating, 3.3 out of 5 stars
    ·
    32 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Generative AI Engineering

    Skills you'll gain: Prompt Engineering, Exploratory Data Analysis, Prompt Patterns, LangChain, Large Language Modeling, Retrieval-Augmented Generation, Model Evaluation, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Data Transformation, Supervised Learning, Responsible AI, Vector Databases, Data Import/Export

    4.6
    Rating, 4.6 out of 5 stars
    ·
    97K reviews

    Beginner · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Natural Language Processing on Google Cloud

    Skills you'll gain: Natural Language Processing, Transfer Learning, Tensorflow, Google Cloud Platform, Recurrent Neural Networks (RNNs), Embeddings, Deep Learning, AI Workflows, Artificial Neural Networks, Feature Engineering, Model Evaluation

    4.4
    Rating, 4.4 out of 5 stars
    ·
    537 reviews

    Advanced · Course · 1 - 3 Months

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

    Pearson

    Introduction to Transformer Models for NLP

    Skills you'll gain: Vision Transformer (ViT), Prompt Engineering, PyTorch (Machine Learning Library), Model Deployment, Transfer Learning, Hugging Face, Natural Language Processing, MLOps (Machine Learning Operations), Large Language Modeling, Cloud Deployment, Computer Vision, Generative AI, Image Analysis, Application Deployment, Generative Model Architectures, Embeddings, Data Preprocessing, Model Evaluation

    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, 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

  • C

    Coursera

    Transfer Learning for NLP with TensorFlow Hub

    Skills you'll gain: Transfer Learning, Tensorflow, Natural Language Processing, Keras (Neural Network Library), Embeddings, Deep Learning, Classification Algorithms, Model Evaluation, Machine Learning, Software Visualization

    4.8
    Rating, 4.8 out of 5 stars
    ·
    181 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Retrieval-Augmented Generation, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Computer Vision, Keras (Neural Network Library), LLM Application, Supervised Learning, Vector Databases, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free
    Free
    D

    DeepLearning.AI

    LangChain Chat with Your Data

    Skills you'll gain: Retrieval-Augmented Generation, LangChain, LLM Application, ChatGPT, Large Language Modeling, Embeddings, Data Processing, Data Import/Export, Vector Databases, Prompt Engineering, Document Management

    4.8
    Rating, 4.8 out of 5 stars
    ·
    655 reviews

    Beginner · Project · Less Than 2 Hours

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In summary, here are 10 of our most popular nlp courses

  • Natural Language Processing: DeepLearning.AI
  • Gen AI Foundational Models for NLP & Language Understanding: IBM
  • Introduction to Artificial Intelligence (AI): IBM
  • Mastering NLP: Tokenization, Sentiment Analysis & Neural MT: Edureka
  • Machine Learning and NLP Basics: Edureka
  • IBM Generative AI Engineering: IBM
  • Natural Language Processing on Google Cloud: Google Cloud
  • Introduction to Transformer Models for NLP: Pearson
  • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
  • Transfer Learning for NLP with TensorFlow Hub: Coursera

Skills you can learn in Software Development

Programming Language (34)
Google (25)
Computer Program (21)
Software Testing (21)
Web (19)
Google Cloud Platform (18)
Application Programming Interfaces (17)
Data Structure (16)
Problem Solving (14)
Object-oriented Programming (13)
Kubernetes (10)
List & Label (10)

Frequently Asked Questions about Nlp

Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans through natural language. It enables machines to understand, interpret, and generate human language in a valuable way. NLP is important because it powers various applications, from chatbots and virtual assistants to sentiment analysis and language translation. As businesses increasingly rely on data-driven insights, the ability to analyze and understand human language becomes crucial for enhancing customer experiences and making informed decisions.‎

Pursuing a career in NLP opens up a variety of job opportunities across multiple industries. Some common roles include NLP Engineer, Data Scientist, Machine Learning Engineer, and AI Research Scientist. These positions often involve developing algorithms and models that can process and analyze text data, creating applications that utilize NLP technologies, and conducting research to advance the field. As organizations continue to integrate AI and machine learning into their operations, the demand for skilled professionals in NLP is expected to grow.‎

To succeed in NLP, you will need a combination of technical and analytical skills. Key skills include programming languages such as Python or R, familiarity with machine learning frameworks, and a solid understanding of linguistics and language structure. Additionally, knowledge of data preprocessing techniques, statistical analysis, and experience with NLP libraries like NLTK or spaCy can be beneficial. Building a strong foundation in these areas will empower you to tackle complex NLP challenges effectively.‎

There are several excellent online courses available for those interested in learning NLP. For a comprehensive understanding, consider the Mastering NLP: Tokenization, Sentiment Analysis & Neural MT Specialization. Alternatively, the Applied NLP and Generative AI Specialization offers practical insights into applying NLP techniques. For a focus on modern architectures, the Introduction to Transformer Models for NLP Specialization is highly recommended.‎

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

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

To learn NLP effectively, start by familiarizing yourself with the basics of programming and data science. Online courses can provide structured learning paths, allowing you to progress from foundational concepts to more advanced topics. Engage in hands-on projects to apply what you learn, and consider joining online communities or forums to connect with other learners and professionals. This collaborative approach can enhance your understanding and keep you motivated.‎

NLP courses typically cover a range of topics, including text preprocessing, sentiment analysis, language modeling, and machine translation. You may also explore advanced subjects like deep learning for NLP, sequence models, and transformer architectures. Practical applications, such as building chatbots or analyzing social media data, are often included to provide real-world context and enhance your learning experience.‎

For training and upskilling employees in NLP, consider courses that offer practical applications and industry-relevant skills. The Building AI Agents: Automation and NLP Foundations course is designed to provide foundational knowledge while focusing on automation. Additionally, the Natural Language Processing with Attention Models course can help employees understand advanced techniques that are increasingly important in the field.‎

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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