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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, Applied Machine Learning, Text Mining, Dimensionality Reduction, Large Language Modeling, Statistical Machine Learning, Artificial Neural Networks, Classification Algorithms, Data Preprocessing, Deep Learning, Tensorflow, Machine Learning Methods, Logistic Regression, Feature Engineering, 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
    E

    Edureka

    Mastering NLP: Tokenization, Sentiment Analysis & Neural MT

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Fine-tuning, Model Evaluation, Recurrent Neural Networks (RNNs), Data Ethics, Responsible AI, Text Mining, Transfer Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Applied Machine Learning, Data Processing, Machine Learning, Data Analysis, Data Cleansing

    3.3
    Rating, 3.3 out of 5 stars
    ·
    7 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Natural Language Processing on Google Cloud

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Transfer Learning, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Recurrent Neural Networks (RNNs), Embeddings, Deep Learning, AI Workflows, Artificial Neural Networks, Cloud API, Feature Engineering, Model Training

    4.4
    Rating, 4.4 out of 5 stars
    ·
    540 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    P

    Packt

    Mastering NLP: Foundations, ML & LLMs

    Skills you'll gain: Large Language Modeling, Retrieval-Augmented Generation, LangChain, LLM Application, Natural Language Processing, Data Ethics, Responsible AI, Text Mining, Embeddings, Deep Learning, Generative AI, Fine-tuning, Artificial Intelligence, Classification Algorithms, Machine Learning Methods, Data Preprocessing, Applied Machine Learning, Machine Learning, Model Optimization, Model Evaluation

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    Edureka

    Machine Learning and NLP Basics

    Skills you'll gain: Machine Learning Methods, Tensorflow, Predictive Modeling, Machine Learning, Text Mining, Deep Learning, Machine Learning Algorithms, Natural Language Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Artificial Intelligence, AI literacy, Classification Algorithms, Data Science, Model Training, Artificial Neural Networks, Data Preprocessing, Model Optimization

    3.4
    Rating, 3.4 out of 5 stars
    ·
    34 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Microsoft

    Microsoft AI & ML Engineering

    Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Data Infrastructure, Data Preprocessing, Model Optimization

    4.5
    Rating, 4.5 out of 5 stars
    ·
    383 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Science, Machine Learning, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.7K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free
    Free
    C

    Coursera

    Transfer Learning for NLP with TensorFlow Hub

    Skills you'll gain: Transfer Learning, Fine-tuning, Tensorflow, Natural Language Processing, Keras (Neural Network Library), Embeddings, Model Training, 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

    AI Foundations for Everyone

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Responsible AI, IBM Cloud, Generative Model Architectures, AI Workflows, LLM Application, Application Deployment, AI literacy, Machine Learning Software, Natural Language Processing, Business Workflow Analysis, Workflow Management, No-Code Development, Artificial Intelligence, Machine Learning, Deep Learning, Data Science

    4.7
    Rating, 4.7 out of 5 stars
    ·
    36K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Preview
    Preview
    B

    Birla Institute of Technology & Science, Pilani

    Natural Language Processing

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Embeddings, Text Mining, Semantic Web, Data Preprocessing, LLM Application, Artificial Intelligence and Machine Learning (AI/ML), ChatGPT, Data Processing, Artificial Intelligence, Artificial Neural Networks, Statistical Machine Learning, Generative AI, Deep Learning, Model Training, Dependency Analysis, Model Evaluation

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

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

    Packt

    Deep Learning, NLP, and AI Applications

    Skills you'll gain: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Transfer Learning, Natural Language Processing, Model Optimization, Deep Learning, PyTorch (Machine Learning Library), Large Language Modeling, Fine-tuning, Keras (Neural Network Library), Artificial Neural Networks, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Tensorflow, Artificial Intelligence, Machine Learning Methods, Computer Vision, Model Training

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Building Vision and NLP Workflows with TensorFlow pipelines

    Skills you'll gain: Model Evaluation, Image Analysis, Computer Vision, Vision Transformer (ViT), Tensorflow, Keras (Neural Network Library), AI Workflows, Model Training, Embeddings, Deep Learning, Large Language Modeling, Natural Language Processing, Model Deployment, Model Optimization, Data Pipelines, Risk Modeling, Data Preprocessing

    Intermediate · Course · 1 - 3 Months

1234…27

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

  • Natural Language Processing: DeepLearning.AI
  • Mastering NLP: Tokenization, Sentiment Analysis & Neural MT: Edureka
  • Natural Language Processing on Google Cloud: Google Cloud
  • Mastering NLP: Foundations, ML & LLMs: Packt
  • Machine Learning and NLP Basics: Edureka
  • Microsoft AI & ML Engineering: Microsoft
  • IBM Machine Learning: IBM
  • Transfer Learning for NLP with TensorFlow Hub: Coursera
  • AI Foundations for Everyone: IBM
  • Natural Language Processing: Birla Institute of Technology & Science, Pilani

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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