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.

DeepLearning.AI
Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Large Language Modeling, Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Algorithms, Keras (Neural Network Library), Unstructured Data, Probability & Statistics
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: PyTorch (Machine Learning Library), Large Language Modeling, Generative AI, Natural Language Processing, Data Ethics, Text Mining, Artificial Neural Networks, Deep Learning, Feature Engineering, Statistical Methods
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Prompt Engineering, Exploratory Data Analysis, Data Wrangling, Prompt Patterns, LangChain, Large Language Modeling, Unsupervised Learning, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, Supervised Learning, Keras (Neural Network Library), Data Transformation, Feature Engineering, Flask (Web Framework), Data Analysis, Responsible AI, LLM Application, Data Import/Export
Beginner · Professional Certificate · 3 - 6 Months

Skills you'll gain: Responsible AI, Generative AI, Natural Language Processing, Business Intelligence, Content Creation, Risk Mitigation
Beginner · Course · 1 - 4 Weeks

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

Edureka
Skills you'll gain: Tensorflow, Predictive Modeling, Machine Learning, Text Mining, Deep Learning, Natural Language Processing, Supervised Learning, Artificial Intelligence, Data Science, Data Processing, Computer Vision, Reinforcement Learning
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Tensorflow, Natural Language Processing, Keras (Neural Network Library), Text Mining, Applied Machine Learning, Deep Learning, Machine Learning, Software Visualization
Intermediate · Guided Project · Less Than 2 Hours

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

Google Cloud
Skills you'll gain: Natural Language Processing, Large Language Modeling, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Cloud API, Feature Engineering
Advanced · Course · 1 - 3 Months

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
Intermediate · Course · 1 - 4 Weeks

DeepLearning.AI
Skills you'll gain: LangChain, LLM Application, Large Language Modeling, Extract, Transform, Load, Data Processing, Data Import/Export, Semantic Web, Generative AI, Prompt Engineering, Document Management
Beginner · Project · Less Than 2 Hours

Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, PyTorch (Machine Learning Library), Unsupervised Learning, Generative AI, PySpark, Computer Vision, Supervised Learning, Keras (Neural Network Library), Feature Engineering, Deep Learning, Reinforcement Learning, LLM Application, Jupyter, Applied Machine Learning, Natural Language Processing, Machine Learning, Python Programming, Data Science
Build toward a degree
Intermediate · Professional Certificate · 3 - 6 Months
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:
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.‎