Free NLP And Text Mining Courses Online
Natural Language Processing (NLP)
Nowadays, a great advance in technology has been achieved, to the point that machines have managed to perform tasks that we considered that only human beings could perform. For example, for a computer to interpret human speech was science fiction about 20 years ago, but today it is a reality. This technology is present in our daily routine. Using only the voice, you can send commands to the mobile phone or control the devices of a smart home.
Smartphone applications like Alexa, Siri, Google Assistant, among others, have made it easier to perform daily tasks such as scheduling activities or looking for a contact. All these types of applications use natural language processing and machine learning.
Definition - Natural Language Processing
Natural Language Processing involves interactions between computers and human languages. NLP enables processing and
Natural Language Processing (NLP)
Nowadays, a great advance in technology has been achieved, to the point that machines have managed to perform tasks that we considered that only human beings could perform. For example, for a computer to interpret human speech was science fiction about 20 years ago, but today it is a reality. This technology is present in our daily routine. Using only the voice, you can send commands to the mobile phone or control the devices of a smart home.
Smartphone applications like Alexa, Siri, Google Assistant, among others, have made it easier to perform daily tasks such as scheduling activities or looking for a contact. All these types of applications use natural language processing and machine learning.
Definition - Natural Language Processing
Natural Language Processing involves interactions between computers and human languages. NLP enables processing and analyzing large amounts of natural language data using computers. It provides machines with the ability to understand natural human language.
Natural language processing is used in multiple tools or software, some examples of its use are:
- Chatbots
- Text summary
- Sentiment analysis
- Classification of texts
- Automatic translation
- Speech recognition
NLP tries to make human language comprehensible to a machine in five main areas: phonology, morphology, syntax, semantics and pragmatics.
Top Skills for NLP Courses
To have a career in NLP, you should have the knowledge of –
- Python
- fastText
- PyTorch
- PySpark & SparkNLP
- BERT
- CoreNLP
- GPT-3
- TensorFlow
- Alexa API
- NLTK
- Scikit-Learn
- Programming languages like R, Java, Julia
- NLP Libraries
Top NLP Libraries
NLTK - Python library for working with natural language that provides easy-to-use interfaces along with fifty corpus and lexical resources such as WordNet, as well as a set of word processing libraries for classification, tokenization, stemming , tagging , parsing and semantic reasoning.
Polyglot - Natural language toolkit that supports massive multilingual applications, including Catalan and Spanish.
TextBlob - Provides a simple API to dive into common Natural Language Processing (NLP) tasks such as tagging part of speech, extracting phrases from names, sentiment analysis, classification, translation, etc.
spaCy - Python natural language processing library specifically designed to be useful for implementing production-ready systems.
OpenNLP - Machine learning-based toolkit for natural language text processing.
Eligibility to Become an NLP Expert
Candidates with a degree in computer science, mathematics, or statistics can take up NLP courses. You should also have a strong aptitude for mathematics and statistics, and have a good command over data modeling and engineering structures. Research oriented professionals with Ph.D. are highly desirable in the corporate world.
Industrial experience and working knowledge with huge datasets, and software programming is also required. It can be a great career move to take up NLP courses and certifications to validate your expertise as an NLP professional.
Popular NLP Courses Online
- Performing Network, Path, and Text Analyses in SAS Visual Analytics by Coursera
- Advanced Certificate Programme in Machine Learning & NLP by upGrad
- Data Science: Natural Language Processing (NLP) in Python by Udemy
- NLP: Twitter Sentiment Analysis by Coursera
-
NLP Master Practitioner Certificate (Advanced to Specialist) by Udemy
- Applied Text Mining in Python by Coursera
- Foundations of mining non-structured medical data by Coursera
- Hands-on Text Mining and Analytics by Coursera
- Learn BERT - most powerful NLP algorithm by Google by Udemy
Free NLP Courses Online
- Explore natural language processingby Microsoft
- Create a Language Understanding solutionby Microsoft
- Cyber-Physical Systems Design & Analysis by Udacity
- Probabilistic Graphical Models 2: Inference by Coursera
- Mining Massive Datasets by edX
- Introduction to Process Mining with ProM by FutureLearn
- Stylistics: Using Linguistics to Explore Texts and Meaningby FutureLearn
- All Things Text in After Effects by FutureLearn
Demand and Scope for NLP Courses
Natural language processing has emerged as a field of computer science and linguistics that works towards to development of artificial intelligence and other related elements. The usefulness of NLP lies in the fact that it is in charge of promoting and developing the way of communicating with machines or different programs.
The worldwide adoption of cloud technologies and AI in the consumer service segment has led to an increase in the demands for NLP certified professionals. NLP is one of the seven most in-demand tech skills to master in 2021 and the market experts speculate that by 2025, the global NLP market will cross $34 billion, thereby marking a remarkable CAGR of 21.5%.