Although Natural Language Processing (NLP) has been with us for quite some time, it has only recently gained industry-wide attention, thanks to Deep Learning. Today, NLP is a core competence area in Data Science and IT, with applications spanning across sectors that rely on harnessing language data’s potential.
Essentially, NLP applications are designed to extract relevant and meaningful information from natural human language data and impart machines with the ability to interact with humans.
Learn AI ML Courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.
What is Natural Language Processing?
To put it in plain words, Natural Language Processing refers to the technique of using advanced computer programs to analyze, understand, and generate natural human languages. Natural Language Processing is a subset of Deep Learning that combines the power of Computer Science and Linguistics to make human languages accessible and legible to machines.
By interpreting unstructured data of one or more languages (generated from multiple sources like text, audio, etc.), NLP algorithms perform a host of functions like sentiment analysis, spelling, and grammar check, named entity recognition, machine translation, text summarization, and social media monitoring, to name a few.
Deep Learning Engineers and NLP Scientists primarily focus on finding innovative data-driven solutions to business challenges. Chatbots and virtual assistants (Siri and Alexa) are two of the most outstanding NLP models that are transforming the face of customer support.
NLP is an emerging technology that’s rapidly gaining traction in the industry. NLP technology powers targeted advertising, voice assistance, grammar checkers, autocorrect, and language translators. As NLP applications continue to expand further, there’ll be a massive upsurge in NLP experts’ demand.
So, if you want to perfect the nuances of Natural Language Processing, now’s the time to enroll in an NLP course!
Wondering what are the best NLP courses right now? Here’s a list of ten best online NLP courses for you!
Best NLP Courses
This is a beginner-level NLP course that focuses on teaching learners the NLP basics by leveraging the Microsoft Azure platform. Azure offers a host of services like text analytics, translation, language understanding, etc., that make it super easy to develop NLP applications.
This 2-hour course includes four modules – Analyze text with the Text Analytics service, Recognize and synthesize speech, Translate text and speech, and Create a language model with Language understanding.
This is an advanced level certification course by Microsoft that allows professionals to master AI and ML concepts and workloads and learn how to implement them on Azure. The course measures five essential skills – describing AI workloads and considerations, describing fundamental principles of machine learning on Azure, describing features of computer vision workloads on Azure, describing features of Natural Language Processing (NLP) workloads on Azure, and describing features of conversational AI workloads on Azure.
Anyone with basic programming knowledge, from both technical and non-technical backgrounds, can enroll in this course.
upGrad offers this short-term (six-month) course for working professionals. Covering over 250 hours of learning, the course consists of five modules – Data Science Tool Kit, Statistics and Exploratory Data Analytics, Machine Learning, Machine Learning II, and Natural Language Processing. Learners also explore tools like Python, NLTK, Pandas, Numpy, Scikit-Learn, MySQL, and Excel. Plus, the course includes more than five industry projects, case studies, and assignments.
Students get dedicated mentorship and plenty of opportunities to interact with industry experts from Gramener, Actify, and Flipkart. upGrad offers placement assistance to all candidates to help launch their careers. On course completion, students get a PG certificate from IIIT-Bangalore.
FYI: Free nlp online course!
This is a level one certificate course designed to test your foundational knowledge of working with and integrating ML techniques into real-world solutions. Google offers this course in partnership with TensorFlow.
Candidates opting for this certification must understand Convolutional Neural Networks, Natural Language Processing, and real-world image data. One must also know how to developing TensorFlow models using Computer Vision.
Candidates who successfully pass the exam can join TensorFlow’s Certificate Network and display their certificate and badges on their resume, GitHub, and social media handles, thereby attracting potential employment opportunities.
Also Read: Deep Learning Free Online Course
In 2016, Amazon launched its in-house Machine Learning University (MLU), intending to deliver courses that can help ML practitioners upskill and expand their domain knowledge.
Taught by Amazon expert Cem Sazara (Applied Scientist), this course helps learners develop a deep understanding of data preprocessing, model evaluation, and ML resources. Also, they gain practical knowledge of NLP specific model training and applications.
Apart from these online NLP courses, here are some other choices offered by reputed institutes:
Another six-month course from upGrad, this ML and DL program also includes five modules – Data Science Tool Kit, Statistics and Exploratory Data Analytics, Machine Learning, Machine Learning II, and Deep Learning. While learners are introduced to all Machine Learning and Deep Learning concepts, they also work on industry projects, case studies, and assignments to sharpen their real-world skills.
The tool suite consists of Python Keras, TensorFlow, MySQL, Excel, Numpy, Matplolib, and Scikit-Learn. Students get one-on-one mentor support, placement assistance and participate in hiring drives and resume building sessions.
This course is an excellent choice for beginners. It includes relevant learning materials like a Python tutorial, text processing with Unix tools, Naive Bayes and sentiment analysis, logistic regression, information retrieval, vector semantics, neural embeddings, recommender systems, and much more. It is a 3-month online course that is great for both students and professionals.
Must Read: Deep Learning Vs NLP
This is an advanced NLP course that requires candidates to be proficient in Python and be well-versed with the fundamentals of calculus, statistics, and machine learning. The course focuses on teaching students about natural languages’ computational properties, neural network models for understanding natural languages, and other associated concepts like word vectors, syntactic, and semantic processing.
By the end of this course, learners gain a deep understanding of advanced neural network algorithms for processing linguistic data.
This advanced NLP course focuses on studying the recent advances in analyzing and generating speech and text using recurrent neural networks (RNNs). Students must understand various Mathematical concepts like Probability, Linear Algebra, and Continuous Mathematics. Also, they must be familiar with basic ML concepts.
The course teaches students to understand the definition of a range of neural network models, neural implementations of attention mechanisms and sequence embedding models, derive and implement optimization algorithms for these models, and execute and evaluate the standard neural network models for languages.
This course encompasses all the relevant NLP topics, including text, classification, tagging, parsing, machine translation, semantic, discourse analysis, and Hidden Markov Models, among other things.
Apart from gaining classroom knowledge, students work on exciting projects like multilingual representations and parsing, coding with natural language, detecting and extracting events, interactive learning for semantic parsing, relation & entity extraction.
If you wish to pursue Machine Learning, Deep Learning, and NLP, there are plenty of fantastic choices today! Since most institutes are now offering their best NLP courses online, you can learn and upskill from the comfort of your home.
If you are looking for a short term Machine Learning Course check out IIT Delhi’s Machine Learning Program in association with upGrad. IIT Delhi is one of the most prestigious institutions in India. With more the 500+ In-house faculty members which are the best in the subject matters.
Now the only question remains – are you ready to master NLP?
What are the main challenges of natural language processing?
Natural language processing is a challenge because it requires human-like reasoning, and the ability to understand context. For example, a computer can understand Mary is hurt, but not Hurt Mary. In order to fully understand natural language processing and its nuances, a computer must be able to think as if it were a human. This is a difficulty because computers have a limited memory and can only follow instructions that have been clearly programmed into the machine.
What is natural language processing?
Natural language processing (NLP) is the field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. It is related to computational linguistics and computational semiotics. NLP-based applications are used in many areas, including natural language understanding systems, information retrieval, question answering systems, speech recognition, machine translation, text mining, chat bots, and image captioning.
What is the future of natural language processing?
Natural language processing is one of the most rapidly growing fields in the computer science field. Many companies are developing NLP software so that it can be used to provide more intelligent search bots, better and more accurate translations, voice recognition and even to automating more and more of the drudgery involved in saving, sifting and processing of text and documents. NLP software is already being used to power automated phone systems and stock market analysis. In the future it's expected that NLP software will be used to help doctors and scientists compile reports from research done from thousands of different studies on a single topic.