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.
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When searching “Best NLP courses” online, one will find themselves flooded with options as AI, ML, NN, and NLP are currently some of the hot selling topics. However, before jumping right into finding the best NLP course, one must understand their knowledge of the subject. The idea of the best NLP course may vary based on whether one is on the beginner’s level or want to deepen their lengths of knowledge.
Therefore, before randomly choosing any natural language processing certification course available online or offline, one needs to assess their requirement. It is needless to say that an advanced level NLP certification will not help much if the person’s fundamentals are not clear.
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!
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Best NLP Courses
1. Microsoft: Explore Natural Language Processing
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.
2. Microsoft Certified: Azure AI Fundamentals
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.
3. Advanced Certificate Programme in Machine Learning and NLP (upGrad)
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!
4. Google Developers Certification
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
5. Amazon: Machine Learning University course on Natural Language Processing
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.
The course materials are available on GitHub, and interested candidates can easily access the tutorials via Amazon MLU’s YouTube page.
Apart from these online NLP courses, here are some other choices offered by reputed institutes:
6. Advanced Certificate Programme in Machine Learning and Deep Learning (upGrad)
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.
7. From Languages to Information (Stanford University)
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
8. Natural Language Processing with Deep Learning (Stanford University)
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.
9. Deep Learning for Natural Language Processing (University of Oxford)
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.
10. Natural Language Processing (University of Washington)
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.
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Here are some questions one can ask themselves to find the best NLP courses.
Before choosing the natural language processing certification, one needs to ask themselves these very simple yet significant questions to find out the NLP course that best suits their needs.
- How do I like to learn?
First, determine which type of learner you are to choose the right NLP certification. Whether auditory ( who prefers learning by hearing and speaking), visual ( learns best by seeing graphs, charts, and seeing information), or kinesthetic ( likes having a hands-on approach like doing a project to learn something).
Once, understood, choose the course that best matches the learning styles, which will majorly help to understand the concepts faster.
If one does not prefer spending a lot of time going through books, then they should avoid courses that have a lot of reading materials provided.
- How much time will I be investing in the course?
One must look for the duration of the course and determine whether or not they will be able to complete that alongside their usual routine. If someone is working, they might not be able to complete a full-time course or a course that demands more than 3 hours a day or 20 hours a week.
Therefore, it is better to assess the chances of the course being completed by the person rather than giving up halfway due to time constraints. Also, some courses might include self-doing projects and tasks that take up additional time.
- What type of feedback will I be getting?
It is always better to have constant feedback throughout the course. Especially if one is a beginner in this topic, they might require feedback on how they can learn the topic better or if they are misinterpreting any concept. If one is unaware of what to improve while they are in their learning phase, they might end up with a significant knowledge gap to bridge later.
Therefore, checking beforehand whether or not any feedback system is there is an important aspect.
- How the assessment will be done?
The assessment process of determining whether or not someone has successfully completed the course is very important. One needs to look for if the course will be taking any exam to give certification or will require to complete certain tasks to pass as qualified.
A course that does not has any assessment criteria will not be helpful if someone is a beginner in the field, as exams, presentations, projects or such assessments helps the learner to understand their knowledge gap and areas of improvement.
- What will be the group size in which I will be taught?
Knowing whether or not one will be taught in a class of hundred, or will be given one-on-one attention, or will not be having any personal interaction is also a factor in judging the suitability of a course.
In most online courses, pre-recorded video lectures and study materials are provided and no personal guidance is given. If that is suitable for someone, then they can opt for it. However, if someone is in need of personal mentorship and guidance then those courses might not be ideal for them.
- What are the additional facilities?
In the case of online courses, the additional facilities may include, access to an online library or being added to a community of like-minded people who share insightful knowledge about the topic and related industry. Or it can also be getting a discount on purchasing other courses.
However, not every course might have such facilities, especially those ones which are already free of cost!
- What are the topics covered in the course?
One also needs to go through the course curriculum beforehand, in order to have an overview of what they will be learning from that course.
If someone is of beginner level, they should opt for courses that start teaching from the very basics of the topic and end at the basics of intermediate to advanced level. On the other hand, one who has an idea of NLP should opt for a course that does not waste much time on clearing the basics and discusses the intermediate and advanced topics.
- Who is going to teach me?
The quality of a course majorly depends on the credibility of the person or institution that has curated it. Therefore, it is important to know, who is responsible for making the course and how much their expertise is in the topic of discussion.
Wasting time by learning from non-credible sources is the last way for a beginner to start their journey.
- How the course has helped others or what are the reviews of it by the prior graduates?
Lastly, it is also important to check whether or not the course has good reviews from the prior students.
It is hard to judge a book by its cover, and one should refrain from doing so when it comes to learning and career growth. A course might appear very fancy and full of insightful topics to learn from, but in reality can either be very complex, tedious, repetitive, or not as informative as it claims to be. Hence, looking for reviews is the safest option before making the final call.
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.