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Top 5 NLP Certifications

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As we move further into a data-driven world dependent on AI technologies, Natural Language Processing, or NLP, is becoming one the most demanded skills. It is present nearly everywhere, but most notably in web searches, advertisement, customer service, language translation services, sentiment analysis, and more. 

NLP certifications are crucial for an individual looking to be a leader in this field. 

Here are the top 5 NLP Certifications currently available:

1. Natural Language Processing Specialization (Coursera)

This specialization course is aimed at preparing you to design NLP applications for question-answering and sentiment analysis. You will also learn how to develop language translation tools, summarize text, and build chatbots. 

The course was designed and is taught by experts in NLP, machine learning, and deep learning. Two of those experts are Younes Bensouda Mourri, an instructor of AI at Stanford University, and Lukasz Kaiser, a Staff Research Scientist at Google Brain who co-authored Tensorflow. 

Here are some of the main aspects of this course: 

  • Logistic regression, Naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, and translate words
  • Dynamic programming, hidden Markov models, and word embeddings for auto correction
  • Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in Tensorflow and Trax
  • Encoder-decoder, causal, and self-attention, along with T5, Bert, transformer, and reformer
  • Intermediate Level
  • Duration: 4 months, 6 hours/week

2. Natural Language Processing with Python Certification Course (Edureka)

This course covers the fundamentals of text processing, and you will eventually classify texts using machine learning algorithms. You will encounter various concepts like Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing, and more. You will use Python’s NLTK package and learn how to build your own text classifier with the Naïve Bayes algorithm.

Here are some of the main aspects of this course: 

  • Topics: Overview of Text Mining; Need of Text Mining; Natural Language Processing (NLP) in Text Mining; Applications of Text Mining; OS Module; Reading, Writing to text and word files; Setting the NLTK Environment; and Accessing the NLTK Corpora
  • Hands-on/demo practice
  • NLTK package
  • Text processing and classification
  • Build your own text classifier
  • Experience in Python programming and a solid understanding of machine learning concepts required

3. Natural Language Processing in TensorFlow (Coursera)

This course is aimed at software developers looking to build AI-powered algorithms. It teaches you the best TensorFlow practices, and you will build NLP systems using it. You will also learn to process text, including tokenizing, as well as resprest sentences as vectors. Other parts of this course involve applying RNNs, GRUs, and LSTMs in Tensorflow. 

It is recommended that you take the first 2 courses of the TensorFlow Specialization and have a solid understanding of coding in Python before taking this course.

Here are some of the main aspects of this course: 

  • Train an LSTM on existing text
  • Build NLP systems using TensorFlow
  • Applying RNNs, GRUs, and LSTMs in TensorFlow
  • Intermediate Level
  • Duration: 14 hours

4. Natural Language Processing in Python (Datacamp)

This course provides you with the core NLP skills needed to convert data into valuable insights. You will learn how to automatically transcribe TED talks, and the course will introduce popular NLP Python libraries such as NLTK, scikit-learn, spaCy, and SpeechRecognition. 

Here are some of the main aspects of this course: 

  • Build your own chatbot
  • Transcribe audio files
  • Extract insights from real-world sources
  • Transcribe Ted Talks
  • 6 courses total
  • Duration: 25 hours

5. Introduction to Natural Language Processing in Python (Datacamp)

This course teaches you the fundamental NLP techniques using Python, which you will then apply to extract insights from real-world text data. You will learn how to identify and separate words, extract topics in a text, and build a fake news classifier. The course will also teach you how to use basic libraries like NLTK and others that use deep learning. 

Here are some of the main aspects of this course: 

  • NLP basics like identifying and separating words
  • Build your own fake news classifier
  • Basic and advanced libraries
  • 4 courses total
  • Over 50 exercises and 15 videos
  • Duration: 4 hours

Alex McFarland is a historian and journalist covering the newest developments in artificial intelligence.