4 months
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About

By the end of this Natural Language Processing Specialization offered by Coursera in partnership with Deeplearning, you will be ready to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots. 

Visit the official programme website for more information

Overview

Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language. 

This technology is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio.

These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future.

This Natural Language Processing Specialization offered by Coursera in partnership with Deeplearning is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper. 

Applied Learning Project

This Specialization will equip you with machine learning basics and state-of-the-art deep learning techniques needed to build cutting-edge NLP systems:

  • Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.
  • Use dynamic programming, hidden Markov models, and word embeddings to autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.
  • Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions. 
  • Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, question-answering, and to build chatbots. Learn T5, BERT, transformer, reformer, and more with ????  Transformers!

Programme Structure

Courses included:

  • Natural Language Processing with Classification and Vector Spaces
  • Natural Language Processing with Probabilistic Models
  • Natural Language Processing with Sequence Models
  • Natural Language Processing with Attention Models

Key information

Duration

  • Part-time
    • 4 months
    • 8 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Intermediate Level

  • Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & statistics

Tuition Fee

To alway see correct tuition fees
  • International

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 4 months.
  • National

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 4 months.

You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access. 

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. 

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Our partners

Natural Language Processing
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