This workshop by Association of Data Scientists will give participants a chance to learn NLP from the beginning. This is a compendium of pre-recorded video during a live workshop conducted by ADaSci.

Natural Language Processing (NLP) is one of the key frontiers of Artificial Intelligence and has been in trend since the rise in popularity of conversational AI. When it comes to communicating with machines, NLP offers some of the best tools and techniques to facilitate the conversation in a human language. Starting from review analysis to intelligent chatbots, there are a variety of interesting applications of NLP. While a lot of potential of NLP has been explored, a lot more is yet to come. 

With an increase in the interesting applications of NLP across the industries, there has been an increasing demand amid professionals to understand the technology, its working and developing interesting applications based on it. To facilitate the same, this workshop comes up with a learning dose where the participants will get hands-on exposure to implementing NLP techniques in Python from scratch.

Format: Pre-recorded videos of more than 5 hours & Colab notebooks


  1. Introduction to Natural Language Processing
    1. Overview of the Natural Language Processing
    2. Syntax, semantics and pragmatics
    3. Representation of texts
    4. Tokenization, N-Grams
    5. Overview of NLTK in Python
  2. Text Analytics
    1. Features of textual data
    2. Reading and analyzing text data in the Python program
    3. Stemming
    4. Lemmatization
    5. Part-Of-Speech (POS) Tagging
    6. Building Corpus
    7. Feature extraction
    8. TF-IDF
    9. Named Entity Recognition
    10. Sentiment Analysis
    11. Visualization of insights
  3. Text Classification
    1. Overview of text classification
    2. Machine learning algorithms for text classification
    3. Sentiment Classification
    4. Review classification
  4. Word Embedding and Word2Vec
    1. Bag of Words
    2. Continuous Bag of Words (CBOW)
    3. Skip Gram
    4. Negative Sampling
    5. Implementation of Word2Vec
  5. Sequence Modeling
    1. Overview of Sequence Modeling
    2. Encoder-Decoder Model
    3. Long-Short Term Memory (LSTM) Networks
    4. Multi-Class Text Classification using LSTM
    5. Sequence to Sequence (Seq2Seq) Modeling using LSTM
  6. Transformer
    1. Overview of Transformers
    2. Bidirectional Encoder Representations from Transformers (BERT)
    3. Implementation of BERT

Learning Outcome

  • Clear concept of NLP techniques with fundamentals
  • Understanding of textual data representation
  • Knowledge of text preprocessing
  • Hands-on knowledge of implementing NLP techniques
  • Strong fundamentals for developing any NLP-based application
  • Practical knowledge of advance concepts such as transformers



  • Knowledge of Python programming language
  • Basic knowledge of linear algebra including vectors, matrices and tensors
  • Familiarity with Google Colab and GPU environment 


Required Tools

  • Any editor to run the Python programs (preferably Google Colab Notebooks)
  • If working on an editor, WordCloud, TextBlob, TensorFlow and Keras must be installed

Access the workshop at $19.99



After payment, you will receive an email with download link of the whole workshop (Videos & notebook links).

ADaSci Members get free access to the workshop

  1. Jameer 6 months ago

    Need to work in NLP

  2. Michael Aydinbas 5 months ago

    Can we have a schedule? Are there any breaks?

  3. Sandeep Verma 5 months ago

    When is the next workshop. Unfortunately missed it today.

  4. Igor G. 5 months ago

    Will there be another one? Is there a recording?

  5. Sakeena 5 months ago

    I need for the job in data entry

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