Natural Language Processing with Python   Live Classes

Natural Language Processing using Python Course focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language.

Scheduled Live Classes
24/7 Live Labs
24/7 Live Support

Why take this Course?

Natural Language Processing is an upcoming technology so the scope is increasing continuously.
NLP is one of the 7 most in-demand tech skills to master in 2021.
By 2025, the global NLP market is expected to reach over $34 billion.


Natural language processing (NPL) is an extremely difficult task in computer science. Languages present a wide variety of problems that vary from language to language. Structuring or extracting meaningful information from free text represents a great solution, if done in the right manner. Previously, computer scientists broke a language into its grammatical forms, such as parts of speech, phrases, etc., using complex algorithms. Today, deep learning is a key to performing the same exercises.

In this module, first we will learn about the basics of the Python language, NLP, and Deep Learning. We will cover the beginner-level codes in the Pandas, NumPy, and SciPy libraries. We will also briefly discuss commonly used libraries in NLP, with some basic examples. Finally, we will discuss the concepts behind deep learning and some common frameworks, such as TensorFlow and Keras. And then we will move on to providing a higher-level overview of NLP.

When dealing with languages and words, we might end up classifying texts across thousands of classes, for use in multiple natural language processing (NLP) tasks. Much research has been undertaken in this field in recent years, and this has resulted in the transformation of words in languages to the format of vectors that can be used in multiple sets of algorithms and processes.

This module offers an in-depth explanation of word embeddings and their effectiveness. We introduce their origin and compare the different models used to accomplish various NLP tasks.

This module covers the use of contextual information across text. With textual work in any form, i.e., speech, text, and print, and in any language, to understand the information provided in it, we try to capture and relate the present and past contexts and aim to gain something meaningful from them. This is because the structure of text creates a link within a sentence and across sentences, just like thoughts, which are persistent throughout. Traditional neural networks lack the ability to capture knowledge from previous events and pass it on to future events and related predictions.

In this module, we will introduce a family of neural networks that can help us in persisting information over an extensive period.


In this module, we will create a chatbot. We will do so in a progressive manner and will make the chatbot in two layers. The first section of the module introduces the chatbot concept, followed by a section on implementing a basic rule-based chatbot system. The last section discusses the training of a sequence-to-sequence (seq2seq) recurrent neural network (RNN) model on a publicly available dataset. The final chatbot will be able to answer specific questions asked of the dataset domain on which the model has been trained.

This module concludes the course with the implementation of sentiment analysis. The first section of this module details the approach mentioned, followed by a second section devoted to its implementation, using TensorFlow.

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Course details

University of Emerging Technologies’ Natural Language Processing using Python Course focuses on step-by-step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learned content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics, and Machine Learning have been discussed.

This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification.

Towards the end of the course, we will be discussing various practical use cases of NLP in the python programming language to enhance your learning experience.

Total Duration of the course is 160 hours

Language: English

University of Emerging Technologies provides you with Role based education, experiential learning, live classes, 24*7 live labs and live support, personalized machines, real life projects, industry oriented, job focused content along with career prep support.

University of Emerging Technologies’ Natural Language Processing using Python course is a good fit for the below professionals:


  • From a college student having exposure to programming to a technical architect/lead in an organization

  • Developers aspiring to be a ‘Data Scientist'

  • Analytics Managers who are leading a team of analysts

  • Business Analysts who want to understand Text Mining Techniques

  • 'Python' professionals who want to design automatic predictive models on text data

Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users.

NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data.

  • The prerequisites for this NLP course are ability to code in Python programming language.

  • Basic understanding of Machine Learning concepts.

Natural Language Processing with Python Course Completion Certificate

University of Emerging Technologies' Natural Language Processing with Python Course Completion Certificate is awarded by The Emerging Tech Foundation, an Independent Not-for profit organisation globally recognised for the emerging technologies.


You will be working on the virtual live lab environment that we provide which will give you the access to all the tools and softwares required for this particular course. The stepwise guide for accessing these services will be available in the LMS and University of Emerging Technologies support team will assist you 24*7 in case you have any doubts.

This course includes eight assignment projects which will hone your skills as per current industry standards and prepare you for your future career needs.

The 2 industry-based certification projects will test your ability to work with real-world data set.

Your certification project is an opportunity for you to explore an interesting problem of your choice in the context of a real-world data set. Projects can be done by you as an individual, or in teams of 2-4 students. Educators and Academic Enablers will consult with you on your ideas, but of course the final responsibility to define and execute an interesting piece of work is yours. Your project will be worth 20% of your final class grade, and will have 4 deliverables:

  • Proposal: 1 page (10%)

  • Midway Report: 3-4 pages (20%)

  • Final Report: 5-6 pages (40%)

  • Poster Presentation: (30%)

In this course, you will learn about scenario-based examples and have hands-on experience to be able to utilize the tools and prompts.

Any computer with standard Windows and or Mac with at least 2 GB RAM and a Core-I3 processor.


Total duration of this course is 160 hours divided over a period of 7-8 weeks. Out of 160 hours, 60-80 hours are dedicated for online sessions and remaining for live practical sessions where you will be working on real life industry focused projects.

You will be spending a minimum of 12 hours for online sessions every week.

Using your LMS, you will always have access to the recorded sessions. And you can also make a special request to attend the live session in some other batch (on the basis of availability).

Virtual Lab is a cloud-based environment where you can execute all your practicals and assignments, work on real-life projects effortlessly.

Using these virtual labs, students can avail the various tools for learning, including additional resources and environment for the course. This will save students from all the hassle of downloading and maintaining these softwares in their own machine.

You’ll be able to access the virtual lab via your browser which requires minimum hardware configurations. If you are stuck somewhere, our support team is available 24*7 to help you out.

All the details to access virtual labs are available on you LMS.

You can interact with the educator during the class using the chat feature.

We provide 24*7 live support to all our students via live chat feature and email. Our academic enablers are always available to help you throughout the course.

Yes, you can interact with other students enrolled in the same course using the course forum where you can discuss about the class and the course material. In case you want to interact with students enrolled in some other course, you can do that using the common forum available for all. University of Emerging Technologies believes in community building and social learning by connecting learners to each other so that they can discuss concepts, work on projects, solve problems and share innovative ideas.

Yes, we have group projects so that students can engage with each other and share ideas.

You will be graded on the basis of weekly quizzes, assignments, lab engagements, midterm and final exams.

Our online classes are Instructor paced.

Yes, the course material is accessible to the students even after the course is over in the form or PDF documents and recorded lectures.

Yes, you will get assistance for job interviews. We have a dedicated team for career guidance and counselling.

Enrollment is a commitment between you and us in which you promise to be a successful learner and we promise to provide you with the best possible learning environment. Our sessions consist of online interactive live classes, live labs and 24*7 live support along with career prep support. Enroll with us and experience the complete learning environment instead of just a demo session.