Natural Language Processing in Data Science

Master NLP for business success: drive insights, automation, and customer experience

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Program Overview

Natural Language Processing (NLP) is a field of artificial intelligence and computational linguistics that focuses on the interaction between computers and human language. It involves developing algorithms and models to enable computers to understand, interpret, and generate natural language.

NLP techniques and models are employed to extract insights, derive meaning, and make predictions from textual data.

By incorporating NLP into data science projects, analysts and data scientists can leverage the rich information contained in textual data, gain insights, and build predictive models that incorporate the language understanding capabilities necessary for many real-world applications.

Uptut specialises in providing professional training courses across industries, focused on Natural Language Processing (NLP). We are dedicated to equipping organisations with the necessary knowledge and skills to harness the power of NLP in their business operations.

Our tailor-made courses address the specific needs and challenges faced by organisations in leveraging NLP technologies. Our team of experts bring their expertise, tailored approach, hands-on learning, and comprehensive curriculum to make Uptut a reliable choice for organisations looking to upskill their teams in NLP and unlock the potential of language data in their business operations.

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Training Objectives

  • Gain a solid understanding of the fundamental concepts, techniques, and models used in Natural Language Processing.
  • Learn the various applications of NLP in real-world scenarios and industry domains. 
  • Gain hands-on experience in applying NLP techniques such as text preprocessing, sentiment analysis, text classification etc.
  • Develop practical skills in implementing NLP solutions using popular libraries and frameworks.
  • Learn how to customize and fine-tune NLP models to address their organisation's specific requirements and domain-specific challenges.
  • Receive training on evaluation metrics and techniques to assess the performance and quality of NLP models
  • Learn how to integrate NLP capabilities into existing business workflows, systems, or applications.

Core training modules

  • Introduction to Natural Language Processing
  • An overview of NLP, its applications, and its significance in data science.
  • Text Preprocessing
  • Techniques for cleaning and transforming raw text data before further analysis.
  • Tokenization and Lemmatization
  • Breaking down text into individual words or tokens and reducing them to their base or root form.
  • Part-of-Speech Tagging
  • Assigning grammatical tags to words in a sentence for syntactic analysis.
  • Named Entity Recognition
  • Identifying and classifying named entities like people, organizations, and locations in text.
  • Sentiment Analysis
  • Analyzing and determining the sentiment or emotional tone expressed in textual data.
  • Text Classification
  • Categorizing text into predefined classes or categories based on its content or characteristics.
  • Topic Modeling
  • Extracting latent topics or themes from a collection of documents.
  • Word Embeddings
  • Representing words as dense vectors to capture semantic relationships and meaning.
  • Language Modeling
  • Developing models that generate coherent and contextually relevant text.
  • Sequence Labeling 
  • Assigning labels or tags to each element in a sequence, such as part-of-speech or named entity labels.
  • Machine Translation
  • Automatically translating text from one language to another.
  • Question Answering
  • Building systems that understand and generate responses to questions based on given contexts or documents.
  • Text Summarization 
  • Generating concise summaries of longer texts while preserving key information.
  • Information Extraction
  • Identifying and extracting structured information from unstructured text, such as relationships and entities.
  • Chatbot Development
  • Creating conversational agents capable of understanding and responding to user queries.
  • Text Similarity and Clustering
  • Measuring the similarity or clustering of text documents based on their content.
  • Language Generation
  • Generating natural language text for various applications, such as dialogue systems or content generation.
  • Speech Recognition
  • Converting spoken language into written text.
  • Ethical Considerations in NLP
  • Exploring ethical implications, biases, and privacy concerns in NLP applications.

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AWS,, DASA & more
100% Live
on-site/online training
Labs and capstone projects
Lifetime Access
to training material and sessions

How Does Personalised Training Work?

Skill-Gap Assessment

Analysing skill gap and assessing business requirements to craft a unique program



Customising curriculum and projects to prepare your team for challenges within your industry



Supplementing training with consulting support to ensure implementation in real projects


Why Natural Language Processing for Your Business?

  • Unlocking Language Data: By leveraging NLP techniques, you can tap into vast amounts of textual information and transform it into actionable knowledge.
  • Improved Customer Experience: NLP allows you to analyse customer feedback, support tickets, social media interactions, and reviews, enabling you to understand customer sentiment, preferences, and needs.
  • Enhanced Business Intelligence: By leveraging NLP techniques, you can gain deeper insights from text data, uncover patterns, and detect trends. This enables your business to make data-driven decisions, identify market opportunities, perform competitive analysis, and drive innovation within your business.

Who will Benefit from this Training?

  • Data Scientists
  • Software Engineers
  • Data Analysts
  • Business Analysts
  • Data Engineers 

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Frequently Asked Questions

1. What are the pre-requisites for this training?
Faq PlusFaq Minus

The training does not require you to have prior skills or experience. The curriculum covers basics and progresses towards advanced topics.

2. Will my team get any practical experience with this training?
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With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.

3. What is your mode of delivery - online or on-site?
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We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.

4. Will trainees get certified?
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Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.

5. What do we do if we need further support after the training?
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We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.

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