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Industry-Leading NLP Training Program

Natural Language Processing Program

Text Preprocessing – TF-IDF & Word2Vec – Deep Learning for NLP – Transformers & BERT – Semantic Search – Sentiment Analysis – Question Answering

Gain hands-on experience with modern NLP workflows, text vectorization, transformers, BERT, semantic search, and real-world language AI applications. Build job-ready skills for roles such as NLP Engineer, AI Developer, and Machine Learning Engineer.

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Batch Details & Schedule

Choose a learning format and schedule that fits your lifestyle

Next Batch Starts

18th May 2026

Session Time

07:20 AM to 08:20 AM

Course Duration

4–5 months

Download Complete Curriculum

Course Features & Highlights

Everything you need to become a successful AI & ML professional

Live Projects

Work on real-world projects from day one with industry use cases

Expert Trainers

Learn from industry professionals with 10+ years of experience

100% Placement Support

Dedicated placement cell with assistance until you get hired

Industry Certification

Get certified and boost your resume with recognized credentials

LMS Access

Access to learning materials and recorded sessions

Mock Interviews

Weekly mock interviews to prepare you for real job scenarios

Resume Building

Professional resume preparation and LinkedIn profile optimization

Soft Skills Training

Communication, aptitude, and personality development sessions

Complete Course Curriculum

Comprehensive modules covering every aspect of Natural Language Processing

  • Module 1: Fundamentals of NLP & Text Preprocessing
    • Strings & Regular Expressions
      • Python String Operations
      • Regular Expressions
      • Code Walkthroughs on Python Problems
    • Text Preprocessing
      • Tokenization
      • Stop-word Removal
      • Stemming
      • Lemmatization
      • Text Cleaning Techniques
    • Deduplication
      • Data Cleaning Techniques for Text Datasets
    • N-Grams
      • Uni-gram
      • Bi-gram
      • N-gram Models
  • Module 2: Text Representation (Text-to-Vector)
    • Text Vectorization Concepts
      • Why Convert Text into Vectors?
      • Feature Engineering for NLP
    • Bag of Words (BoW)
      • Concepts & Code Samples
    • TF-IDF
      • Term Frequency & Inverse Document Frequency
      • Why Log is Used in IDF
      • Practical Code Examples
    • Word2Vec
      • Word2Vec with Code Samples
      • Avg-Word2Vec
      • TF-IDF Weighted Word2Vec
    • Text Encodings
      • Text Encoding Techniques for ML & AI
      • Live Practical Sessions
  • Module 3: Deep Learning for NLP
    • Advanced Word2Vec
      • CBOW Architecture
      • Skip-Gram Model
      • Algorithmic Optimizations
    • RNNs & LSTMs
      • Why RNNs?
      • Types of RNNs
      • Need for LSTM & GRU
      • LSTM Networks
      • GRU Networks
      • Deep RNN
      • Bidirectional RNN
    • Transformers & BERT
      • Transformers Architecture
      • BERT
      • Fine-Tuning Techniques
    • Generative Models
      • GPT-1
      • GPT-2
      • GPT-3
    • Advanced Architectures
      • Attention Models
  • Module 4: Real-World Case Studies & Applications
    • Sentiment Analysis
      • Exploratory Data Analysis (EDA)
      • Modeling & Classification
      • IMDB Sentiment Classification
    • Semantic Search
      • Semantic Search Engine for Q&A
      • Design & Code Implementation
      • ML System Design for Product Search Engines
    • Tag Prediction
      • Multi-Label Classification
  • Module 5: Live Sessions & Interview Preparation
    • Classical NLP to State-of-the-Art Models
    • BERT Code Walkthroughs
    • Question Answering Systems
    • Transformers from Scratch

Prerequisites & Eligibility

Course Prerequisites
Basic understanding of programming concepts and Python fundamentals is beneficial
Dedication to complete hands-on labs, case studies, and capstone projects
Commitment for the program duration (3 Months, 200 Session Hours)

Certification

Get industry-recognized certification that validates your skills and boosts your career prospects

  • Industry-recognized NLP course completion certificate from Avowal Data Systems
  • Digital certificate with a unique verification ID for easy authenticity checks
  • Covers text preprocessing, vectorization, deep learning, transformers, and real-world NLP applications
  • Shareable on LinkedIn, resumes, portfolios, and other professional platforms
  • Valid proof of practical NLP and AI skill development for employers and hiring teams
  • Includes project-based learning recognition and course syllabus coverage
Frequent Questions

Find answers to common questions about our NLP training program

  • What will I learn in this NLP course?

    This course covers text preprocessing, vectorization techniques such as BoW and TF-IDF, Word2Vec, deep learning for NLP, transformers, BERT, semantic search, sentiment analysis, and real-world NLP applications.

  • Is prior programming knowledge required for an NLP course?

    Basic programming knowledge is helpful, especially Python fundamentals, but the course starts from core concepts and gradually moves into advanced NLP models and practical implementations.

  • Does this NLP course include hands-on projects and practical sessions?

    Yes, the course includes live practical sessions, code walkthroughs, case studies, and hands-on work on tasks like sentiment analysis, semantic search, question answering, and transformer-based NLP solutions.

  • Will I learn modern NLP tools like BERT and transformers?

    Yes. The curriculum includes transformers architecture, BERT, fine-tuning techniques, and modern NLP workflows used in intelligent search, classification, and language understanding systems.

  • What career opportunities are available after completing NLP training?

    After completing NLP training, learners can pursue roles such as NLP Engineer, Machine Learning Engineer, AI Developer, Text Analytics Specialist, Data Scientist, and AI Research Associate.