Natural Language Processing; Confluence of Artificial Intelligence and linguistics. It involves intelligent analysis of written language
Duration : 6 months Classes : 36 Days : Weekdays / Weekends
NLP is a branch of AI that enables computers to comprehend, generate, and manipulate human language. NLP has helped enable the era of generative AI, from the communication skills of large language models (LLMs) to the ability of image generation models to understand requests.
As AI-powered devices and services become increasingly more intertwined with your daily life and the world, so does the impact that NLP has on ensuring a seamless human-computer experience. This professional-level training addressing NLP tasks from the perspective of Artificial Intelligence. This training tackles the advanced NLP together with introduction to the fundamental concepts of Natural Language Processing (NLP) with Python.
Learn more about this impactful AI subfield.
Hands-on experience is a crucial component of this training. Students are exposed to real time project, after completion of each module.
Here is your chance to learn this highly in-demand set of skills with a gentle introduction to the topic that leaves no stone unturned.
Target Audience:-
- Data Analysts and Data Scientists
- AI / ML / DS - Engineers
- Fresh Guaduates
- IT Professionals looking to transition into AI and Data Science roles
- Research Scholars and AI Enthusiasts
Learning Outcomes:-
- Understand the core concepts of NLP
- Explain key linguistic principles
- Build and evaluate machine learning models for NLP
- Advanced NLP applications like text generation and sequence labeling
- Develop and deploy NLP applications
- Analyze and interpret model outputs
- Demonstrate proficiency in NLP tools and frameworks
- Prepare for technical interviews or research roles
Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training
Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas
This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.
Module 1: Mathematical & Programming Prerequisites
✔ Recap: Python for data science
✔ Recap: Probaility and basic Linear Algebra
✔ Introduction to Machine Learning fundamentals
Module 2: Linguistic and Text Processing Basics
✔ Introduction to NLP
✔ Text Pre-processing: Tokenization, Stopword Removal, Stemming, and Lemmatization
✔ N-gram Models
Module 3: Feature Engineering and Classical Models
✔ Vector Representation: One-Hot Encoding, Bag-of-Words (BoW), and TF-IDF.
✔ Basic Text Classification
✔ Part-of-Speech (POS) Tagging
✔ NER
Module 4: Word Embeddings and Neural Networks
✔ Word Embeddings: Word2Vec, GloVe
✔ Introduction to basic Neural Networks for Text
Module 5: Sequential Models (RNNs/LSTMs)
✔ Recurrent Neural Networks, LSTMs and GRUs
✔ Handling sequential data and dependency
✔ Introduction to the Sequence-to-Sequence architecture
Module 6: Transformers and Attention
✔ The Attention Mechanism
✔ The Transformer architecture
✔ Concepts of Pre-training and Fine-tuning
Module 7: Large Language Models
✔ Introduction to LLMs
✔ Utilizing the Hugging Face ecosystem
✔ Techniques: Prompt Engineering, In-Context Learning, and efficient Fine-tuning
Module 8: Advanced NLP Applications
✔ Machine Translation
✔ Text Summarization
✔ Question Answering
✔ Information Extraction
✔ Chatbots and conversational AI
Module 9: NLP with Machine Learning
✔ Text classification
✔ Sentiment analysis
✔ Spam detection
Module 10: Capstone Project
✔ Build an NLP application (e.g., sentiment analyzer, chatbot)
Student Reviews
Bhawana
Fabulous NLP + ML course
I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.
Harish
Excellent ML course!
The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.