LLM - Build GenAI Solutions

✅ Learn the fundamental concepts and techniques of NLP, including text preprocessing, word embedding, and deep learning models.
✅ Sentiment analysis, Text classification, Text Summarization and Text generation
✅ Don't just use available Libraries, Buils NLP & LLM solutions ground up

DURATION

8 weeks (42 Hours)
Starting soon, January'24

LOCATION

Instructor led online sessions
Weekdays (Evening hours) / Weekend sessions

EXPERT INSTRUCTORS

Industry experts along with NLP researchers with real world experiences

CURRICULUM

Learning hands-on through practical NLP applications
Solve 5+ Real Industry Projects
Build LLM applications ground up

Pre-requisites

Basic programming constructs in any coding language (Python preferred)
Basic understanding of Machine Learning algorithms

Course Investment

INR 23998/-

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Your potential future recruiters

Why Learn LLM From Setu?

Practical skills

Comprehensive Curriculum designed to meet current Industry demand.

Industry immersive

- Learn hands on
- On Real World Use cases
- On Real industry data
- Build LLM based solutions

SETU’s Proprietary IDE

Learn on SETU’s OpenAI integrated proprietary Data Environment

Mentoring & Networking

Learn and be mentored by top Data Leaders on the projects.
Build a strong network with them, keep yourself ahead of the curve.

Problem Solving & Story Telling

Not just technical modeler, build the most demanded skills of Problem solving and Data Driven story telling.
Be the Thought Partner to business & functional leaders, not just an executioner.

Peer Learning

We learn 10% by Reading, 20% by Listening, 30% by Watching.
We learn 70% by discussing. We learn 80% by Practicing & Experiencing
Peer Learning grows you faster than Solo learning.

Meet The Leaders

Shikha Jain

Associate Faculty,Content Associate - SETU

Data Scientist | GenAI Enthusiast | Researcher | Expertise in Transformers, GenAI Models, LLMs, NLP & Deep Learning

Course Curriculum

Week 1

Fundamentals

Introduction to NLP - Basics, Applications and Future Scope
Working with web data - Collection, Inspection and Scrapping
Data Preprocessing

W 2-3

Applications of NLP

Build your own ML Model for Media Sentiment Analysis - Media Data Analysis
Working with highly unstructured data - Scrapping, Noise Removal and Pattern Matching
Feature Engineering - NLP Pipeline
Text Vectorization - BOW, n-gram, TF-IDF
Implementation of ML algorithms in NLP - Clustering, Topic Modelling, Sentiment Analysis

W 4-5

Advanced Application

Building ML model for NLP - News Data Analysis
Introduction to Advanced NLP Tools - Word Embedding and Deep Learning in NLP
Chat GPT - Introduction and Prompt Engineering for 20+ Applications

W 6-8

large Language Model

Sequence to Sequence Models -- Attention Mechanisms -- Transformer Fundamentals -- Transformer Architecture
Implement a Transformer Based Model for Text Processing
Embeddings -- Pre-training -- BERT application -- GPT evolutions -- Generative Pre-trained Transformers
Build an application of Text Generation , Conditional Text Generation and Text Completion
Security -- Bias -- Safety of LLM

Enrol now to Start the journey