Professional / Advanced
Certified Industry Program
Machine Learning + Deep Learning + LLMs
A combined technical AI program covering machine learning, neural networks and modern large language model application development.
Duration
4 Months
Regular Batch
1 hour/day (Monday–Saturday)
Weekend Batch
3 hours/class (Saturday–Sunday)
Course Fee
INR 40,000.00
Course Overview
Machine Learning + Deep Learning + LLMs is a 4-month technical AI program designed for software engineers, developers, data practitioners, and tech enthusiasts. The program covers end-to-end ML algorithms, neural architectures, CNNs, Transformers, modern LLM application development, vector stores, RAG pipelines, model evaluation, and deployment.
What You Will Learn (Learning Outcomes)
Understand and build core ML workflows.
Develop a practical foundation in deep learning and neural networks.
Understand LLMs, embeddings, RAG and API-based AI apps.
Complete portfolio-ready technical AI projects.
Course Modules & Detailed Syllabus
5 Modules • 36 Classes / Topics
01
Module 1 – Python & Data Foundation
5 Topics / Classes-
Python essentials for AI/ML
-
NumPy and Pandas basics
-
Data preprocessing and feature preparation
-
Exploratory data analysis basics
-
Train-test split and evaluation mindset
02
Module 2 – Machine Learning
9 Topics / Classes-
Machine learning fundamentals and workflow
-
Supervised vs unsupervised learning
-
Regression algorithms
-
Classification algorithms
-
Clustering basics
-
Feature engineering and preprocessing
-
Model evaluation metrics
-
Overfitting, underfitting and cross-validation basics
-
Practical ML projects
03
Module 3 – Deep Learning
8 Topics / Classes-
Neural network fundamentals
-
Perceptron, layers, weights and activation functions
-
Forward and backward propagation concepts
-
Loss functions and optimizers
-
CNN basics for image tasks
-
RNN/LSTM overview for sequence data
-
Introduction to transformers
-
Deep learning project workflow
04
Module 4 – Large Language Models
9 Topics / Classes-
LLM fundamentals and transformer architecture overview
-
Tokens, embeddings and vector representations
-
Prompting for LLM applications
-
Using LLM APIs
-
Embeddings and vector database concepts
-
RAG architecture and document-based Q&A
-
Fine-tuning concepts and when to use them
-
Evaluation, hallucination, safety and guardrails
-
Building practical LLM-powered applications
05
Module 5 – Integrated Projects
5 Topics / Classes-
Machine learning prediction project
-
Deep learning application project
-
RAG/LLM application project
-
Project documentation and presentation
-
Portfolio and deployment overview
Batch Timings & Fee Structure
| Batch Type | Schedule & Timing | Program Fee | Action |
|---|---|---|---|
| Regular Batch | 1 hour/day (Monday–Saturday) | INR 40,000.00 | Enroll Now |
| Weekend Batch | 3 hours/class (Saturday–Sunday) | INR 40,000.00 | Enroll Now |
Flexible installment and EMI options available upon academic counselling request.