Is prior experience required?

Recommended. This is an advanced program designed for learners with prior programming and basic ML knowledge. If you’re new, we provide a short prep kit to get you comfortable with Python, NumPy and basic model concepts.

What is the duration of the program?

The program includes ~55 guided hours delivered via live sessions, hands-on labs, code reviews, and a capstone aligned to Deep Learning, NLP and Generative AI.

Will I get job assistance?

Yes. You’ll receive resume & LinkedIn optimization, portfolio review, mock interviews, and curated referrals for relevant AI/ML roles.

Which tools and frameworks are covered?

PyTorch, Hugging Face Transformers, tokenizers, vector databases, experiment tracking basics, and lightweight MLOps for safe deployments.

Do I get a certificate?

Yes. You’ll receive a QR-verified certificate from Cinute Digital Pvt. Ltd. after completing assessments and the capstone project.

Live Online + Classroom55 HoursProject-basedPlacement Support

Master Program in Deep Learning, NLP & Generative AI

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Become industry-ready with Neural Networks, CNNs, RNNs/LSTMs, Transformers, Prompt Engineering, fine-tuning LLMs, embeddings and vector databases. Build portfolio projects and earn a QR-verified certificate.

Curriculum includes data pipelines, tokenization, evaluation (BLEU, ROUGE, accuracy, F1), guardrails, lightweight MLOps, and deployment.

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Hands-on labs with PyTorch & Hugging Face
Transformers, BERT/GPT-style models, LoRA fine-tuning
Prompt engineering & retrieval-augmented generation (RAG)
Deploy to cloud • basic MLOps & monitoring

★★★★★#1 Mumbai’s Premium Training Institute

Request a Callback

Want to know exactly how much it costs & when the next batch starts? Tell us where to call you!

Full Name *

Email Address *

Mobile Number *

By submitting, you agree to our Privacy Policy.

Why Advanced Data Analytics?

Data analytics drives profitability, forecasting, and decisions in 2025. Join our mentor-led Advanced Data Analytics program to build Python, SQL, BI, and ML skills with real projects and placement support.

0 Hours

Program Duration

4 Months • Hybrid

0:0

Practical : Theory

Industry-Rich Experience

0 + Years

Team Expertise

Mentor-led • Industry Aligned

Job Assistance

Resume • Mock Interviews • Referrals

0++

Data Analyst Jobs (India)

Open Roles Across Sectors

0 % CAGR

Market Growth (2020–2030)

Data/Analytics Industry

Master dashboards & reporting (Power BI/Tableau), SQL for analytics, feature engineering, and ML for business with career support.

*Outcomes vary by prior experience, pace, and project depth.

Deep Learning, NLP & Generative AI with Python

An advanced, practical program to design, train, fine-tune, and deploy modern AI models- including Transformers, LLMs, and generative pipelines. Get industry-ready with hands-on projects, portfolio artifacts, and real deployment workflows.

55 Hours

Hands-On Projects

Expert Faculty

Prior ML Experience Needed

100% Job-Ready

Master Neural Networks

Build CNNs, RNNs, and Transformers from scratch and with modern libraries. Understand optimization, regularization, and inference.

Work with LLMs & Prompting

Apply prompt engineering, adapters (LoRA/QLoRA), and RAG to production use cases without overspending on compute.

Production-Ready NLP

Tokenization, embeddings, vector search, evaluation, and monitoring that stands up in real apps and APIs.

Deploy & Scale

Package models with FastAPI, containerize with Docker, and ship to cloud with CI/CD and observability best practices.

Safety & Ethics

Mitigate bias, implement guardrails, and comply with responsible AI guidelines for enterprise use.

MLOps Essentials

Version datasets & models, track experiments, and automate training pipelines for repeatable results.

What you’ll learn (and build)

From neural network fundamentals to state-of-the-art NLP and generative AI, this course ensures you can ship working AI systems. You will implement tokenization & embeddings, construct and fine-tune Transformer/LLM architectures, and wire up RAG pipelines with vector databases. You’ll package models with FastAPI, containerize with Docker, and deploy to cloud with CI/CD while tracking experiments and monitoring performance.

Curriculum aligned to high-demand AI roles and interview patterns.
Python-first stack: PyTorch, Transformers, FastAPI, Faiss/PGVector.
Project portfolio with measurable business impact and metrics.

Keywords: Deep Learning course, NLP course, Generative AI with Python, Transformer models, Large Language Models, LLM fine-tuning, RAG, vector databases, MLOps, AI deployment, prompt engineering.

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5-Core Curriculum Modules

A 110+ hour, industry-aligned path across SQL/MySQL, Excel, Power BI, Tableau, and Python libraries—culminating in real projects and job-ready skills.

*Module order may vary slightly based on cohort needs and instructor discretion.

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Tools & Technologies You’ll Master

A job-ready AI/ML stack for real projects: modeling, MLOps, APIs, and visualization. Learn the tools that recruiters recognise and teams use.

Python
TensorFlow
PyTorch
Keras
NLTK
spaCy
Hugging Face
Docker
NumPy
Pandas
scikit-learn
FastAPI

Master the Python data science toolkit end-to-end - from data wrangling and feature engineering to deep learning, LLMs, and deployment.

*Tooling may vary by project and track.

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Your AI Career Roadmap

Follow these 4 proven steps to go from learner to a job-ready Deep Learning / NLP / Generative AI professional with a portfolio recruiters trust.

Program Duration

≈ 55 Hours

Guided, project-based

Portfolio Projects

Deployed & documented

Target CTC

₹10–20 LPA

Role & location vary

1
Job-Ready Foundations
Complete the 55-Hour GenAI Hero Program
Deep Learning fundamentals → NLP pipelines → Transformers & LLMs. Master embeddings, tokenization, and hands-on model training with Python.
2
Portfolio & GitHub
Build 3+ Production-Style AI Projects
Ship an end-to-end RAG app, a fine-tuned LLM (LoRA/QLoRA), and a vision/NLP capstone. Document with READMEs, metrics, and demos.
3
Cloud & MLOps
Deploy, Observe & Secure
Expose FastAPI endpoints, containerize with Docker, and deploy to cloud. Add vector search, logging, evals, and guardrails for safe AI.
4
Offer & Onboarding
Career Prep & Land a GenAI Role
Resume ATS optimization, mock interviews, DS/ML warm-ups, and project storytelling. Target ₹10–20 LPA roles in AI Engineer / NLP / GenAI Dev.

Learn from anywhere. Your journey to a Generative AI career starts here.

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Real-World Projects You’ll Build

Apply Deep Learning, NLP, and Generative AI to solve real problems. Build a job-ready portfolio with clean code, clear storytelling, and measurable impact.

# NLP Sentiment Analysis (Real Reviews)

Classify customer sentiment from real-world reviews; surface topics and pain points for product teams.

Data cleaning & label strategy
Model comparison (LogReg, BiLSTM, Transformers)
Explainability with SHAP

PythonPandasscikit-learnTransformers