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Flagship AI TrackAdvanced⏱ 4 Months • 150 Hours

AI & Machine Learning

Master Deep Learning, Computer Vision, Natural Language Processing (NLP), and Generative AI. Build custom LLM applications, RAG pipelines, vector search databases, and deploy MLOps inference endpoints.

★★★★★
4.9(1,920 ratings)
11,800 Students Enrolled
Updated Jan 2026
Enroll Now — ₹19,999Request Program Syllabus 📄
AI & Machine Learning
LIVE ONLINE PROGRAM

AI & Machine Learning

Program Duration4 Months • 150 Hours
Placement Track100% Assisted Referral
Session Format1-on-1 Interactive

What you'll learn

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Master Python for Data Science (NumPy, Pandas, Matplotlib, Scikit-Learn)
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Build Deep Learning models with PyTorch and TensorFlow / Keras
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Train Transformers, Convolutional Networks (CNNs), and Recurrent Neural Nets (RNNs)
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Develop Generative AI apps with LangChain, LlamaIndex, and OpenAI / Gemini APIs
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Implement RAG (Retrieval-Augmented Generation) with Pinecone & Qdrant vector databases
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Fine-tune Open-Source Large Language Models (LLaMA 3, Mistral, Gemma)
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Deploy model inference endpoints using FastAPI, TorchServe, and Triton Server
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Establish MLOps pipelines with MLflow, DVC, and automated model tracking
YOUR INSTRUCTOR
DSJ

Dr. Sarah Jenkins

AI Research Lead & Ex-Google AI Scientist

Experienced industry practitioner dedicated to mentorship, enterprise architecture, and student placement success.

Have Questions?

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PROGRAM SYLLABUS OVERVIEW

Course Content & Syllabus

Structured step-by-step curriculum & core learning topics taught by industry architects.

1

Module 1: Mathematical Foundations & Scikit-Learn ML Models

KEY CONCEPTS & SYLLABUS TOPICS COVERED:

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Linear Algebra, Calculus & Probability for Machine Learning
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Data Preprocessing, Feature Engineering & Scaling
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Supervised Learning: Regression & Classification
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Unsupervised Learning: Clustering & Dimensionality Reduction
2

Module 2: PyTorch Deep Learning & Computer Vision

3

Module 3: Natural Language Processing & Transformers

4

Module 4: Generative AI, RAG Systems & MLOps