100% Placement Advanced Level

Artificial Intelligence

Artificial Intelligence (AI) is used to build smart machines that can think, learn, and make decisions like humans. This course introduces you to AI concepts, machine learning, and deep learning, which are transforming many industries. Build future-ready skills that are in high demand worldwide.Open doors to exciting career opportunities in the tech industry.Explore real-world applications of AI across multiple industries.

Why This Course?

Lead the AI Revolution.

Artificial Intelligence is no longer the future; it is the present. This intensive 6-month program bypasses basic theory to immerse you in real-world corporate data sets, model training, and AI deployment.

Whether you want to build the next ChatGPT or optimize global logistics through predictive analytics, you will graduate with a portfolio that demands attention.

    • AI/ML Engineer
    • Data Scientist
    • NLP Specialist
    • AI Prompt Engineer
Stack Mastered

Python

TensorFlow

PyTorch

Scikit-Learn

OpenAI API

LangChain

AWS SageMaker

The Curriculum

Your Learning Roadmap.

1
Phase 01

Foundations & Data Eng.

Master Python for Data Science. Deep dive into Probability, Statistics, Linear Algebra, and exploratory data analysis using Pandas and NumPy.

2
Phase 02

Machine Learning Algorithms

Build predictive models. Cover Supervised & Unsupervised learning, Regression, Random Forests, SVMs, and hyperparameter tuning.

3
Phase 03

Deep Learning & Vision

Enter the world of Neural Networks. Build CNNs for image recognition and RNNs for sequence data using TensorFlow and Keras.

4
Phase 04

Generative AI & NLP

The cutting edge. Learn Natural Language Processing, Transformers, LLMs, Prompt Engineering, and building apps with LangChain.

Final Phase

MLOps & Capstone Project

Deploy your models to the cloud (AWS/GCP). Build a portfolio-grade, end-to-end AI application for your final corporate presentation.

Detailed Syllabus

  • Advanced Python Programming & OOP concepts
  • Data Structures: Lists, Tuples, Dictionaries, Sets
  • Linear Algebra: Matrices, Vectors, Eigenvalues
  • Probability Theory & Inferential Statistics
  • Data Manipulation with Pandas & NumPy

  • Supervised Learning: Linear & Logistic Regression
  • Decision Trees, Random Forests & XGBoost
  • Unsupervised Learning: K-Means Clustering, PCA
  • Model Evaluation: Cross-validation, ROC/AUC
  • Building pipelines with Scikit-Learn

  • Architecture of Artificial Neural Networks (ANNs)
  • Forward & Backpropagation, Gradient Descent
  • Computer Vision with Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs) & LSTMs
  • Hands-on with PyTorch and TensorFlow/Keras
Admissions Open 2026

Build the Future.

Seats are limited for the upcoming AI cohort. Secure your spot and start your journey toward a high-paying tech career today.

Chat with us