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Program Highlights

Master Artificial Intelligence & Machine Learning

  • Python Programming for Data Science
  • Mathematics for ML (Linear Algebra, Calculus, Statistics)
  • Supervised & Unsupervised Learning Algorithms
  • Deep Learning with TensorFlow & PyTorch
  • Natural Language Processing (NLP)
  • Computer Vision & Image Processing
  • 6+ real-time projects + portfolio
20
Weeks
550+
Hours of content
93%
Placement rate
4.8
⭐ Student rating
Curriculum

What You'll Learn

A structured journey from Python basics to building advanced AI and deep learning models.

Detailed Syllabus

Module Breakdown

Every module is hands-on, with real-world datasets and industry-standard AI/ML tools.

Module 1: Python for Data Science

NumPy, Pandas, Matplotlib, Seaborn, and data manipulation techniques.

Module 2: Mathematics for ML

Linear algebra, calculus, probability, and statistical concepts for ML.

Module 3: Supervised Learning

Linear regression, logistic regression, SVM, decision trees, and ensemble methods.

Module 4: Unsupervised Learning

K-means, hierarchical clustering, PCA, and dimensionality reduction.

Module 5: Deep Learning Fundamentals

Neural networks, backpropagation, activation functions, and optimizers.

Module 6: TensorFlow & PyTorch

Building and training deep learning models with TensorFlow and PyTorch.

Module 7: Natural Language Processing

Text preprocessing, embeddings, RNNs, LSTMs, and transformers (BERT, GPT).

Module 8: Computer Vision

CNN architectures, image classification, object detection, and GANs.

Module 9: Model Deployment & MLOps

Model deployment with Flask, FastAPI, Docker, and cloud platforms.

Module 10: Capstone Project

End-to-end AI/ML project from data collection to production deployment.

Outcomes

What You'll Achieve

You'll emerge as a versatile AI/ML Engineer ready for data science roles, AI research, and product development.

Python Expert

Master Python for data analysis, visualization, and machine learning.

ML Engineer

Build and deploy supervised and unsupervised ML models at scale.

Deep Learning Specialist

Design and train neural networks with TensorFlow and PyTorch.

NLP Practitioner

Build text classification, sentiment analysis, and language models.

Computer Vision Expert

Develop image and video processing solutions with CNNs.

Career Ready

Build a strong portfolio and get hired as an AI/ML Engineer or Data Scientist.