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IIT Mumbai

Generative AI

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  • Industry-Relevant Curriculum
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Generative AI
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About this course

Generative AI enables the creation of intelligent content such as text, images, code, and media using advanced AI models. It is widely used to build innovative applications, automate workflows, and enhance digital experiences.

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Generative AI Career Transitions

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What role does a Data Scientist play?

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25 Dec 2025
10:30:00 - 11:30:00
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200+ Hours of Content
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Weekday (Morning)
25 Dec 2025
10:30:00 - 11:30:00
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Artificial Intelligence Course Syllabus

Live Course Self-Paced Industry Expert Academic Faculty

Python for Data Science - Fundamentals

Preview
  • Introduction to Python
    00:00:00

    Introduction to Python

  • Object Oriented Programming
    00:00:00
  • Python Basics
    00:00:00
  • Data Preprocessing
    00:00:00
  • Difference between Data Science, Machine Learning, Deep Learning, AI & Data Science
    00:00:00
  • Data Handling with NumPy
    00:00:00

    Data Handling with NumPy

  • Data Manipulation Using Pandas
    00:00:00
  • SQL Basics
    00:00:00

    SQL Basics

  • Advanced SQL
    00:00:00
  • Regression Model
    00:00:00

    Regression Model

  • Clustering Algorithms
    00:00:00
  • Performance Metrics
    00:00:00
  • Dimensionality Reduction
    00:00:00
  • Time Series Models
    00:00:00
  • American Sign Language Recognition
    00:00:00

    American Sign Language Recognition

  • Gesture Recognition
    00:00:00
  • Shark Species Classification
    00:00:00
  • Stock Market Forecasting
    00:00:00
  • Cyber Threat Detection Using NLP
    00:00:00
  • Introduction to AI & Data Science, CNN & RNN
    00:00:00

    Introduction to AI & Data Science, CNN & RNN

  • Introduction to AI & Data Science, CNN & RNN
    00:00:00
  • Introduction to Keras API, Tensorflow and Neural Networks
    00:00:00
  • Single Cell (perceptron)
    00:00:00
  • Multi cell perceptron Topology, gradient-descent, Back-propagation
    00:00:00
  • Weights & Biases
    00:00:00
  • Build a Neural Network from scratch
    00:00:00
  • Use cases of Deep Learning in the industry
    00:00:00
  • Lifecycle of Deep Learning Project
    00:00:00
  • NLP
    00:00:00

    NLP

  • Text Pre-processing
    00:00:00
  • Text Classification
    00:00:00
  • Language Modeling
    00:00:00
  • AI & Data Science Applications
    00:00:00
  • Computer Vision
    00:00:00
  • Deep Learning
    00:00:00
  • Transformers
    00:00:00

    Transformers

  • LSTM
    00:00:00
  • BERT
    00:00:00
  • GPT
    00:00:00
  • LLM
    00:00:00
  • VAEs
    00:00:00
  • LangChain
    00:00:00
  • Prompt Engineering
    00:00:00

    Prompt Engineering

  • Image-Based Applications of Generative AI
    00:00:00
  • Text-Based Applications of Generative AI
    00:00:00
  • Audio-Based Applications of Generative AI
    00:00:00

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Artificial IntelligenceProjects

Image Recognition System

Image Recognition System is a computer vision project that enables machines to identify and classify objects, people, or patterns within images. Using deep learning algorithms and neural networks, this project helps learners understand how AI analyzes visual data, detects features, and makes accurate predictions, with applications in healthcare, security, autonomous vehicles, and more.

Self-Driving Car Simulation

Image Recognition System helps learners build AI models that can detect, classify, and analyze objects or patterns in images. This project teaches computer vision techniques and deep learning concepts for real-world applications like facial recognition, autonomous vehicles, and security systems.

Predictive Analytics Project

Predictive Analytics Project enables learners to analyze historical data and build machine learning models that forecast future trends and outcomes. This project teaches techniques for data preprocessing, model selection, and prediction, with applications in sales forecasting, stock market analysis, and business decision-making.

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Generative AI Training FAQs

What is Artificial Intelligence?

Artificial Intelligence (AI) is a technology that enables machines to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.

This course primarily uses Python due to its simplicity and extensive libraries for AI and machine learning.

The course covers Python programming, machine learning, deep learning, NLP, computer vision, and hands-on AI projects.

Learners will work with Python, TensorFlow, PyTorch, Keras, Scikit-learn, OpenCV, and NLP libraries.

Students can pursue roles like AI Engineer, ML Engineer, Data Scientist, NLP Engineer, and Computer Vision Engineer.

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