Aritificial Intelligence

From Theory to Reality

Smart Bridge

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What you will learn

  • Introduction to AI

  • ANN

  • RNN

  • Transfer Learning

  • Flask

  • Python

  • CNN

  • LSTM (Long Short Term Memory)

  • Time Series

This course provides a comprehensive introduction to Artificial Intelligence, covering key concepts, tools, and applications. Students will gain hands-on experience with Python programming and essential AI libraries. The course delves into Deep Learning, Transfer Learning, and Time Series Modeling, equipping learners with the skills to build and optimize AI models. Additionally, students will develop practical AI solutions by integrating models into web applications using the Flask framework. The curriculum follows a project-based learning approach, ensuring real-world exposure and application-driven understanding.

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Python Basics
Preview 18:31
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Numpy Library
Preview 44:58
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Pandas Library
Preview 40:35

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Introduction to ANN
Preview 39:48
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Steps to ANN
Preview 11:16
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Regression Problem
Preview 30:48
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Binary Problem
Preview 37:17
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Multiclass Problem
Preview 35:05

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Introduction to CNN
Preview 06:08
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Types of Images
Preview 06:34
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CNN Architecture Overview
Preview 04:03
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Convolution layer
Preview 09:29
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Pooling layer
Preview 03:06
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Flattening Layer
Preview 02:01
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Fully Connected layer
Preview 03:06
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CNN Practical
Preview 50:54

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Introduction to RNN
Preview 03:09
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Deep Dive into RNN
Preview 04:36
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Key Components
Preview 07:31
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Types of RNN
Preview 03:27
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RNN 3 Types
Preview 23:18
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Many to Many
Preview 08:43
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Architecture Explanation
Preview 18:07
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RNN Model Building (Google Stock price Prediction)
Preview 25:50
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RNN Model prediction (Google Stock price Prediction)
Preview 07:02
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Vanishing Gradient
Preview 06:01
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RNN Key Takeaways
Preview 02:11

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LSTM Introduction
Preview 05:47
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LSTM Deep Dive
Preview 04:16
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Key Components
Preview 09:53
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Architecture Explanation
Preview 12:16
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LSTM Airline Passengers Prediction(reshaping, scaling)
Preview 08:28
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LSTM Airline Passengers Prediction(Model Building)
Preview 24:26
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LSTM Airline Passengers Prediction (plot)
Preview 11:11
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LSTM Take Aways
Preview 09:21

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Introduction to Transfer Learning
Preview 04:53
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Workflow and Applications
Preview 04:06
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Inception V1 theory
Preview 04:44
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Inception V2 and V3 Theory
Preview 13:36
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Inception V3 Coding
Preview 19:34
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VGG-16 and VGG-19 Theory
Preview 18:48
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VGG-16 and VGG-19 Model Exploring Coding
Preview 17:44
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VGG-16 and VGG-19 Coding on customised dataset
Preview 22:52
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Resenet-50
Preview 23:50
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Resenet-50 Model Exploration Coding
Preview 07:04
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ResNet-50 Coding on Customised dataset
Preview 08:24

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Introduction to Timeseries
Preview 08:14
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Components of Time Series
Preview 12:57
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Key Models
Preview 11:27
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Auto Regression Coding
Preview 25:46
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ARIMA and SARIMA Coding
Preview 19:06

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Introduction to Flask
Preview 06:23
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Other Frameworks
Preview 02:10
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Flask Framework
Preview 07:14
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Why Flask
Preview 03:05
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Steps in Building Webapp using Flask
Preview 09:16
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Flask Practical
Preview 32:38
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Flask Deployment
Preview 18:46
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Smart Bridge

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₹ 5999.00

  • Course Duration
    17 h 14 m 2 s
  • Course Level
    Advanced
  • Student Enrolled
    0
  • Language
    English
This Course Includes
  • 17 h 14 m 2 s Video Lectures
  • 0 Quizzes
  • 1 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion