Updated on May, 2024
Language - English
delivery needs improvement
Artificial Intelligence Projects: Project-Based Learning
Pack of 7 Courses which is 100% hands-on. Contains 50+ Demos, 14 Projects.
Development,Artificial Intelligence,Data Science
Lectures -139
Resources -7
Duration -18.5 hours
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Course Description
Artificial intelligence (AI) is one of the most rapidly growing fields in technology. AI is being used to develop new and innovative products and services in a wide range of industries, from healthcare to finance to transportation.
This online video course will teach you how to build AI projects using a variety of programming languages and tools. You will learn how to collect and prepare data, train and evaluate machine learning models, and deploy AI models to production.
Artificial Intelligence Projects: Project-Based Learning Course Overview
This course Pack of 7 Courses which is 100% hands-on. Contains 50+ Demos, 14 Projects. You also get the Dataset and Code files required along with Video explanations/steps of the projects and demos. Also, you will get highly structured video resources for the theory.
We will Learn :
Computer Vision
Data Science with Python
Machine Learning
Deep Learning Fundamentals
Deep Learning with TensorFlow and Keras
Data Visualization and Tools
Natural Language Processing (NLP)
Goals
What will you learn in this course:
Understand the concept of Explainable AI
Uncover the blackbox nature of Artificial Neural Networks and visualize their hidden layers using the GradCam technique.
Develop a Deep Learning model to automate and optimize the brain tumor detection processes at a hospital.
Build and train AI model to detect and localize brain tumors using ResNets and ResUnet networks (Healthcare applications).
Understand the theory and intuition behind Segmentation models and state-of-the-art ResUnet networks.
Build, train, and deploy AI models in business to predict customer default on credit cards using the AWS SageMaker XGBoost algorithm.
Optimize XGBoost model parameters using hyperparameters optimization search.
Apply AI in business applications by performing customer market segmentation to optimize marketing strategy.
Prerequisites
What are the prerequisites for this course?
Basic knowledge of programming is recommended but not required.
Curriculum
Check out the detailed breakdown of what’s inside the course
Computer Vision
17 Lectures
-
Section 1 - Resource Files
-
Computer Vision Projectivity
01:47
01:47
-
Convolutional Neural Network (CNN)
01:13
01:13
-
Demo-1 - Neural Network
09:33
09:33
-
Demo-2 - Neural Network with Keras
10:44
10:44
-
Demo-3 - Data Cleaning Neural Network
08:03
08:03
-
CNN Architecture
01:18
01:18
-
Demo-4 - Digit Classification with CNN
18:29
18:29
-
Demo-5 - Object Detection with CNN
14:01
14:01
-
OpenCV
00:51
00:51
-
Demo-6 - Image Processing with OpenCV
06:23
06:23
-
Demo-7 - OpenCV Examples
08:51
08:51
-
Demo-8 - YOLO with OpenCV
09:24
09:24
-
Object Detection & Classification using CNN
01:17
01:17
-
Project-1 - Object Detection & Classification using CNN
01:05
01:05
-
Project-1 - Solution
23:27
23:27
-
Project-2 - Face Detection using OpenCV
01:12
01:12
Data Science with Python
23 Lectures
Machine Learning
17 Lectures
Deep Learning Fundamentals
19 Lectures
Deep Learning with Tensorflow and Keras
26 Lectures
Data Visualization and Tools
20 Lectures
Natural Language Processing (NLP)
17 Lectures
Instructor Details
Learnkart Technology Pvt Ltd
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