Artificial Intelligence Projects: Project-Based Learning

Name: Artificial Intelligence Projects: Project-Based Learning Course
Rating: 4.4 (312 reviews)
Author: Learnkart Technology Pvt Ltd

Pack of 7 Courses which is 100% hands-on. Contains 50+ Demos, 14 Projects.

updated on icon Updated on Sep, 2024

language icon Language - English

person icon Learnkart Technology Pvt Ltd

English [CC]

category icon Development ,Data Science,Python

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 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.

What you 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

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

Basic knowledge of programming is recommended but not required.

Artificial Intelligence Projects: Project-Based Learning

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

About me

Tech enthousiast currently employed as a Data Engineer. My main focus is Scala + Spark on Kubernetes.

To prepare for Databricks certifications I highly recommend the books "Spark: The Definitive Guide" and "Learning Spark". Prof. Mark C. Lewis also has an excellent playlist about Spark on YouTube.

I'm happy to help in case you have any questions, just send me a message. You can also message me if you want to share feedback, see typos, or have ideas on how to improve my courses.