The Complete Healthcare Artificial Intelligence Course 2022

Creating powerful AI model for Real-World Healthcare applications with Data Science, Machine Learning and Deep Learning

4.29 (164 reviews)
Udemy
platform
English
language
Data Science
category
instructor
1,409
students
18.5 hours
content
Nov 2021
last update
$69.99
regular price

What you will learn

Pandas.

Matplotlib.

Sigmoid activation function.

Tanh activation function.

ReLU activation function.

Leaky Relu activation function.

Exponential Linear Unit activation function.

Swish activation function.

Markov models.

Support Vector Machines

Other common classifiers

Import data from the UCI repository.

Convert text input to numerical data.

Build and train classification algorithms.

Compare and contrast classification machine learning.

Building the AI.

Machine learning and deep learning model based on the given data with high accuracy.

RF with Response Coding.

Maximum voting Classifier.

Stacking model.

Random Forest Classifier.

One-hot Encoding.

NLP (Natural Language Processing)

NLTK (Natural Language Toolkit)

Logistic Regression.

Naive Bayes

Response Encoding

Linear Support Vector Machines

Geolocation Features.

Handling Missing Data And Anomalies in Python.

Data standardization.

Temporal Features.

Seaborn

Deep Learning.

Keras.

Google Colab .

Anaconda.

Jupiter Notebook.

Description

Interested in the field of Machine Learning, Deep Learning and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with my experience and knowledge I did gain throughout years, I can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into the Machine Learning, Artificial Intelligence and Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning, Deep Learning and Artificial Intelligence . Throughout the brand new version of the course we cover tons of tools and technologies including:

  • Deep Learning.

  • Google Colab

  • Anaconda

  • Jupiter Notebook

  • Artificial Intelligent In Healthcare.

  • Artificial Neural Network.

  • Neuron.

  • Activation Function.

  • Keras.

  • Pandas.

  • Seaborn.

  • Feature scaling.

  • Matplotlib.

  • Generating a DNA Sequence.

  • Data Pre-processing.

  • Sigmoid Function.

  • Tanh Function.

  • ReLU Function.

  • Leaky Relu Function.

  • Exponential Linear Unit Function.

  • Swish function.

  • Markov Models.

  • K-Nearest Neighbors Algorithms (KNN).

  • Support Vector Machines (SVM).

  • Importing library and data.

  • Deep feedforward networks.

  • Analysing Data.

  • Exploratory Analysis.

  • Handling Missing Data And Anomalies in Python.

  • Data standardization.

  • Temporal Features.

  • Geolocation Features.

  • Data Scaling.

  • Data Visualization.

  • Visualizing Geolocation Data.

  • Understanding Machine Learning Algorithm.

  • Splitting Data into Training Set and Test Set.

  • Training Neural Network.

  • Model building.

  • Analysing Results.

  • Model compilation.

  • A Comparison Of Categorical And Binary Problem.

  • Make a Prediction.

  • Testing Accuracy.

  • Confusion Matrix.

  • ROC Curve.

  • One-hot Encoding.

  • NLP (Natural Language Processing).

  • NLTK (Natural Language Toolkit).

  • Logistic Regression.

  • Naive Bayes.

  • Response Encoding.

  • Linear Support Vector Machines.

  • RF with Response Coding.

  • Random Forest Classifier.

  • Stacking model.

  • Maximum voting Classifier.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are five big projects on healthcare problems and one small project to practice. These projects are listed below:

  • Predicting Taxi Fares in New York City

  • DNA Classification Project.

  • Heart Disease Classification Project.

  • Diagnosing Coronary Artery Disease Project.

  • Breast Cancer Detection Project.

  • Predicting Diabetes with Multilayer Perceptrons Project.

  • Iris Flower.

  • Medical Treatment Project.


Content

Introduction

Course Structure
How To Make The Most Out Of This Course
AI in Healthcare
What is Neuron
What is deep Learning
What is ANN
What is keras
Introduction to Pandas and visualization
Data Preprocessing by Pandas
How to install Anaconda
Important terms in Neural Network

Activation function

What is activation function
What is sigmoid function
What is tanh function
What is Rectified Linear Unit function
What is Leaky ReLU function
What is The Exponential Linear Unit Function
What is The Swish function
What is The softmax function
Time to code all the activation functions

DNA Classification Project

Introduction to DNA Classifier
Importing library and data
Showing data
Generating a DNA sequence
Splitting the dataset into training test and test set
Scoring method and results
Summary of the project

Heart Disease Classification Project

Introduction to the project
Important Parameters
Objective of this project
Importing library and data
Exploratory analysis
Handling missing data in Python
Data scaling
Data visualization
Splitting training set into test set and Evaluating the model
Summary of the project

Diagnosing Coronary Artery Disease Project

Introduction
Importing data and Analysing data
Fixing missing data
Splitting the dataset into training test and test set
Training Neural Network
A comparison of categorical and binary problem
Summary of the project

Breast Cancer Detection Project

Introduction to the project
Importing library and data and Preprocessing data
Data visualization
Understanding Machine Learning Algorithm
Training model
Make a Prediction
Summary of the project

Predicting Diabetes with Multilayer Perceptrons Project

Introduction
Importing datas and libraries
Visualizing data
Handling missing values
Data standardization
Splitting the data into training, testing, and validation sets
Model building
Model compilation
Model training
Testing accuracy
Confusion matrix
ROC curve
Further improvement
Summary of the project

Thank you

Extra Link
Thank you

Bonus- Extra projects outside the healthcare scope

Bonus project

Bonus- Extra projects outside the healthcare scope

Bonus project

Screenshots

The Complete Healthcare Artificial Intelligence Course 2022 - Screenshot_01The Complete Healthcare Artificial Intelligence Course 2022 - Screenshot_02The Complete Healthcare Artificial Intelligence Course 2022 - Screenshot_03The Complete Healthcare Artificial Intelligence Course 2022 - Screenshot_04

Reviews

Tuanne
September 30, 2023
The topic is very interesting and worth taking the time to listen to. I have learned a lot. Now I'm learning more about the course. This course is very comprehensive in discussing healthcare artificial intelligence courses. Very informative and insightful.
JonnyHoang
September 9, 2023
Great course!!! Every theoretical concept is explained very clearly and then demonstrated with practical examples, followed by exercises to gain experience. A great balance between theory and coding. After this course, you will have the tools to power yourself when working on data-related projects. It will provide some exercises and projects to practice what you have learned and that is when you will learn the most. As with everything, you will only become an expert with time and experience.
Tuấn
September 3, 2023
I love this course so I'm taking the third one because it's very informative, more practical, and has follow-up without any test. Hoang Quy La does a great job. Please continue to uphold
Pth123
September 2, 2023
At first, I started with the intention to go quickly through some video scripts. but I changed then. There is so much to learn here. Thank you teacher!
Starlight06
September 2, 2023
A detailed course, covering the topic in-depth. I learned here and think that it is necessary to share them with other.
Duvvuri
August 31, 2023
No required data files were shared and no proper instructions on how to work with the data like using Google Drive to uoload the files or shared Google Drive for the data files to run Python.
Goh
August 23, 2023
Is a good course, if have some example in image prediction or classification will be more interesting.
Jesse
June 26, 2023
Well... the instructor is difficult to understand no matter what language you speak. It is better to just mute him and read the slides.
Ziyou
August 31, 2022
The class content is very great, but I suggest read the code first and then listen the course will be easier to understand why step by step should look like this!! Hope it helps!
Jad
November 7, 2021
first he provides false information , he is not knowledgeable about the topic at all , he cannot even pronounce basic key words properly which shows that he knows nothing . also his accent is so poor so without the text the he is "reading" I would not be able to know a single word he's saying
Stephen
April 10, 2021
I love the course so much. The course with a very useful projects, well-explained. I can't wait to see the upcoming projects.
Alicia
March 15, 2021
After completing this course, I got a job at Toshiba. Thank you Hoang so much. You create an amazing course for everyone to learn.
Pablo
March 13, 2021
After completing the course, I am really satisfied it. I got promoted as a senior data analyst. I really appreciate all the hard-work Hoang puts into the course. Thank you so much
Aman
March 13, 2021
After completing this course, I did apply job in the ECO DISTRIBUTION PTY. LTD and It is successfully. I cant describe any words right now. This is a great course. Thank you so much for the course.
Robert
March 13, 2021
I got a job in a hospital as a data analyst. Thank you a lot for your course. It is just amazing. I am really appreciate for your hard work.

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3811732
udemy ID
1/29/2021
course created date
2/10/2021
course indexed date
AhmedELKING
course submited by