4.54 out of 5
4.54
263 reviews on Udemy

Modern Artificial Intelligence with Zero Coding

Build 5 Practical Projects & Harness the Power of AI to solve practical, real-world business problems with Zero Coding!
Instructor:
Dr. Ryan Ahmed, Ph.D., MBA
2,701 students enrolled
English [Auto]
Build, train and deploy AI models to detect people emotions using Google Teachable Machine
Explain the difference between learning rate, epochs, batch size, accuracy and loss.
Predict Insurance Premium using Customer Features such as age, smoking habit and geo-location using AWS AI AutoPilot
Build, train and deploy advanced AI to detect cardiovascular disease using DataRobot AI
Leverage the power of AI to recognize food types using DataRobot AI
Develop an AI model to detect and classify chest disease using X-Ray chest data using Google Teachable Machines
Evaluate trained AI models using various KPIs such as confusion matrix, classification accuracy, and error rate
List the various advantages of transfer learning and know when to properly apply the technique to speed up training process
Understand the theory and intuition behind residual networks, a state-of-the-art deep neural networks that are widely adopted in business, and healthcare
Learn how to train multiple AI models based on XG-Boost, Artificial Neural Networks, Random Forest Classifiers and compare their performance in DataRobot
Understand the impact of classifier threshold on False Positive Rate (Fallout) and True Positive Rate (Sensitivity)
Learn how to use SageMaker Studio AutoML tool to build, train and deploy AI/Ml models which requires almost zero coding experience
Differentiate between various regression models KPIs such as R2 or coefficient of determination, Mean absolute error, Mean Squared error, and Root Mean Squared Error
Build, train and deploy XGBoost-based algorithm to perform regression tasks using AWS SageMaker Autopilot

Do you want to build super powerful applications in Artificial intelligence (AI) but you don’t know how to code?

Are you intimidated by AI and don’t know where to start?

Or maybe you don’t have a computer science degree and want to break into AI?

Are you an aspiring entrepreneur who wants to maximize business revenue and reduce costs with AI but don’t know how to get there quickly and efficiently?

If the answer is yes to any of these questions, then this course is for you!

Artificial intelligence is one of the top tech fields to be in right now!

AI will change our lives in the same way electricity did 100 years ago.

AI is widely adopted in Finance, banking, healthcare, transportation, and technology. The field is exploding with opportunities and career prospects.

This course solves a key problem which is making AI available to anyone with no coding background or computer science degree.

The purpose of this course is to provide you with knowledge of key aspects of modern AI without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.

In this course, we will assume that you have been recently hired as a consultant at a start-up in San Francisco. The CEO has tasked you to apply cutting edge AI techniques to 5 projects. There is only one caveat, your key data scientist quit on you and do not know how to code, and you need to generate results fast. In fact, you only have one week to solve these key company problems. Your will be provided with datasets from all these departments and you will be asked to achieve the following tasks:

  • Project #1: Develop an AI model to detect people emotions using Google Teachable Machines (Technology).

  • Project #2: Develop an AI model to detect and classify chest disease using X-Ray chest data using Google Teachable Machines (HealthCare).

  • Project #3: Predict Insurance Premium using Customer Features such as age, smoking habit and geo-location using AWS AI AutoPilot (Business).

  • Project #4: Detect Cardiovascular Disease using DataRobot AI (HealthCare).

  • Project #5: Recognize food types and explore AI explainability using DataRobot AI (Technology).

Course Introduction, Key Learning Outcomes, and Key Tips for Success

1
Course Introduction and Welcome Message
2
Course Introduction Key Tips for Success, Best Practices and Getting Certified
3
What is Artificial Intelligence (AI)?
4
AI Recipe and Key Ingredients!
5
Supervised vs. Unsupervised AI Training
6
Course Outline and Key Learning Outcomes

AI In Healthcare: Disease Detection With AI-Powered Google Teachable Machine

1
Case Study 1. Chest Disease Detection Using Google Teachable Machine
2
The Rise of AI in HealthCare
3
Reading Material: The Rise of AI in Healthcare Applications
4
Quiz: The Rise of AI in Healthcare Applications

Please read the article entitled: "The Rise of Artificial Intelligence in Healthcare Applications" and answer the following questions.

Link to article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325854/

5
Project Overview
6
AI Model Training & Testing in Google Teachable Machines
7
Under the Hood - Artificial Neural Networks Simplified
8
Under the Hood - Artificial Neural Networks Training & Testing Processes
9
Under the Hood - AI Lingo Demystified
10
Under the Hood - Confusion Matrix
11
ANN Demo in Tensorflow Playground
12
Export, Save and Deploy the AI Model
13
Convolutional Neural Networks (CNNs) Deep Dive
14
Covid-Net Overview
15
COVID-NET
16
Final Project Overview
17
Final Project Solution

Emotion AI with AI-powered Google Teachable Machines

1
Case Study 2. Emotion AI with Google Teachable Machine
2
Introduction to Emotion AI and Project Overview
3
Reading Material: Emotion AI For Ad Testing and Media Analytics
4
Quiz: Emotion AI For Ad Testing and Media Analytics
5
Teachable Machine Demo #1 - Data Collection
6
Teachable Machine Demo #2 - Model Training
7
Teachable Machine Demo #3 - Model Deployment and Testing
8
Classification Models KPIs - Part #1
9
Classification Models KPIs - Part #2
10
Transfer Learning
11
Off the shelf Networks, ResNets, and ImageNet
12
Final Project Overview
13
Final Project Solution

AI for Cardiovascular Disease Detection with DataRobot

1
Case Study 3. Cardiovascular Disease Detection with DataRobot
2
Project Overview: Cardiovascular Disease Detection with DataRobot AI
3
Reading Materials: AI for Cardiovascular Disease Detection
4
Quiz: AI for Cardiovascular Disease Detection
5
DataRobot Demo #1: Signup and data upload
6
DataRobot Demo #2: Target Selection & Exploratory Data Analysis
7
DataRobot Demo #3: Model Training and Feature Importance
8
Precision, Recall, ROC and AUC
9
DataRobot Demo #4: Model Evaluation and Assessment
10
DataRobot Demo #5: Model Deployment and Inference
11
Introduction to XG-Boost [Optional Lecture/Additional Material]
12
What is Boosting? [Optional Lecture/Additional Material]
13
Decision Trees and Ensemble Learning [Optional Lecture/Additional Material]
14
Gradient Boosting Deep Dive #1 [Optional Lecture/Additional Material]
15
Gradient Boosting Deep Dive #2 [Optional Lecture/Additional Material]

AI in Business With AWS Autopilot

1
Case Study 4. AI in Business
2
Introduction to AI in business with AWS
3
Reading Material: AI Applications in Business
4
Quiz: AI Applications in Business
5
Project Overview: Insurance Premium Prediction
6
Simple and Multiple Linear Regression
7
Amazon Web Services (AWS) 101
8
Amazon S3 and EC2
9
Introduction to AWS SageMaker
10
Regression Metrics
11
AWS SageMaker AutoPilot Demo #1
12
AWS SageMaker AutoPilot Demo #2
13
AWS SageMaker AutoPilot Demo #3

AI for Food Recognition & Explainable AI with DataRobot

1
Case Study 5. Food Recognition with AI & Explainable AI
2
Project Introduction: Food Recognition with AI
3
Reading Material: Machine Learning and AI in the Food Industry
4
Quiz: Machine Learning and AI in the Food Industry
5
DataRobot Demo #1 - Upload & Explore Dataset
6
DataRobot Demo #2 - Train AI Model
7
DataRobot Demo #3 - Explainable AI
8
Logistic Regression Theory [Optional Lecture/Additional Material]
9
Bias Variance Tradeoff [Optional Lecture/Additional Material]
10
L1 & L2 Regularization Part #1 [Optional Lecture/Additional Material]
11
L1 & L2 Regularization Part #2 [Optional Lecture/Additional Material]
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
4.5
4.5 out of 5
263 Ratings

Detailed Rating

Stars 5
142
Stars 4
89
Stars 3
23
Stars 2
4
Stars 1
1
30-Day Money-Back Guarantee

Includes

10 hours on-demand video
5 articles
Full lifetime access
Access on mobile and TV
Certificate of Completion
Modern Artificial Intelligence with Zero Coding
Price:
$218.98 $169

Community

For Professionals

For Businesses

We support Sales, Marketing, Account Management and CX professionals. Learn new skills. Share your expertise. Connect with experts. Get inspired.

Community

Partnership Opportunities

Layer 1
samcx.com
Logo
Register New Account
Compare items
  • Total (0)
Compare
0