10 Days of No Code Artificial Intelligence Bootcamp
10 Days of No Code Artificial Intelligence Bootcamp, available at $89.99, has an average rating of 4.43, with 115 lectures, 11 quizzes, based on 1143 reviews, and has 8156 subscribers.
You will learn about Build, train, test and deploy 10 AI/ML models in 10 days without writing any code. Build, train, test and deploy AI models to classify fashion items using Google Teachable Machine. Visualize State-of-the-Art Artificial Intelligence Models Using Tensorspace JS, Google Tensorflow Playground and Ryerson 3D CNN Visualizations. Explain the difference between learning rate, epochs, batch size, accuracy, and loss. Build, train and deploy advanced AI to detect Diabetic Retinopathy disease using DataRobot AI. Leverage the power of AI to solve regression tasks and predict used car prices using DataRobot AI. Evaluate trained AI models using various KPIs such as confusion matrix, classification accuracy, and error rate. Understand the theory and intuition behind Residual Neural Networks (ResNets), a state-of-the-art deep NNs that are widely adopted in several industries. Understand the impact of classifier threshold on False Positive Rate (Fallout) and True Positive Rate (Sensitivity). Predict employee attrition based on their features such as employee engagement, distance from home, job satisfaction using DataRobot AI. Develop an AI model to detect face masks using Google Teachable Machines. Build, train and deploy XGBoost-based algorithm to perform regression tasks using AWS SageMaker Autopilot. Learn how to transfer knowledge from a pre-trained Artificial Neural Network to a new network using transfer learning strategy. Learn how to train multiple AI models based on XG-Boost, Artificial Neural Networks, Random Forest Classifiers and compare their performance in DataRobot. 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 and Mean Squared error. Learn how to build, train, test and deploy advanced machine learning classification models using Google Vertex AI. Understand how to leverage the power of AI/ML to predict bank customers credit card default using their features such as interest rates and loan purpose Learn how to create a new dataset using Google Vertex AI Develop and manage experiments using Google Vertex AI. Understand the theory, intuition, and mathematics behind simple and multiple linear regression and differentiate between various regression models KPIs. Deploy the best model after the hyperparameters optimization job is complete and Learn how to assess feature importance and explain model predictions. Deploy and monitor AI/ML models and create AI/ML applications with Google Vertex AI. This course is ideal for individuals who are Seasoned consultants who don’t possess coding skills (or have basic coding skills) and wanting to transform businesses by leveraging AI. or Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business. or AI Practitioners wanting to advance their careers and build their portfolio. or Tech enthusiasts who are passionate about AI and want to gain real-world practical experience. It is particularly useful for Seasoned consultants who don’t possess coding skills (or have basic coding skills) and wanting to transform businesses by leveraging AI. or Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business. or AI Practitioners wanting to advance their careers and build their portfolio. or Tech enthusiasts who are passionate about AI and want to gain real-world practical experience.
Enroll now: 10 Days of No Code Artificial Intelligence Bootcamp
Summary
Title: 10 Days of No Code Artificial Intelligence Bootcamp
Price: $89.99
Average Rating: 4.43
Number of Lectures: 115
Number of Quizzes: 11
Number of Published Lectures: 113
Number of Published Quizzes: 11
Number of Curriculum Items: 126
Number of Published Curriculum Objects: 124
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will Learn
- Build, train, test and deploy 10 AI/ML models in 10 days without writing any code.
- Build, train, test and deploy AI models to classify fashion items using Google Teachable Machine.
- Visualize State-of-the-Art Artificial Intelligence Models Using Tensorspace JS, Google Tensorflow Playground and Ryerson 3D CNN Visualizations.
- Explain the difference between learning rate, epochs, batch size, accuracy, and loss.
- Build, train and deploy advanced AI to detect Diabetic Retinopathy disease using DataRobot AI.
- Leverage the power of AI to solve regression tasks and predict used car prices using DataRobot AI.
- Evaluate trained AI models using various KPIs such as confusion matrix, classification accuracy, and error rate.
- Understand the theory and intuition behind Residual Neural Networks (ResNets), a state-of-the-art deep NNs that are widely adopted in several industries.
- Understand the impact of classifier threshold on False Positive Rate (Fallout) and True Positive Rate (Sensitivity).
- Predict employee attrition based on their features such as employee engagement, distance from home, job satisfaction using DataRobot AI.
- Develop an AI model to detect face masks using Google Teachable Machines.
- Build, train and deploy XGBoost-based algorithm to perform regression tasks using AWS SageMaker Autopilot.
- Learn how to transfer knowledge from a pre-trained Artificial Neural Network to a new network using transfer learning strategy.
- Learn how to train multiple AI models based on XG-Boost, Artificial Neural Networks, Random Forest Classifiers and compare their performance in DataRobot.
- 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 and Mean Squared error.
- Learn how to build, train, test and deploy advanced machine learning classification models using Google Vertex AI.
- Understand how to leverage the power of AI/ML to predict bank customers credit card default using their features such as interest rates and loan purpose
- Learn how to create a new dataset using Google Vertex AI Develop and manage experiments using Google Vertex AI.
- Understand the theory, intuition, and mathematics behind simple and multiple linear regression and differentiate between various regression models KPIs.
- Deploy the best model after the hyperparameters optimization job is complete and Learn how to assess feature importance and explain model predictions.
- Deploy and monitor AI/ML models and create AI/ML applications with Google Vertex AI.
Who Should Attend
- Seasoned consultants who don’t possess coding skills (or have basic coding skills) and wanting to transform businesses by leveraging AI.
- Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business.
- AI Practitioners wanting to advance their careers and build their portfolio.
- Tech enthusiasts who are passionate about AI and want to gain real-world practical experience.
Target Audiences
- Seasoned consultants who don’t possess coding skills (or have basic coding skills) and wanting to transform businesses by leveraging AI.
- Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business.
- AI Practitioners wanting to advance their careers and build their portfolio.
- Tech enthusiasts who are passionate about AI and want to gain real-world practical experience.
The no-code AI revolution is here! Do you have what it takes to leverage this new wave of code-friendly tools paving the way for the future of AI?
Businesses of all sizes want to implement the power of Machine Learning and AI, but the barriers to entry are high. That’s where no-code AI/ML tools are changing the game.
From fast implementation to lower costs of development and ease of use, departments across healthcare, finance, marketing and more are looking to no-code solutions to deliver impactful solutions.
But groundbreaking as they are, they’re nothing without talent like YOU calling the shots…
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Do you want to leverage machine learning and AI but feel intimidated by the complex coding involved?
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Do you want to master some of the top no-code tools on the market?
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Do you want to implement ML and AI solutions in your business, but don’t have the academic background to understand?
Yes?! Then this course is for you.
Master the top tools on the market and start solving practical industry scenarios when you enroll in our new course: 10 Days of No Code Artificial Intelligence Bootcamp
Join our best-selling instructor Dr. Ryan Ahmed and learn how to build, train, test, and deploy models that solve 10 practical challenges across finance, human resources, business, and more, using these state-of-the-art tools:
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Google Teachable Machine
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Google TensorFlow Playground
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DataRobot
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AWS SageMaker Autopilot
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Google Vertex AI
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Tensorspace.JS
The best part? You’ll be done in 10 days or less!
Take a look at the 10 professional projects you will complete:
Day #1: Develop an AI model to classify fashion elements using Google Teachable Machines.
Day #2:Deep-dive into AI technicalities by tweaking hyperparameters, epochs, and network architecture.
Day #3:Build, train, test, and deploy an AI model to detect and classify face masks using Google Teachable Machines.
Day #4:Visualize state-of-the-art AI models using Tensorspace.JS, Google Tensorflow Playground, and Ryerson 3D CNN Visualizations.
Day #5:Develop a machine learning model to predict used car prices using DataRobot.
Day #6:Develop an AI model to predict employee attrition rate using DataRobot.
Day #7:Develop an AI model to detect Diabetic Retinopathy Disease using DataRobot
Day #8:Build, train, test, and deploy an AI model to predict customer sentiment from text.
Day #9:Develop an AI to predict credit card default using AWS SageMaker Autopilot.
Day #10:Develop an AI model to predict university admission using Google Vertex AI.
Ready to challenge your AI skills in new and exciting ways? Enroll now and experience the power of no-code AI tools.
Course Curriculum
Chapter 1: Welcome to the Course!
Lecture 1: Main Course Intro
Lecture 2: Course Introduction and Best Practices
Lecture 3: AI Superpowers
Lecture 4: Key AI Components
Lecture 5: Course Outline
Chapter 2: Day 1: Develop an AI model to classify fashion elements using Google Teachable
Lecture 1: Introduction to Day 1
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. AI Applications in Fashion
Lecture 4: Task 3. Data Exploration
Lecture 5: Task 4. Model Training and Testing in Google Teachable Machines
Lecture 6: Task 5. Export and Deploy Model in Google Teachable Machines
Lecture 7: Task 6. Final Project
Lecture 8: End of Day 1
Chapter 3: Day 2: Deep Dive into AI technicalities
Lecture 1: Introduction to Day 2
Lecture 2: Task 1. Project Overview
Lecture 3: Task 2. Artificial Neural Networks (ANNs) Simplified
Lecture 4: Task 3. AI Training vs. Testing Process
Lecture 5: Task 4. AI Lingo
Lecture 6: Task 5. Confusion Matrix
Lecture 7: Task 6. Final Project Part A
Lecture 8: Task 7. Final Project Part B
Lecture 9: End of Day 2
Chapter 4: Day 3: Detect and classify face masks using Google Teachable Machines
Lecture 1: Introduction Day 3
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Business Case
Lecture 4: Task 3. Google Teachable Machines Demo: Data Collection
Lecture 5: Task 4. Google Teachable Machines Demo: Model Training
Lecture 6: Task 5. Google Teachable Machines Demo: Model Evaluation/Deployment
Lecture 7: Task 6. Classifier Models KPIs
Lecture 8: Task 7. Precision vs. Recall
Lecture 9: Task 8. Final Project
Lecture 10: End of Day 3
Chapter 5: Day 4: Visualize Artificial Intelligence Models Using Tensorspace.JS and GTP
Lecture 1: Introduction Day 4
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Artificial Neural Networks 101
Lecture 4: Task 3. Visualize ANNs in GTP
Lecture 5: Task 4. Final Project Part A
Lecture 6: Task 5. Convolutional Neural Networks (CNNs)
Lecture 7: Task 6. CNNs Visualization
Lecture 8: Task 7. LeNet Architecture Overview
Lecture 9: Task 8. 3D Visualization in Tensorspace.JS
Lecture 10: Task 9. ResNet Visualization in TensorSpace.JS
Lecture 11: Task 10. Final Project
Lecture 12: End of Day 4
Chapter 6: Day 5: Develop an ML Model to predict used car prices using DataRobot
Lecture 1: Introduction Day 5
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Success Stories and Business Case
Lecture 4: Task 3. Data Overview
Lecture 5: Task 4. DataRobot Demo: Data Upload
Lecture 6: Task 5. DataRobot Demo: Exploratory Data Analysis
Lecture 7: Task 6. DataRobot Demo: Model Training
Lecture 8: Task 7. DataRobot Demo: Model Assessment
Lecture 9: Task 8. DataRobot Demo: Model Deployment
Lecture 10: Task 9. Technicalities
Lecture 11: Task 10. Final Project Part A
Lecture 12: Task 11. Final Project Part B
Lecture 13: End of Day 5
Chapter 7: Day 6: Develop an AI model to predict employee’s attrition using DataRobot
Lecture 1: Introduction Day 6
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Success Stories and Business Case
Lecture 4: Reading Materials: How AI is Transforming Human Resources?
Lecture 5: Task 3. Data Overview
Lecture 6: Task 4. DataRobot Demo: Data Upload
Lecture 7: Task 5. DataRobot Demo: Data Exploration
Lecture 8: Task 6. DataRobot Demo: Model Training
Lecture 9: Task 7. Classification Models KPIs
Lecture 10: Task 8. Model Assessment
Lecture 11: Task 9. Final Project
Lecture 12: End of Day 6
Chapter 8: Day 7: Develop an AI model to detect Diabetic Retinopathy Using DataRobot
Lecture 1: Introduction Day 7
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Business Case and Success Stories
Lecture 4: Task 3. Data Exploration
Lecture 5: Task 4. DataRobot Demo: Data Upload
Lecture 6: Task 5. DataRobot Demo: Model Training
Lecture 7: Task 6. DataRobot Demo: Deploy Model
Lecture 8: Task 7. Explainable AI
Lecture 9: Task 8. Final Project
Lecture 10: End of Day 7
Chapter 9: Day 8: Deploy an AI model to predict customer sentiment from Text
Lecture 1: Introduction to Day 8
Lecture 2: Task 1. Project Card and Demo
Lecture 3: Task 2. Business Case, Reading Materials and Quiz
Lecture 4: Task 3. Data Exploration
Instructors
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Dr. Ryan Ahmed, Ph.D., MBA
Best-Selling Professor, 400K+ students, 250K+ YT Subs -
Ligency Team
Helping Data Scientists Succeed -
SuperDataScience Team
Helping Data Scientists Succeed -
Mitchell Bouchard
B.S, Host @RedCapeLearning 540,000 + Students
Rating Distribution
- 1 stars: 21 votes
- 2 stars: 18 votes
- 3 stars: 105 votes
- 4 stars: 379 votes
- 5 stars: 620 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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!
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