No-Code and No-Math Machine Learning
No-Code and No-Math Machine Learning, available at $64.99, has an average rating of 4.6, with 41 lectures, based on 115 reviews, and has 1151 subscribers.
You will learn about Build machine learning models to use on real problems without a single line of code and no math skills Use the main tools applied in classification, regression and time series forecasting problems Implement machine learning in the following tools: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure and Orange Learn how to deploy machine learning models This course is ideal for individuals who are People interested in building real machine learning models without a single line of code or People interested in starting their studies in Machine Learning and Data Science or Students who have little programming or math experience or Undergraduate and graduate students who are studying subjects related to the area of Artificial Intelligence It is particularly useful for People interested in building real machine learning models without a single line of code or People interested in starting their studies in Machine Learning and Data Science or Students who have little programming or math experience or Undergraduate and graduate students who are studying subjects related to the area of Artificial Intelligence.
Enroll now: No-Code and No-Math Machine Learning
Summary
Title: No-Code and No-Math Machine Learning
Price: $64.99
Average Rating: 4.6
Number of Lectures: 41
Number of Published Lectures: 41
Number of Curriculum Items: 41
Number of Published Curriculum Objects: 41
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Build machine learning models to use on real problems without a single line of code and no math skills
- Use the main tools applied in classification, regression and time series forecasting problems
- Implement machine learning in the following tools: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure and Orange
- Learn how to deploy machine learning models
Who Should Attend
- People interested in building real machine learning models without a single line of code
- People interested in starting their studies in Machine Learning and Data Science
- Students who have little programming or math experience
- Undergraduate and graduate students who are studying subjects related to the area of Artificial Intelligence
Target Audiences
- People interested in building real machine learning models without a single line of code
- People interested in starting their studies in Machine Learning and Data Science
- Students who have little programming or math experience
- Undergraduate and graduate students who are studying subjects related to the area of Artificial Intelligence
If you want to learn machine learning but you feel intimidated by programming or math fundamentals, this course is for you!
You are going to learn how to build projects using six tools that do not require any prior knowledge of computer programming or math! This course was designed for you to create hands-on projects quickly and easily, without a single line of code. It is suitable for beginners and also for students with intermediate or advanced knowledge, who need to increase productivity but at the same time do not have the time to implement code from scratch. You can perform exploratory data analysis, build, train, test and put machine learning models into production with a few clicks!
We are going to cover 6 tools that are widely used for commercial projects: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure Machine Learning, and Orange! All projects will be developed calmly and step by step, so that you can make the most of the content. There is an exercise along with the solution at the end of each section, so you can practice the steps for each tool! There are more than 30 lectures and 5 hours of videos!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Course content
Lecture 2: Machine Learning – intuition
Lecture 3: Course materials
Chapter 2: Google Vertex AI
Lecture 1: Overview
Lecture 2: Datasets
Lecture 3: Training
Lecture 4: Regression metrics
Lecture 5: Deploy and predictions
Lecture 6: HOMEWORK
Lecture 7: Homework solution
Chapter 3: Data Robot AI
Lecture 1: Overview
Lecture 2: Datasets
Lecture 3: Classification metrics
Lecture 4: Training
Lecture 5: Deploy and predictions
Lecture 6: HOMEWORK
Lecture 7: Homework solution
Chapter 4: Obviously AI
Lecture 1: Overview
Lecture 2: Dataset, training, and predictions
Lecture 3: HOMEWORK
Lecture 4: Homework solution
Chapter 5: Big ML
Lecture 1: Overview
Lecture 2: Dataset
Lecture 3: Training and evaluating
Lecture 4: Predictions
Lecture 5: HOMEWORK
Lecture 6: Homework solution
Chapter 6: Microsoft Azure
Lecture 1: Overview
Lecture 2: Workspace and dataset
Lecture 3: Machine learning pipeline
Lecture 4: Evaluation and deploy
Lecture 5: Auto ML
Lecture 6: HOMEWORK
Lecture 7: Homework solution
Chapter 7: Orange
Lecture 1: Overview
Lecture 2: Classification
Lecture 3: Time series
Lecture 4: HOMEWORK
Lecture 5: Homework solution
Chapter 8: Final remarks
Lecture 1: Final remarks
Lecture 2: BONUS
Instructors
-
Jones Granatyr
Professor -
AI Expert Academy
Instructor
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 2 votes
- 3 stars: 10 votes
- 4 stars: 32 votes
- 5 stars: 69 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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