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Automated Machine Learning for Beginners (Google & Apple)

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Automated Machine Learning for Beginners (Google & Apple), available at $74.99, has an average rating of 4.44, with 103 lectures, 6 quizzes, based on 476 reviews, and has 83485 subscribers.

You will learn about Master Automated Machine Learning with Google Cloud AutoML & Apple Create ML Train meaningful Machine Learning Models without a single line of code Tackle problems in Computer Vision, Natural Language Processing and Regression Identify & Solve Real-Life Machine Learning Problems Build a Simple AI-Powered App for Android, iOS or both Ideate your own Product as part of your Course Project This course is ideal for individuals who are Beginners without any background in programming or computer science or Anyone who wants to automate the Machine Learning process or Students who want to start a career in Artificial Intelligence and Machine Learning or Professionals who want to learn how to apply Machine Learning in their respective jobs or Anyone beginning their journey in Machine Learning It is particularly useful for Beginners without any background in programming or computer science or Anyone who wants to automate the Machine Learning process or Students who want to start a career in Artificial Intelligence and Machine Learning or Professionals who want to learn how to apply Machine Learning in their respective jobs or Anyone beginning their journey in Machine Learning.

Enroll now: Automated Machine Learning for Beginners (Google & Apple)

Summary

Title: Automated Machine Learning for Beginners (Google & Apple)

Price: $74.99

Average Rating: 4.44

Number of Lectures: 103

Number of Quizzes: 6

Number of Published Lectures: 92

Number of Published Quizzes: 6

Number of Curriculum Items: 110

Number of Published Curriculum Objects: 99

Original Price: $79.99

Quality Status: approved

Status: Live

What You Will Learn

  • Master Automated Machine Learning with Google Cloud AutoML & Apple Create ML
  • Train meaningful Machine Learning Models without a single line of code
  • Tackle problems in Computer Vision, Natural Language Processing and Regression
  • Identify & Solve Real-Life Machine Learning Problems
  • Build a Simple AI-Powered App for Android, iOS or both
  • Ideate your own Product as part of your Course Project

Who Should Attend

  • Beginners without any background in programming or computer science
  • Anyone who wants to automate the Machine Learning process
  • Students who want to start a career in Artificial Intelligence and Machine Learning
  • Professionals who want to learn how to apply Machine Learning in their respective jobs
  • Anyone beginning their journey in Machine Learning

Target Audiences

  • Beginners without any background in programming or computer science
  • Anyone who wants to automate the Machine Learning process
  • Students who want to start a career in Artificial Intelligence and Machine Learning
  • Professionals who want to learn how to apply Machine Learning in their respective jobs
  • Anyone beginning their journey in Machine Learning

Begin your AI journey with Automated Machine Learning!

This course focuses on giving you the big picture of Artificial Intelligence: the streamlined process of creating AI machine learning models. Leave the mathematical equations and Python coding aside and concentrate on what really matters!

Course Architecture guarantees Best Cognitive Learning Outcomes

Richard Shinn, PhD in AI and CEO of AIBrain, is the Chief Architect behind this course. He designed the entire course structure to help learners acquire cognitive skills; learning by examples first, then learning based on denotational semantics and operational semantics. This two-step approach is particularly useful when we deal with the complexity of real-world problems.

Learn Hands-On

From day 1, you will learn hands-on skills. You will follow our lab instructors to build Machine Learning models with AutoML. By the end of the course, you will be able to build a working AI-powered mobile app. Following Richard Feynman’s principle “What I cannot create, I do not understand” we teach practical knowledge from day one.

Deepen your Skills

To make sure that you will get a deep understanding of all the topics, you will have practical homework assignments accompanying all labs. Each lab has its own homework assignments to help you deepen the skills learned during the course. 

Gain a Certificate from a Leading AI Company

Kick-start your career in AI with an official certificate from a leading AI company! Upon completion of the course, you will be awarded with a verified certificate of completion. 

Complete a Term Project: Build your own ML Model

As part of this course, you will ideate your own AI-powered product that leverages Machine Learning. You will build a simple low-fidelity prototype of an AI-powered application before building a custom Machine Learning model with AutoML for your idea.

Get 1-1 Advice and Guidance

We have lab instructors available for 1-on-1 assistance in case you need help with your homework assignments. Reach out to our lab instructors any time in our AI School Community.

Join the AI School Community

Use our vivid AISchool Community and Discord channel to discuss with your peers and leverage the power of community. Share your questions and answers with lab instructors and fellow students. 

Evaluate your Progress

During your journey, you will always have the possibility to evaluate your progress and understanding of the materials through quizzes. This will help you to constantly measure your success and help to check your understanding of core concepts. 

Build your Professional Network

Stay in touch with your peers and leverage a professional network of like-minded AI practitioners. In our community, we provide a dedicated alumni channel for all successful graduates of our course.

The course takes you through 4 carefully structured topics.

Topic 1

Introduction to Automated Machine Learning

Find out how AutoML is transforming the data science game by enabling anyone to build machine learning models without a single line of code. Familiarize yourself with the 5-Step ML Pipeline to solve any Machine Learning problem, before building your very first AI-powered smartphone application in 30 minutes.

Topic 2

Vision AI with Google AutoML & Apple CreateML

AI can help computers to interpret and understand digital images. In this segment, you will train models that can accurately locate and classify objects.

Topic 3

NLP & Tables with Google AutoML & Apple CreateML

AI can help computers understand text and spoken words just like humans. Use SNS posts and new articles to train models to classify emotion and content.

AI can analyze patterns across data with numerous variables. Use tabular data to predict house prices.

Topic 4

Deploy AI in an Application

Easily deploy models on to your device and test it in real world settings.

Course Curriculum

Chapter 1: Introduction to the Course

Lecture 1: Welcome to the Course

Lecture 2: Introduction Video

Lecture 3: The AIBrain Community

Lecture 4: Choose your Machine Learning Platform

Chapter 2: Introduction to Automated Machine Learning

Lecture 1: Why Automated Machine Learning?

Lecture 2: The 5-Step Machine Learning Pipeline

Lecture 3: Term Project Announcement

Chapter 3: Vision AI with Google AutoML

Lecture 1: Before You Begin

Lecture 2: Guidelines for AutoML Labs

Lecture 3: Image Classification – Introduction

Lecture 4: Image Classification – 5 Step ML Pipeline

Lecture 5: Image Classification – Preparing Dataset & Train Model

Lecture 6: Image Classification – Deploy & Test

Lecture 7: Image Classification – Takeaways

Lecture 8: Image Classification – Assignment

Lecture 9: Object Detection – Introduction

Lecture 10: Object Detection – 5 Step ML Pipeline

Lecture 11: Object Detection – Preparing Dataset

Lecture 12: Object Detection – Train & Evaluate

Lecture 13: Object Detection – Takeaways

Lecture 14: Object Detection – Assignment

Chapter 4: Vision AI with Apple Create ML

Lecture 1: Before You Begin

Lecture 2: Image Classification – Introduction

Lecture 3: Image Classification – 5 Step ML Pipeline

Lecture 4: Image Classification – Getting Started

Lecture 5: Image Classification – Train & Evaluate Model

Lecture 6: Image Classification – Takeaways

Lecture 7: Image Classification – Assignment

Lecture 8: Object Detection – Introduction

Lecture 9: Object Detection – 5 Step ML Pipeline

Lecture 10: Object Detection – Getting Started

Lecture 11: Object Detection – Dataset Annotation

Lecture 12: Object Detection – Evaluate Model

Lecture 13: Object Detection – Takeaways

Lecture 14: Object Detection – Assignment

Chapter 5: Natural Language Processing with Google AutoML

Lecture 1: Sentiment Analysis – Introduction

Lecture 2: Sentiment Analysis – 5 Step ML Pipeline

Lecture 3: Sentiment Analysis – Obtaining Dataset & Train Model

Lecture 4: Sentiment Analysis – Deploy & Evaluate

Lecture 5: Sentiment Analysis – Takeaways

Lecture 6: Sentiment Analysis – Assignment

Lecture 7: Document Classification – Introduction

Lecture 8: Document Classification – 5 Step Pipeline

Lecture 9: Document Classification – Train Model

Lecture 10: Document Classification – Evaluate & Test Model

Lecture 11: Document Classification – Takeaways

Lecture 12: Document Classification – Assignment

Chapter 6: Natural Language Processing with Create ML

Lecture 1: Sentiment Analysis – Introduction

Lecture 2: Sentiment Analysis – 5 Step Pipeline

Lecture 3: Sentiment Analysis – Getting Started

Lecture 4: Sentiment Analysis – Dataset Preparation

Lecture 5: Sentiment Analysis – Training & Evaluation

Lecture 6: Sentiment Analysis – Takeaways

Lecture 7: Sentiment Analysis – Assignment

Lecture 8: Document Classification – Introduction

Lecture 9: Document Classification – 5 Step ML Pipeline

Lecture 10: Document Classification – Getting Started

Lecture 11: Document Classification – Dataset Preparation

Lecture 12: Document Classification – Training & Testing

Lecture 13: Document Classification – Takeaways

Lecture 14: Document Classification – Assignment

Chapter 7: Tabular Prediction with Google AutoML

Lecture 1: Tabular Prediction – Introduction

Lecture 2: Tabular Prediction – The 5-Step ML Pipeline

Lecture 3: Tabular Prediction – Train & Evaluate

Lecture 4: Tabular Prediction – Takeaways

Lecture 5: Tabular Prediction – Assignment

Chapter 8: Tabular Prediction with CreateML

Lecture 1: Tabular Prediction – Introduction

Lecture 2: Tabular Prediction – 5-Step ML Pipeline

Lecture 3: Tabular Data – House Price Prediction

Lecture 4: Tabular Prediction – Takeaways

Lecture 5: Tabular Prediction – Assignment

Chapter 9: Term Project 1: Digital Prototyping

Lecture 1: Digital Prototyping with Figma

Lecture 2: Why Prototyping?

Lecture 3: Getting Started with Figma

Lecture 4: Populating your Prototype

Lecture 5: Takeaways

Lecture 6: Product Idea & Digital Prototype

Chapter 10: Deploy AI in Android App

Lecture 1: Introduction

Lecture 2: The 5-Step Machine Learning Pipeline

Lecture 3: Prerequisites

Lecture 4: Set Up Android Studio

Lecture 5: Brief Introduction to Android Studio

Lecture 6: Deploy ML Model in Sample Andoid Application

Instructors

Rating Distribution

  • 1 stars: 6 votes
  • 2 stars: 12 votes
  • 3 stars: 50 votes
  • 4 stars: 153 votes
  • 5 stars: 255 votes

Frequently Asked Questions


How long do I have access to the course materials?


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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