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AI For Everyone: From Basics to Applications

Course Overview

In this course, we review Machine Learning and AI from top to bottom. Starting with an overview of the history of the field, we then move on to basic concepts and processes in machine learning. From there, we give detailed explanations of common algorithms in both general Machine Learning and other fields such as natural language processing (NLP). By the end of the course, students are not only familiar with common algorithms, but will have gained valuable hands-on experience with TensorFlow, a common open source AI and Machine Learning framework, as well as Machine Learning Platform for AI (PAI), Alibaba Cloud’s sophisticated but simple drag-and-drop Machine Learning tool.

In this course, we will introduce you to a wide variety of Machine Learning and AI material, including:

  • The early history of machine learning and artificial intelligence
  • Common machine learning algorithms and their applications
  • Common deep learning tools and methods (Neural Networks, TensorFlow)
  • Natural Language Processing: algorithms and applications
  • Hands-on practice with TensorFlow and Alibaba Cloud’s Machine Learning Platform for AI (PAI)

Target Audience

Developers

Solution Architects

Data Scientists

Students

Chapter 1: Machine Learning Overview: Concepts and History

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Machine Learning and Artificial Intelligence

Gain a simple understanding of Machine Learning and AI at a high level

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Lecture 2: Bacis Machine Learning Concepts and Processes

Understand Machine Learning techniques at a high level

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Lecture 3: Classification of Machine Learning Methods

Understand the concept, essence and mainstream technology of cloud native

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Lecture 4: Development history of Machine Learning

Understand the early history of Machine Learning and AI techniques

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Quiz

Test for the whole chapter and get your certification

Quiz

Chapter 2: Introduction to Machine Learning Algorithms

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Perceptron

Understand the perceptron algorithm

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Lecture 2: KNN (K-nearest Neighbors)

Understand the KNN algorithm

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Lecture 3: Naïve Bayes

Understand the Naïve Bayes algorithm

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Lecture 4: Decision Tree

Understand the Decision Tree algorithm

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Lecture 5: Hierarchical Clustering

Understand the Hierarchichal Clustering algorithm

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Lecture 6: K-means Clustering

Understand the K-Means Clustering algorithm

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Lecture 7: Hands-on (lab) section

Try out some basic Machine Learning algorithms hands-on

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Quiz

Test for the whole chapter and get your certification

Quiz

Chapter 3: Neural Network Basics and Deep Learning

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Neural Networks: Basic Concepts

Understand Neural Networks at a high level

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Lecture 2: Neural Networks: Structure

Understand the architecture of Neural Networks at a high level

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Lecture 3: Neural Networks: Optimization

Understand optimization algorithms that are used with Neural Networks

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Lecture 4: Deep Learning: Basic Concepts

Understand the general ideas behind so-called "Deep Learning"

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Lecture5: Convolutional Neural Networks and their Applications

Understand the applications of CNNs, one of the most common types of Neural Network

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Lecture 6: Recurrent Neural Networks and their Applications

Understand the applications of RNNs

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Lecture 7: Hands-on practice

Gain hands-on practice with Neural Networks

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Quiz

Test for the whole chapter and get your certification

Quiz

Chapter 4: Natural Language Processing

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Statistical Language Model

Understand statistical language models

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Lecture 2: Word2Vec

Understand the Word2Vec model

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Lecture 3: Transformer

Understand the Transformer model

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Lecture 4: BERT

Understand the BERT language model

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Lecture 5: Sentiment Analysis

Understand the basics of sentiment analysis

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Lecture 6: Chatbots

Understand the basics of intelligent chatbots

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Lecture 7: Machine Translation

Understand the basics of Machine Translation

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Quiz

Test for the whole chapter and get your certification

Quiz

Chapter 5: Introduction to TensorFlow

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Architecture and Working Principles

Understand how TensorFlow works at a high level

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Lecture 2: Basic Syntax

Understand TensorFlow's grammar and syntax

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Lecture 3: Development Process

Understand how to set up TensorFlow and begin writing code

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Lecture 4: Development history of Machine Learning

Understand the basics of Neural Network model development

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Quiz

Test for the whole chapter and get your certification

Quiz

Chapter 6: Alibaba Cloud Machine Learning Platform for AI (PAI)

Course List

Learning Objectives

Video Course

Course Content

Lecture 1: Introduction to PAI

Understand what PAI is and what it can do

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Lecture 2: Visual (Studio) Development With PAI

Understand how to use PAI's visual development interface

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Lecture 3: Notebook Development With PAI

Understand how to use PAI's Jupyter notebook interface

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Lecture 4: Application: Image Classification

See how PAI can be used to classify images

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Lecture 5: Application: Sentiment Analysis

See how PAI can be used to build a sentiment analysis tool

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Lecture 6: Application: Product Recommendations

See how PAI can be used to build recommender systems

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Quiz

Test for the whole chapter and get your certification

Quiz