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 |
Start Learning | Course Content |
Lecture 2: Bacis Machine Learning Concepts and Processes |
Understand Machine Learning techniques at a high level |
Start Learning | Course Content |
Lecture 3: Classification of Machine Learning Methods |
Understand the concept, essence and mainstream technology of cloud native |
Start Learning | Course Content |
Lecture 4: Development history of Machine Learning |
Understand the early history of Machine Learning and AI techniques |
Start Learning | Course Content |
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 |
Start Learning | Course Content |
Lecture 2: KNN (K-nearest Neighbors) |
Understand the KNN algorithm |
Start Learning | Course Content |
Lecture 3: Naïve Bayes |
Understand the Naïve Bayes algorithm |
Start Learning | Course Content |
Lecture 4: Decision Tree |
Understand the Decision Tree algorithm |
Start Learning | Course Content |
Lecture 5: Hierarchical Clustering |
Understand the Hierarchichal Clustering algorithm |
Start Learning | Course Content |
Lecture 6: K-means Clustering |
Understand the K-Means Clustering algorithm |
Start Learning | Course Content |
Lecture 7: Hands-on (lab) section |
Try out some basic Machine Learning algorithms hands-on |
Start Learning | |
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 |
Start Learning | Course Content |
Lecture 2: Neural Networks: Structure |
Understand the architecture of Neural Networks at a high level |
Start Learning | Course Content |
Lecture 3: Neural Networks: Optimization |
Understand optimization algorithms that are used with Neural Networks |
Start Learning | Course Content |
Lecture 4: Deep Learning: Basic Concepts |
Understand the general ideas behind so-called "Deep Learning" |
Start Learning | Course Content |
Lecture5: Convolutional Neural Networks and their Applications |
Understand the applications of CNNs, one of the most common types of Neural Network |
Start Learning | Course Content |
Lecture 6: Recurrent Neural Networks and their Applications |
Understand the applications of RNNs |
Start Learning | Course Content |
Lecture 7: Hands-on practice |
Gain hands-on practice with Neural Networks |
Start Learning | Course Content |
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 |
Start Learning | Course Content |
Lecture 2: Word2Vec |
Understand the Word2Vec model |
Start Learning | Course Content |
Lecture 3: Transformer |
Understand the Transformer model |
Start Learning | Course Content |
Lecture 4: BERT |
Understand the BERT language model |
Start Learning | Course Content |
Lecture 5: Sentiment Analysis |
Understand the basics of sentiment analysis |
Start Learning | Course Content |
Lecture 6: Chatbots |
Understand the basics of intelligent chatbots |
Start Learning | Course Content |
Lecture 7: Machine Translation |
Understand the basics of Machine Translation |
Start Learning | Course Content |
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 |
Start Learning | Course Content |
Lecture 2: Basic Syntax |
Understand TensorFlow's grammar and syntax |
Start Learning | Course Content |
Lecture 3: Development Process |
Understand how to set up TensorFlow and begin writing code |
Start Learning | Course Content |
Lecture 4: Development history of Machine Learning |
Understand the basics of Neural Network model development |
Start Learning | Course Content |
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 |
Start Learning | Course Content |
Lecture 2: Visual (Studio) Development With PAI |
Understand how to use PAI's visual development interface |
Start Learning | Course Content |
Lecture 3: Notebook Development With PAI |
Understand how to use PAI's Jupyter notebook interface |
Start Learning | Course Content |
Lecture 4: Application: Image Classification |
See how PAI can be used to classify images |
Start Learning | Course Content |
Lecture 5: Application: Sentiment Analysis |
See how PAI can be used to build a sentiment analysis tool |
Start Learning | Course Content |
Lecture 6: Application: Product Recommendations |
See how PAI can be used to build recommender systems |
Start Learning | Course Content |
Quiz |
Test for the whole chapter and get your certification |
Quiz |