Coursera

离散数学概论 Discrete Mathematics Generality (Coursera)

Offered by Peking University,
离散数学概论 Discrete Mathematics Generality (Coursera)

本课程面向非计算机软件专业本科生及相关IT行业从业人士，介绍计算机科学和信息技术理论基础的概念和思想方法。

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

离散数学是计算机科学的基础理论，离散结构的基础知识和逻辑思维的形式化是信息技术类学生的基本功，离散数学的基本概念是理科专业学生进行信息类课程学习的重要基础。

本课程介绍计算机科学和信息技术理论基础的概念和思想方法，介绍数理逻辑、集合论、图论、抽象代数和形式语言与自动机等各部分的基本概念，介绍离散数学基本概念和空间信息技术之间的联系与结合，培养学生理解和掌握离散数学基本概念，采用形式化方法分析问题，并能自觉运用逻辑分析、结构层次分析和同构类比等思想方法解决问题的能力。

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Self-Driving Cars (Coursera) Coursera
University of Toronto

Introduction to Self-Driving Cars (Coursera)

CS: Software Engineering Computer Science

Welcome to Introduction to Self-Driving Cars, the first course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the terminology, design considerations and safety assessment of self-driving cars. By the end of this course, you will be able to: Understand commonly used hardware used for self-driving cars; Identify the main components of the self-driving software stack; Program vehicle modelling and control; Analyze the safety frameworks and current industry practices for vehicle development

Jul 27th 2026
5-12 Weeks
Computer Science Vehicle Dynamics Software Development
Details
Agile Planning for Software Products (Coursera) Coursera
University of Alberta

Agile Planning for Software Products (Coursera)

CS: Design & Product

This course covers the techniques required to break down and map requirements into plans that will ultimately drive software production. Upon successful completion of this course, you will be able to: create effective plans for software development; map user requirements to developer tasks; assess and plan for project risks; apply velocity-driven planning techniques; generate work estimates for software products.

Aug 3rd 2026
4 Weeks
Risk Agile PERT
Details
Problem Solving, Python Programming, and Video Games (Coursera) Coursera
University of Alberta

Problem Solving, Python Programming, and Video Games (Coursera)

CS: Programming

This course is an introduction to computer science and programming in Python. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. However, a learner can take the knowledge and skills from this course and apply them to non-game problems, other programming languages, and other computer science courses.

Jul 27th 2026
5-12 Weeks
Programming Python Algorithms
Details
Algorithmic Thinking (Part 2) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 2) (Coursera)

CS: Theory

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Aug 10th 2026
4 Weeks
Python Computing Algorithms
Details
Introduction to User Experience Design (Coursera) Coursera
Georgia Institute of Technology

Introduction to User Experience Design (Coursera)

CS: Design & Product

The focus of this course is to introduce the learner to User Experience (UX) Design. User Experience design is design that is user centered. The goal is to design artifacts that allow the users to meet their needs in the most effective efficient and satisfying manner. The course introduces the novice to a cycle of discovery and evaluation and a set of techniques that meet the user's needs.

Aug 10th 2026
5-12 Weeks
Computer Science UX User Experience
Details
Approximation Algorithms Part II (Coursera) Coursera
École normale supérieure

Approximation Algorithms Part II (Coursera)

CS: Software Engineering CS: Programming

This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques.

Aug 3rd 2026
4 Weeks
Algorithms Computer Science Linear Programming
Details
Introduction to Graph Theory (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Introduction to Graph Theory (Coursera)

CS: Software Engineering CS: Theory

We invite you to a fascinating journey into Graph Theory — an area which connects the elegance of painting and the rigor of mathematics; is simple, but not unsophisticated. Graph Theory gives us, both an easy way to pictorially represent many major mathematical results, and insights into the deep theories behind them. In this course, among other intriguing applications, we will see how GPS systems find shortest routes, how engineers design integrated circuits, how biologists assemble genomes, why a political map can always be colored using a few colors. We will study Ramsey Theory which proves that in a large system, complete disorder is impossible!

Jul 27th 2026
5-12 Weeks
Network Algorithms Genomes
Details
Visual Perception for Self-Driving Cars (Coursera) Coursera
University of Toronto

Visual Perception for Self-Driving Cars (Coursera)

CS: Software Engineering Computer Science

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks.

Jul 27th 2026
5-12 Weeks
Neural Networks Computer Science Vehicle Dynamics
Details
Internet History, Technology, and Security (Coursera) Coursera
University of Michigan

Internet History, Technology, and Security (Coursera)

Security & Networking

The impact of technology and networks on our lives, culture, and society continues to increase. The very fact that you can take this course from anywhere in the world requires a technological infrastructure that was designed, engineered, and built over the past sixty years. To function in an information-centric world, we need to understand the workings of network technology. This course will open up the Internet and show you how it was created, who created it and how it works. Along the way we will meet many of the innovators who developed the Internet and Web technologies that we use today.

Jul 27th 2026
5-12 Weeks
Network Security Computing
Details
International Cyber Conflicts (Coursera) Coursera
The State University of New York

International Cyber Conflicts (Coursera)

Security & Networking

By nature, cyber conflicts are an international issue that span across nation-state borders. By the end of the course, you will be able to apply the knowledge gained for analysis and management of international cyber incidents and conflicts including for activities such as development of policy related to cybercrime and cyberwarfare. Management of cyber incidents and conflicts requires an interdisciplinary perspective including an understanding of: 1) characteristics of the cyber threats and conflicts themselves, 2) international efforts to reduce and improve cyber security, and 3) psychological and sociopolitical factors.

Aug 3rd 2026
5-12 Weeks
Networks Cybercrime Computer Science
Details