Explore
Browse by Domains
Browse by Degrees
Popular Programs
PG Program in Artificial Intelligence and Machine Learning
6 Months Online Weekend
Applied Data Science Program
12 Weeks Live Virtual Weekdays & Weekend
No Code AI and Machine Learning: Building Data Science Solutions
12 Weeks Online Weekend
PG Program in Data Science and Business Analytics
MIT Data Science and Machine Learning Program
12 weeks Online Weekend
PG Program in Cloud Computing
6 months Online Weekend
Data Science & Business Analytics
Master of Data Science (Global) Program
24 Months Online
Data Analytics Essentials
15 week Online
MS in Data Science Programme
18 months Online
DP-100 - Microsoft Azure Data Scientist Associate Certification Training Program
8 Weeks Online
PL-300 - Microsoft Power BI Data Analyst Certification Training Program
6 Weeks Online
Artificial Intelligence & Machine Learning
PG Program in Artificial Intelligence for Leaders
4 Months Online Weekend
MS in Information Science: Machine Learning
2 Years Online/Hybrid
Generative AI for Business with Microsoft Azure Open AI Program
10 Weeks Online
Microsoft Programs
AZ-900 - Microsoft Azure Fundamentals Training Program
AZ-104 - Microsoft Azure Administrator Training Course
Management
Advanced Digital Marketing and Growth Strategies
12 Weeks Online
NUS Business School Future Leaders Programme
Executive PG Program in Management
12 months Online Weekend
PGP in Strategic Digital Marketing
Cloud Computing
Cyber Security
Post Graduate Program in Cyber Security
16 weeks Online
CompTIA Security+ Bootcamp
6 weeks Online
Software Development
Professional Certificate in Full Stack Software Development: Building Scalable Cloud Applications
6 Months Online
Digital Marketing
Design Thinking
Design Thinking: From Insights to Viability
14 Weeks Online Weekend
Post Graduate Program in User Experience Design
Study Abroad
2 Years Hybrid
MBA
Masters
Know more about
Data Science and Business Analytics
17 programs 48% avg. salary hike
AI & Machine Learning
12 programs 48% avg. salary hike
3 programs 48% avg. salary hike
4 programs 48% avg. salary hike
7 programs 48% avg. salary hike
2 programs 48% avg. salary hike
MBA Courses
1 programs 48% avg. salary hike
Study Abroad Programs
1 programs Earn about 150K USD (in US)
Study in US Programs
Quick Links
GL Excelerate
Get the desired career support
Webinar on Demand
Watch the on-demand webinars
What is your work experience?
This will help us recommend the best programs for you.
Currently in college
0-3 yrs experience
3-8 yrs experience
8+ yrs experience
College Students
Start your career on the right foot, with curated programs, job platforms, and postgraduate programs.
Gain skills in 3-12 months to accelerate career growth and land your first job
GL Live Sessions
Online sessions with industry experts
EXPLORE
Career Path
200+ in-demand careers
Learn for Free
An easy way to get started on your career path with us.
Academy
Get certified with 1000+ Free Courses
START FOR FREE
Distributed Systems teaching courses are designed to give learners an in-depth understanding of distributed systems' structure, components, and algorithms. Learners will learn distributed computing principles, like communication protocols, synchronization, replication, fault tolerance, databases, file systems, and networks. Learners will also study the design and implementation of these systems, tools, and techniques used to manage them. These are essential in software engineering and computer systems fields.
EXPLORE OUR COURSES
Learn the concepts of distributed systems with Great Learning's comprehensive course syllabus. Expand your skills in distributed computing.
LEARN MORE
Advanced Certification In Software Engineering
10 months · Online
We are allocating a suitable domain expert to help you out with program details. Expect to receive a call in the next 4 hours.
Distributed systems are systems using message forwarding to allow components spread over a network of computers to interact and coordinate their operations. Distributed systems allow sharing of resources, such as hardware, software, and data, among multiple computers, providing scalability and fault tolerance. Examples of distributed systems include cloud computing, content distribution networks, peer-to-peer networks, and distributed databases.
Networking in distributed systems is the process of connecting computers and other devices within a distributed system. This process allows for sharing of data, resources, and services across the network. It also provides communication between the devices and systems, enabling them to work together to achieve the desired system goals. Networking in distributed systems is a critical component for many distributed applications, as it enables them to access and process data from other devices and share resources and services.
Naming in distributed systems is the process by which resources in a distributed system are given names so that they can be referenced and located more easily. It allows for the efficient communication, organization, and management of resources in a distributed system. The goal of naming is to provide a consistent and intuitive way of referring to resources in a distributed system.
Synchronization in distributed systems is the process of coordinating the activities of distributed processes or programs so that they appear to be executed as a unit. It ensures that all parts of the distributed system are aligned and that the system is in a consistent and correct state. Synchronization is essential for systems that require multiple processes to work together to achieve a common goal.
Security in distributed systems is the practice of protecting resources, data, and information in a distributed computing environment. This includes protecting against malicious attacks, unauthorized access, data breaches, and other threats. Security is achieved through a combination of preventive measures, such as authentication, encryption, and access control, and detection and response measures, such as logging and monitoring.
Fault tolerance in distributed systems is the ability of the system to remain operational and continue functioning despite the occurrence of faults or errors within its components. Fault tolerance is achieved by building redundancy and redundancy into the system so that if one component fails, another can take over its functionality without affecting the overall system. This helps to ensure that the system continues to provide reliable service even if one of its parts malfunctions or fails.
Data replication in distributed systems is the process of storing multiple copies of data across different nodes within a network. It is used to ensure data availability and reliability in case of failures and outages and to provide faster access to data. It can also help improve performance and reduce latency since data can be retrieved from multiple nodes simultaneously.
Data consistency in distributed systems is a set of rules that ensures data remains consistent across all copies of the data in the system. All copies of the data must be identical and up to date, and any changes made to one copy must be reflected in all other copies. This ensures that the data is always consistent and reliable across the distributed system.
Resource sharing in distributed systems is the ability of computers in a distributed system to access and utilize the resources of other computers in the system. This includes hardware components, such as CPUs and memory, and software services, such as databases and web servers. Sharing resources can increase availability and performance, as multiple computers can cooperate to process requests.
Distributed systems are a network of independent computers that collaborate to achieve a common goal. They are commonly used when a single computer can't handle the required load or when data is spread across multiple locations.
Examples include cloud computing, distributed programming, peer-to-peer file sharing, and distributed databases
Distributed systems can be broadly categorized into two types:
Distributed systems are employed in multiple applications, including:
There are several benefits to learning distributed systems, including:
Distributed Systems job roles require the ability to design, develop, and maintain distributed systems, handle large-scale data processing, and work with cloud and virtualization technologies.
These roles establish the weight of solid programming, data management, and problem-solving abilities
The average salary for a Distributed Systems Engineer with professional skills is $91,175, and the hike ranges between 15-20% when transitioning into higher job designations within the organization. Working professionals can gain a hike by escalating their practical knowledge through the best Distributed Systems online course.
Distributed Systems module is learned in the Advanced Software Engineering course.
The key topics covered in the Distributed Systems online course syllabus are:
Prerequisites for learning Distributed Systems include the fundamental understanding in:
Great Learning offers Distributed Systems courses with an extensive syllabus covering topics like distributed system architecture, distributed commit protocols, and leader election. It provides practical experience through hands-on projects and offers guidance from experienced industry professionals.
Yes. Great Learning offers free Distributed System related courses on the Great Learning Academy platform.
Free Courses Include: Free Serverless Computing Course, Free Cloud Foundations Course, and What is IoT course?
Enter your registered email and we'll send you a link to change your password.