We may earn an affiliate commission when you visit our partners.
Course image
Kevin Cardwell

This dynamic 4-hour course is designed to demystify the complexities of data communication networks. It provides a comprehensive walkthrough of the concepts, structures, and mechanisms that enable digital communication across different platforms and devices. This course will help you understand what is taking place each and every time you use your computer, phone or device!

Read more

This dynamic 4-hour course is designed to demystify the complexities of data communication networks. It provides a comprehensive walkthrough of the concepts, structures, and mechanisms that enable digital communication across different platforms and devices. This course will help you understand what is taking place each and every time you use your computer, phone or device!

This course is ideal for IT professionals, network administrators, and anyone looking to deepen their understanding of data communication networks. With content tailored for those who have foundational knowledge in IT and are eager to advance their networking skills.

Participants should have a basic understanding of IT, computer operations, and foundational networking concepts. This background will help in grasping the advanced topics covered in the course.

After completing this course, learners will be able to identify the various components and their roles within a data communication network. They will distinguish among the major types of network topologies and assess the functions of key network protocols. Additionally, learners will formulate basic strategies for securing a data network, equipping them with essential skills for network management and security.

Enroll now

What's inside

Syllabus

Understanding the Network Landscape
Module 1 provides an essential overview of data networking, examining the core components, topological structures, protocols, and fundamental network security concepts. Through a series of informative videos, learners will gain a foundational understanding of how modern communication systems are built and secured.
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores core data networking concepts, structures, and mechanisms standard in the IT industry
Develops foundational networking knowledge and skills for IT professionals and network administrators
Enhances understanding for those with foundational IT and networking knowledge
Taught by Kevin Cardwell, an experienced and recognized instructor in the field of data communications
Requires some foundational knowledge in IT and computer operations, which may not be suitable for complete beginners

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Comprehensive data networking overview for professionals

According to students, this course provides a solid theoretical foundation and a comprehensive overview of data communication networks, suitable for IT professionals and those with a basic IT background. Learners commend the instructor's clear explanations and the course's ability to demystify complex concepts. While appreciated for its concise nature and coverage of emerging technologies, some find the pace challenging, especially in advanced modules. A recurring point is the course's focus on theory, with several mentions of a lack of hands-on labs or practical application, making it more of an introduction than a deep-dive for skill development.
Highly relevant for IT professionals seeking an overview.
"I'm an IT professional, and this course served as an excellent refresher and introduced me to some newer concepts..."
"Perfect for busy professionals... It's concise and to the point."
"I would recommend this for someone with a basic IT background looking to refresh or expand."
Provides a broad, theoretical understanding of network concepts.
"This course is fantastic for anyone wanting a solid foundation in networking."
"Good for a general understanding. The early modules on fundamentals were great."
"This course provides a solid theoretical grounding. It covers a broad range of topics..."
Instructor's explanations make complex topics accessible.
"The instructor explains complex topics clearly, especially in Module 1."
"The instructor's clear delivery makes even complex topics accessible."
"Highly recommend for foundational knowledge. The instructor's explanations are superb."
Covers many topics quickly, leading to less depth in some areas.
"The course covers a lot of ground, almost too much for its duration. I found the pace a bit too fast..."
"The content on emerging technologies like IoT was a bit brief, but it's a short course so I wasn't expecting deep dives."
"I felt like it was trying to be too many things at once. I needed more foundational understanding before tackling Modules 2 and 4..."
Lacks practical exercises, labs, or real-world application.
"I was hoping for more hands-on examples or labs to solidify the concepts, especially concerning network configuration."
"Lacks practical application. While the theoretical concepts are explained, I felt there wasn't enough emphasis on how to actually apply these concepts..."
"It's quite theoretical. I'd say it's more for conceptual understanding than hands-on skill development."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Communication Networks with these activities:
Review concepts and foundations: Computer Networking: A Top-Down Approach
Review the fundamental principles and concepts of computer networking to strengthen your understanding before diving into the course material.
Show steps
  • Read and take notes on chapters 1 and 2
  • Complete the end-of-chapter exercises and review questions
  • Summarize the key concepts in a short written summary
Attend a workshop on advanced network protocols
Expand your knowledge by attending a workshop focused on advanced network protocols, gaining insights from experts and practical demonstrations.
Browse courses on Network Protocols
Show steps
  • Identify relevant workshops and register to attend
  • Actively participate in the workshop sessions
  • Take detailed notes and ask questions to enhance your understanding
  • Follow up on topics discussed after the workshop
Experiment with packet simulators
Enhance your understanding of network behavior and protocols by experimenting with packet simulators.
Browse courses on Packet Tracer
Show steps
  • Choose a packet simulator and install it
  • Create a simple network topology for testing
  • Send and capture packets to observe their behavior
Five other activities
Expand to see all activities and additional details
Show all eight activities
Test your skills by configuring networking scenarios in a virtual environment
Enhance your practical skills by configuring and testing network scenarios in a virtual environment, allowing you to experiment with real-world scenarios without risk.
Browse courses on Network Configuration
Show steps
  • Set up a virtual network environment using tools like VMware or GNS3
  • Configure routers and switches within the virtual network
  • Simulate network traffic and observe the behavior of network devices
  • Troubleshoot and resolve issues that arise during the configuration process
Engage in peer discussions on network design principles
Participate in peer discussions to exchange ideas and perspectives on network design principles, broadening your understanding and learning from the collective knowledge of the group.
Browse courses on Network Design
Show steps
  • Join a study group or online forum focused on network design
  • Share your ideas and participate in discussions on various network design topics
  • Collaborate on projects or case studies related to network design
Build a small-scale network from scratch
Gain hands-on experience by building and configuring a small-scale network, putting your knowledge into practice and reinforcing your understanding.
Browse courses on Network Architecture
Show steps
  • Gather the necessary hardware (routers, switches, cables)
  • Design the network topology and configuration settings
  • Assemble and connect the network components
  • Configure the network devices and test connectivity
  • Monitor the network and troubleshoot any issues that arise
Design and present a case study on network security
Apply your knowledge of network principles to present a case study that analyzes real-world network security challenges and solutions.
Browse courses on Network Security
Show steps
  • Choose an organization or scenario to use as a case study
  • Identify the network security challenges faced by the organization
  • Design a network security solution to address the identified challenges
  • Create a slide presentation or report outlining your case study
  • Present your case study to your classmates or colleagues
Volunteer as a mentor for junior IT professionals or students
Strengthen your understanding while giving back by mentoring others, sharing your knowledge and providing guidance.
Show steps
  • Identify opportunities to mentor through organizations or educational institutions
  • Connect with mentees and provide support in their networking journey
  • Share your experiences, knowledge, and best practices

Career center

Learners who complete Data Communication Networks will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Communication Networks.
The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.
The premier applied machine learning masterwork, taking practitioners through intuitive concept breakdowns, production-grade Scikit-Learn workflows, and deep neural architecture implementations.
A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.
A timeless mathematical masterpiece that provides an uncompromising Bayesian and probabilistic foundation for linear classifiers, graphical models, kernel methods, and sampling algorithms.
Bridging constrained sensor nodes, industrial gateways, and cloud backends, Perry Lea provides a comprehensive architectural blueprint for edge computing systems. Chapters cover fog topology design, Kubernetes at the edge (K3s/KubeEdge), hardware accelerators, and low-latency stream analytics.
Is widely regarded as a foundational text in computer networking, offering a comprehensive top-down approach starting from the application layer. It's excellent for gaining a broad understanding of networking principles, which are essential for network management. It is commonly used as a textbook in academic institutions for both undergraduate and graduate programs. The book provides a solid foundation without requiring extensive prior knowledge of programming or mathematics.
The definitive mathematical and theoretical canon of statistical learning, establishing the rigorous analytical foundations of regularized regression, tree ensembles, and high-dimensional inference.
Running machine learning inference directly on milliwatt microcontrollers eliminates network round-trip latency and preserves user privacy at the extreme edge. Pete Warden and Daniel Situnayake demonstrate how to quantize, deploy, and optimize TensorFlow Lite models on embedded sensors.
A distilled practitioner field guide outlining best practices for the entire machine learning lifecycle, from problem formulation and feature engineering to model deployment and monitoring.
Ultra-reliable low-latency 5G networks and Multi-access Edge Computing (MEC) form the backbone of autonomous vehicles, smart cities, and mobile AR. Mengwei Xu, Xiao Ma, and Qing Li analyze task offloading, edge container orchestration, and video analytics across cellular edge nodes.
Coauthored by Edge Impulse founders Daniel Situnayake and Jenny Plunkett, this engineering guide walks through the full lifecycle of deploying embedded AI on edge devices. Readers master sensor dataset curation, digital signal processing, model compression, and fleet monitoring in production.
Delivers an end-to-end systems architecture guide for building reliable production ML systems, addressing data engineering trade-offs, real-time feature computation, and model drift mitigation.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern foundation models.
Distributing compute nodes outside physically hardened data centers exposes edge infrastructure to side-channel tampering, rogue gateways, and DDoS amplification. Mohiuddin Ahmed and Paul Haskell-Dowland detail zero-trust authentication, intrusion detection, and lightweight cryptography for edge deployments.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment workflows.
Bridges linear algebra, multivariable calculus, vector geometry, and probability directly to fundamental machine learning algorithms like PCA, Gaussian mixture models, and support vector machines.
Extending cloud workloads closer to end users demands seamless orchestration across AWS Wavelength, Local Zones, Outposts, and IoT Greengrass. Sean Howard walks engineers through designing resilient hybrid edge topologies, securing disconnected device fleets, and optimizing telemetry pipelines.
A classic in the field, this book focuses specifically on the process of designing networks from a systems analysis perspective. It emphasizes aligning network design with business goals and provides a practical methodology. While the latest edition is from 2010, the principles of top-down design remain highly relevant for professionals.
Provides a broad and unified survey of modern networking technologies, including SDN and NFV, which are central to network virtualization. It covers the concepts, architecture, and applications of these technologies. It is an excellent starting point for gaining a broad understanding and is often used as a textbook in academic settings.
A more in-depth exploration than 'Network Security Essentials,' this book delves into the theory and practice of cryptography and network security. It covers a wide range of topics, from encryption algorithms to network security applications. comprehensive resource often used as a textbook for undergraduate and graduate-level courses.
Instructs data scientists on applied model evaluation, cross-validation, hyperparameter tuning, and pipeline construction through Scikit-Learn maintainers Andreas Müller and Sarah Guido.
Deploying autonomous AI agents across hybrid cloud and edge environments requires orchestrating small language models locally while delegating complex reasoning to cloud clusters. Brian Pitman explores latency-aware routing, edge inference optimization, and resilient multi-agent coordination.
Provides a balance of theoretical and practical aspects of network management. It covers the background, technologies, and tools necessary for network managers. It is suitable for both academic study and as a reference for practitioners looking to deepen their understanding of network management concepts and protocols like SNMP.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, demonstrating how to fine-tune, optimize, and deploy attention architectures across diverse natural language processing and understanding tasks.
Edited by distributed systems pioneer Rajkumar Buyya and Satish Narayana Srirama, this foundational volume establishes the taxonomy, resource scheduling algorithms, and storage hierarchies of fog and edge computing. Case studies evaluate smart healthcare, connected transit, and tactile internet testbeds.
Python key language for network automation. focuses on using Python for network automation, programmability, and DevOps. It's an excellent resource for network engineers and managers looking to develop scripting and automation skills, which are increasingly vital for efficient network management in contemporary environments.
Delivers battle-tested operational patterns for serving foundation models, addressing GPU cluster throughput, semantic caching, automated evaluation benchmarks, and continuous latency minimization.
Focusing specifically on network virtualization, this book provides a foundational understanding of the concepts and technologies involved. It is suitable for readers who want to build a solid base in network virtualization before exploring more advanced topics or specific vendor implementations.
Specifically addresses the modern approach to enterprise network management through automation. It outlines the tools, technologies, and processes required for network automation, making it highly relevant for those focusing on contemporary network management practices and the integration of DevOps principles.
Investigates the engineering realities of running automated ML pipelines in production, addressing data drift detection, automated retraining loops, telemetry infrastructure, and continuous validation.
Practical guide to building and operating a network security monitoring (NSM) capability. It covers data collection, detection techniques, and analysis. It's an essential resource for security analysts and anyone responsible for monitoring network traffic for malicious activity.
Orchestrating containerized microservices on resource-constrained edge gateways requires lightweight Kubernetes distributions with minimal memory overhead. Karthikeyan Shanmugam demonstrates how to deploy, secure, and scale production MicroK8s clusters across ARM IoT devices using Kubeflow and telemetry add-ons.
Offers a practical introduction to penetration testing and ethical hacking. It guides readers through the process of identifying and exploiting vulnerabilities in networks and systems. It hands-on guide suitable for those interested in offensive security and understanding how attackers operate.
Details cloud-native DevOps architectures for orchestrating automated machine learning lifecycles, integrating CI/CD triggers, model registry synchronization, and automated hyperparameter sweep workers.
Details an applied architectural methodology for running high-performance open-weights models on local workstations, tackling quantization fidelity, memory bandwidth limits, and prompt assembly trade-offs.
Serves as a beginner's guide to automating network tasks using tools like Python and Ansible. It's highly relevant for those looking to implement automation in their network management practices, a key contemporary topic. It provides practical examples and recipes for automating network devices.
Bringing deep neural networks onto constrained field hardware hinges on balancing model accuracy against strict power, memory, and thermal budgets. Pethuru Ray surveys federated edge learning, vision accelerators, and industrial automation case studies across smart manufacturing and healthcare.
Offers a rigorous theoretical foundation for reasoning under uncertainty, combining graph theory and probability distributions to model complex high-dimensional dependencies across autonomous intelligent systems.
This highly detailed and classic reference for understanding the TCP/IP protocol suite in depth. It uses examples and analysis of live network traffic to explain how protocols work. While dense, it's an invaluable resource for anyone needing a deep technical understanding of network communication.
Covering hardware platforms, virtualization layers, and edge-to-cloud middleware, K. Anitha Kumari, G. Sudha Sadasivam, and D. Dharani offer a structured introduction to edge computing fundamentals. Readers examine container offloading, latency modeling, and smart-grid deployment architectures.
Based on real bug bounty reports, this book offers practical insights into finding vulnerabilities in web applications. It's a valuable resource for aspiring bug bounty hunters and those interested in learning about common web security flaws through real-world examples.
Provides a comprehensive overview of the networking technologies and protocols used in IoT. It explores the different types of IoT networks, and discusses the challenges and opportunities in designing and deploying IoT networks.
Processing sensitive video, biometric, and location telemetry on local edge servers reduces raw data exposure but introduces differential privacy and federated learning challenges. Bruce Gu, Longxiang Gao, and Tom H. Luan formulate mathematical privacy guarantees for multi-tenant edge networks.
A deep understanding of TCP/IP is fundamental to network management. provides a comprehensive and accessible explanation of the TCP/IP protocol suite. It's an excellent resource for students and professionals who need to solidify their understanding of how networks communicate at a foundational level. It can serve as a valuable reference.
Takes a problem-solving approach to understanding networking, which can significantly deepen a reader's understanding of why networks are designed the way they are. It's valuable for those who want to move beyond theoretical concepts and understand the practical challenges and solutions in networking, which is highly relevant to effective network management.
Introduces core computational linguistics concepts and practical tokenization, tagging, and syntactic parsing workflows through clear Python examples, establishing strong fundamentals for language analysis.
Offers practical, real-world networking knowledge that goes beyond entry-level certifications. It covers a wide range of topics relevant to network design and operations from a hands-on perspective. It's a valuable resource for both students and professionals looking to bridge the gap between theory and practice.
Focusing on the critical aspect of routing design, this book delves into advanced concepts and best practices for creating efficient and scalable routing solutions. It's considered a more advanced text, often recommended for those pursuing expert-level certifications like the CCDE.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Data Communication Networks.

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner
Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections
14-day refund window on annual Coursera Plus and single courses
7-day free trial on monthly Coursera Plus subscriptions
Free course audit option for lectures and readings
Verified certificates from top universities & companies
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser