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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Networks Illustrated: principles Without Calculus course is offered by Princeton University and is taught by two top educators with a background of Electrical Engineering. This is a beginner-level programme and takes approximately 24 hours to complete. This course has around 12 modules, with extensive videos and quizzes. Besides, you will get practice assignments and exercises within the curriculum.
The Online Networks Illustrated: Principles Without Calculus Programme by Coursera explores answers using simple language and addresses fundamental questions about the social and technical network systems by summarising theories. The course proceeds with illustrations, anecdotes and analogies and mathematics as elementary as addition and multiplication.
Coursera’s Networks Illustrated: Principles Without Calculus, is a course which explores the theories behind the social and technical connections. Networking Courses usually involve a lot of mathematical details for better understanding of the algorithms and systems behind the social and technological networks. However, to fully understand networking, you need to look more into the main ideas behind how the networking systems function.
The Highlights
Full online learning
Self-paced training
Beginner level course
Readings and practise exercises
Flexible deadlines
Free course
Subtitles in English
Programme Offerings
- Complete Online Course
- Extensive Video Lectures
- quizzes
- Exercises With Problem Sets
- Flexible Deadlines
- Free Of Cost
- Practice Exercises
Courses and Certificate Fees
| Certificate Availability |
|---|
| no |
The Networks Illustrated: Principles without Calculus by Coursera is free of cost programme. The entire curriculum is available for free. However, no certificate will be provided upon course completion.
Eligibility Criteria
The Networks Illustrated: Principles without Calculus by Coursera does not offer any certificate. You can access the entire course, free of cost.
What you will learn
After completing the course, Networks Illustrated: Principles Without Calculus, the students will have enough knowledge about:
Communicating effectively without disrupting other’s calls or messages or Internet usage
Investigate Wifi and understand how Wifi relies on “random access” methods to manage interference
Algorithms used in Google, Amazon, Netflix and YouTube
How to spread influence via social media networks like Facebook and Twitter
How to Control congestion on the Internet and Routing Traffic through the internet
Who it is for
Admission Details
To enrol for the Networks Illustrated: Principles without Calculus course:
1. Go to the course URL.
2. Select the “Enrol for Free” option.
3. Create an account on Coursera. If you don’t have a Coursera account, log in via Google, Facebook or Apple account.
4. As the course is free of cost, all the course material will be available to you from the get-go.
Application Details
You need not fill an application form to enrol in the Coursera Networks Illustrated: Principles without Calculus Training. You can simply join the course and access all the study material for free by signing up with your Google, Facebook, Coursera, or Apple account.
The Syllabus
Sharing and ranking is hard
Networking principles without “Calculus”
Crowds may or may not be wise
Network is expensive
End to End and Bigger and Bigger
Divide and conquer
Multiple Access
Mobile Penetration
FDMA
Attenuation
OG
Cells and 1G
TDMA
2G
CDMA
Cocktail Party Analogy
SIR
Near-far Problem
DPC
CDMA & 3G
Negative Feedback
DPC Computation: Part A
DPC Computation: Part B
Distributed Computation
Convergence
Handoffs
Summary
Traffic Analogy
Unlicensed Spectrum
Wifi Standards
Accessing Wifi
Wifi Deployment
Interference
CSMA vs ALOHA
Random Access Protocols
ALOHA Scalability
Controlled vs Random Access
ALOHA
ALOHA Successful Transmission
CSMA Carrier Sensing
ALOHA Throughput
CSMA Backoff
Summary
Search Engines
New Word in the Dictionary
Web graphs
Dangling Notes and Disconnected Graph
The “Random Surfer”
In-degree
Importance Equations
PageRank Example Summary
Robust Ranking
PageRank Example Calculation
Summary
Amazon and eCommerce
The Wisdom of Crowds
Average Ratings
Rating Aggregation Challenges
Bayesian Ranking: Part I
Naïve Averaging
Bayesian Ranking: Part II
What does Amazon do?
Bayesian Ranking Practice
Summary
Video Streaming
Netflix Timeline
Netflix Recommendation System
Recommendation is Everywhere
Performance of Different Methods
Netflix Prize and Logistics
Our Example
User-Movie Interactions
Neighbourhood Predictor
Raw Average
Baseline Predictor
Cosine Similarity
Similarity
Similarity Values
Leveraging Similarity
Summary
Copy of Cosine Similarity
Viral Style and Video Recommendation
YouTube Timeline
Viral
Information cascade & Sequential Decision making
Popularity
Guessers
Analysing Cascades
Considerations
Number-guessing Thought-Experiment
Emperor’s New Clothes
Summary
Social Graph
Marketing Strategies
Facebook and Twitter
Closeness Centrality
Degree Centrality
Cluster Density
Betweenness Centrality
Summary
Demand for Data
Our Mobile Data Plans
Jobs’ Inequality of Capacity
Net Utility
Comparing Pricing Schemes
Usage-based points
Utility
Flat rate creates waste
Demand Curve
Demand
The tragedy of the Commons
Summary
NSFNET
ARPANET
Internet
Resource Pooling
Statistical Multiplexing
Circuit vs Packet Switching
Routing Traffic
Distributed Hierarchy
IP Address
Shortest-Path Problem
Forwarding
Example: Three Hops
Cost Updates
DHCP and NAT
Example: Two Hops
Routing Protocols
Prefix and Host Identifier
Bellman-Ford Example
RIP and Message Passing
Example: Summary
Summary
Layered Protocol Stack
Divide and Conquer
Headers
Transport & Network Layers
Processing Layers
Distributed Congestion Control
Traffic Jam & Bucket Analogy
Controlling Congestion
End Hosts
Cautious Growth of Window Size
Sliding Window
Inferring Congestion
Loss-Based Congestion Interference
Congestion Control Versions
Delay-Based Congestion Interference
Summary
Milgram’s Experiment
“Small World” in Culture
Triad Closures and Homophily
Watts-Strogatz Model
Average Shortest Path
Structural vs Algorithmic Small Worlds
Random Graphs
Clustering Coefficient
Discovering Short Paths
Regular Graph
Watts-Dodds-Newman Model
Summary