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Overview
The Applied Social Network Analysis in Python course offered by Coursera in partnership with University of Michigan will introduce the learner to network analysis through tutorials using the NetworkX library.
The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks.
Key facts
- The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network.
- The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem.
- This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python.
What You Will Learn
- Represent and manipulate networked data using the NetworkX library
- Analyze the connectivity of a network
- Measure the importance or centrality of a node in a network
- Predict the evolution of networks over time
Skills you'll gain
- Graph Theory
- Python Programming
- Computer Programming
- Data Analysis
- Network Model
- Computer Networking
- Network Architecture
- Algorithms
Programme Structure
Courses included:
- Why Study Networks and Basics on NetworkX
- Network Connectivity
- Influence Measures and Network Centralization
- Network Evolution
Key information
Duration
- Part-time
- 21 days
- 10 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Computer Sciences Software Engineering Machine Learning View 330 other Short Courses in Software Engineering in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate level
- Some related experience required
Tuition Fees
Additional Details
Course is free for the first 7 days. After 7 days, the course can be accessed with the Coursera Plus Subscription
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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