Applied Social Network Analysis in Python
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Rating | 4.5★ based on 246 ratings |
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Length | 5 weeks |
Starts | Jul 10 (41 weeks ago) |
Cost | $79 |
From | University of Michigan via Coursera |
Instructors | Christopher Brooks, Kevyn Collins-Thompson, Daniel Romero, V. G. Vinod Vydiswaran |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Data Analysis Software Development |
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What people are saying
social network analysis
I learned many interesting new concepts in social network analysis and a bunch of new graph algorithms, which are rarely taught in the "traditional" algorithm course.
The problem is that the course is not called "Applied Graph Analysis in Python" but "Applied Social Network Analysis in Python".
4) More time should have been spent on prediction and other advanced topics, at least another week to bring the "Applied" into "Applied Social Network Analysis.
very good introductory course for social network analysis using Python.
The instructor was very clear in what he presented, and gave a good overview of Social Network Analysis.
老师讲解的非常好 , 逻辑清楚,条理明晰。建议编程作业稍微有点难度。所以扣掉一颗星。 希望越来越好。 Nice overview of general graph theory, and some useful exercises on how it can be applied for social network analysis.
the very best course it is very helpful and useful Excellent Good starting point for those who want ro learn social network analysis.
One of the best courses on social network analysis.
I found it hard sometimes to understand the concepts but this gave me quite an introduction on social network analysis and encouraged me to learn more about them.
ok Good Course This course is a excellent introduction to social network analysis.
Great hands on learning experience to social network analysis in Python Very challenging and comprehensive course, also directly applicable to machine learning problems, as an example, the last assignment applies network knowledge to extract features and exploit them in predictive modelling problems A very interesting course, beyond my expectation.
The Course Deserves 5 Stars BUTThe fundamental flaw that felt absent in the last two courses of the specialisation was the in lecture Jupyter Notebook Demonstrations, it really helped the students feel in sync with the mentors.Please correct the same all the 5 courses of this specialisation deserve 5 starts :) Very good insights into social network analysis.
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machine learning
Weekly quizzes check your understanding of the concepts and the assignments let you apply the material on practical examples, from basic network properties to link prediction using machine learning.
It was fun to see how you could connect the graph theoretical components to the machine learning concepts from earlier courses.
The last assignment required machine learning, which was not taught in this course.
Thanks!The cherry on top was to apply machine learning techniques to predict how the net evolves.
Final programming assignment was very easy, you can re-use the code written in the final assignment of Machine Learning course in this specialisation (but that does not mean it's a bad thing).
The machine learning connection could have been mentioned earlier in the course Very helpful, I didn't know anything about graphs, networks modelling and the NetworkX package before this course.
Anyone learning Machine Learning and AI should definitely take this course.
Brought together several machine learning and python skills that I learned in the previous courses.
Very new on this topic and very interesting It was a wonderful course, linked network's models and machine learning.
I was really satisfied from the last week assignment when I had to work with real-life example plus machine learning classifier.
Especially, the assignment of week 4 is too good, that give me an overview of how we can apply machine learning in network analysis.
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introduction to network
Extremely good introduction to network analysis.
A great introduction to network analysis.
It provides a brief but comprehensive introduction to network analysis.
This class was an excellent introduction to network analysis, where concepts, metrics and purpose of application where provided in a clear and digestible manners.
A bit intense, bu rewarding Great class for an introduction to networks.I didn't give it 5 stars because it didn't give me enough information to apply the concepts learned to real life projects.
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last assignment
Moreover, I spent most of the time (particularly in the last assignment) trying to deal with the autograder.
The last assignment is very practical and challenging.
The last assignment was challenging enough to bring the entire specialization to to satisfying close.
The last assignment was specially fun.
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other courses
Great lecturer, comprehensive material and unlike other courses in this specialisation, actually prepares you well for the assignments and quizzes.
I think my appreciation for this course is intensified by the irritation with other courses.
The assignments were not as difficult as in other courses of the specialization, and very helpful to understand the contents.
This course was very interesting and well taught, finally after all other courses I have managed to complete the assignments for this one in the recommended amount of time.
Personally I thought it was pitched at just the right level because the ML work is just enough to have to go through the process, without any complicated feature optimisation.Only wish the other courses worked as well as this one.
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final assignment
The final assignment worth to put all together with the skills learned in the other 4 courses of the specialization.
Then the fourth and final assignment is an interesting application of what you've learned but the grader is a NIGHTMARE.
I particularly liked the final assignment.
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Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Analysis Coordinator $65k
discharge analysis $68k
Operation Analysis $73k
Security Analysis $84k
Data Scientist (Social Network Analysis) $84k
Process Analysis $84k
IT Analysis $95k
Analysis $95k
Analysis Engineer 1 $103k
Business Analysis/Business Systems Analysis $120k
Senior Network Analysis Manager $148k
Vice Assistant President Network Analysis $190k
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Rating | 4.5★ based on 246 ratings |
---|---|
Length | 5 weeks |
Starts | Jul 10 (41 weeks ago) |
Cost | $79 |
From | University of Michigan via Coursera |
Instructors | Christopher Brooks, Kevyn Collins-Thompson, Daniel Romero, V. G. Vinod Vydiswaran |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Data Analysis Software Development |
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