Hands On Training

Intermediate Network Analysis in Python

DataCamp

(3)

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

DataCamp's Introduction to Network Analysis With Python is completed and you want to learn more advanced techniques to analyze social, transport, and biological networks. This course is for you! This course will allow you to increase your network analytics skills and knowledge. This course will teach you how to use inverse and bipartite graphs to analyze changing time series within networks. Data Science is all about graph projections. Learn how to store and load graph data from files. The final chapter will consolidate all of this knowledge. This chapter will teach you how to analyze forum data and become a Pythonista Network Analysis Ninja.

Highlights

Hands on training

Top 10 Percentile

Rating & Reviews

Top 30 Percentile

Pedagogy

Top 30 Percentile

Parameters

Pedagogy

Acquire all major Python Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Hands on training

This course stands out as one of the top 10 percentile options in Python Programming, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training as well as essential Case Based Learning and Virtual Labs, this course is tailored to meet diverse educational needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in Python Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming.

Course Overview

Virtual Labs

International Faculty

Case Based Learning

Post Course Interactions

Case Studies,Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Network Analysis in Python

What You Will Learn

Herein, you'll build on your knowledge and skills to tackle more advanced problems in network analytics!

You'll gain the conceptual and practical skills to analyze evolving time series of networks, learn about bipartite graphs, and how to use bipartite graphs in product recommendation systems

You'll also learn about graph projections, why they're so useful in Data Science, and figure out the best ways to store and load graph data from files

You'll consolidate all of this knowledge in a final chapter case study, in which you'll analyze a forum dataset and come out of this course a Pythonista Network Analyst ninja!

Course Content

Expand all sections

Module 1: Bipartite graphs product recommendation systems

Module 2: Graph projections

Module 3: Comparing graphs time-dynamic graphs

Module 4: Tying it up!

Course Instructors

Eric Ma

Data Carpentry instructor and author of nxviz package

Eric uses code to solve big biological data problems at MIT. His tools of choice are: deep learning, network analysis, non-parametric and Bayesian statistics. He has domain expertise in the life scie...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%