Data Science and Machine Learning are rapidly growing fields that use scientific methods and processes to extract useful knowledge and insights from data. In this course, Mining Data from Networks, you will learn foundational knowledge of solving real world data science problems. First, you will learn the basics of implementing network analysis including understanding and visualizing network data. Next, you will discover how to define and identify important network data using NetworkX and Python. Finally, you will explore understanding and implementing link prediction and collaborative filtering systems. When you’re finished with this course, you will have the skills and knowledge of NetworkX needed to solve data science and machine learning problems.
Author Name: Justin Flett
Author Description:
Justin Flett is a Mechatronics Engineer currently working as a Professor within the Faculty of Applied Science and Technology at Sheridan College. Justin has previously held positions at Hydro One Networks, Ford Motor Company, and ABB Robotics spanning across both the electrical and mechanical engineering industries. Most recently, he has been working as an Product Development Professional specializing in training, services, and consultation nation-wide, ranging from design fundamentals to adva… more

Table of Contents

• Course Overview
  1min
• Understanding Networks
  18mins
• Visualizing Network Data
  22mins
• Defining and Identifying Network Data
  32mins
• Implementing Link Prediction Models for Network Analysis
  17mins
• Implementing Collaborative Filtering Models for Network Analysis
  15mins