Critical Thinking, Innovation, Research and Development, Commercialization
Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.
Organizations now have access to massive amounts of data and it’s influencing the way they operate. They are realizing in order to be successful they must leverage their data to make effective business decisions.
8-10 hours per week
Progress at your own speed
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To deliver a project successfully, it’s important to start by clearly identifying what the project is, and what its outcomes will be. In the course, we will show you practical ways to explore and understand your goals from the outset of your project, and to consider all the factors that may affect its execution. Step by step you will learn how to plan, scope, schedule, cost and manage your project from beginning to end. Since every project relies on the people who are delivering it, the course also enables you to explore how you can effectively communicate, manage people and employ leadership skills to successfully deliver your own project.
In Introduction to Project Management, you will learn practical ways to use project management skills, whether your project is large or small. Join us to explore how you can benefit from using project management techniques in your own projects.
In this course, you will further upskill through the application of the risk management canvas, which is a framework that enables you to manage risk within your own environment. It will immerse you in the concepts of risk management and help you to apply the key processes.
Practical activities through the course will allow you to apply the knowledge you learn as each week focuses on a key stage of the risk management process. The theories and practices taught in the course can easily be applied to any project, organization or business environment.
Risk Management for Projects is brought to you by the same team that developed the highly successful Introduction to Project Management MOOC, and builds on risk management for projects introduced in that course.
Participating in this course will ensure that you gain the know-how to reduce your project and organizational risk in the future.
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Section 1: The basics of working with big data
Understand the four V’s of Big Data (Volume, Velocity, and Variety); Build models for data; Understand the occurrence of rare events in random data.
Show More Understand characteristics of the web and social networks; Model social networks; Apply algorithms for community detection in networks. Section 3: Clustering big data Clustering social networks; Apply hierarchical clustering; Apply k-means clustering. Section 4: Google web search Understand the concept of PageRank; Implement the basic; PageRank algorithm for strongly connected graphs; Implement PageRank with taxation for graphs that are not strongly connected. Section 5: Parallel and distributed computing using MapReduce Understand the architecture for massive distributed and parallel computing; Apply MapReduce using Hadoop; Compute PageRank using MapReduce. Section 6: Computing similar documents in big data Measure importance of words in a collection of documents; Measure similarity of sets and documents; Apply local sensitivity hashing to compute similar documents. Section 7: Products frequently bought together in stores Understand the importance of frequent item sets; Design association rules; Implement the A-priori algorithm. Section 8: Movie and music recommendations Understand the differences of recommendation systems; Design content-based recommendation systems; Design collaborative filtering recommendation systems. Section 9: Google’s AdWordsTM System Understand the AdWords System; Analyse online algorithms in terms of competitive ratio; Use online matching to solve the AdWords problem. Section 10: Mining rapidly arriving data streams Understand types of queries for data streams; Analyse sampling methods for data streams; Count distinct elements in data streams; Filter data streams. Show Less
At a glance
About the instructors
Frank Neumann
Professor, School of Computer Science at University of Adelaide
About the instructors
Vahid Roostapour
PhD Student, School of Computer Science at University of Adelaide
Wanru (Kelly) Gao
Lecturer, School of Computer Science at University of Adelaide
Aneta Neumann
Postgraduate Researcher, School of Computer Science at University of Adelaide
Question: This course is self-paced, but is there a course end date?
Answer: Yes. The first course release started on May 15, 2017 and ends on December 1, 2018.
The new release of the course starts on December 1, 2018 and ends on December 1, 2020.
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine.
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Ways to take this course
Choose your path when you enroll
Price
Verified Track
$199 usd
Access to course materials
Unlimited
World Class institution and universities
edx suppport
Shareable certificate upon completion
Graded assignments and exams
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