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Certificate of Achievement
has completed the following course:
Big Data: Statistical Inference and Machine Learning
Queensland University of Technology
The participant reviewed a range of methods, models and algorithms used for big data analytics. They had the opportunity to put their knowledge into practice when exploring three common problems in big data analytics: prediction, dimension reduction and clustering. They also applied the principles of decision making using regression tree approaches and gained valuable experience using the popular and emerging platforms – R, H2O Flow and Weka.
3 weeks, 2 hours per week
Professor Kerrie Mengersen
Deputy Director, ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)
Queensland University of Technology
Transcript
Learning outcomes
- Identify big data application areas
- Explore big data frameworks
- Model and analyse data by applying selected techniques
- Demonstrate an integrated approach to big data
- Develop an awareness of how to participate effectively in a team working with big data experts
Syllabus
- Introduction to the relationship between statistical inference and machine learning
- The application of methods from these areas to real world projects
- An overview of the most popular methods currently used in these fields.
- Machine learning methods used to undertake prediction and analysis of a given data set.
- Specific methods such as neural networks, decision trees, principal component analysis and clustering.
- The practical application of modern analysis tools such as R Studio and H2o.
Issued on 1st August 2017
The person named on this certificate has completed the activities in the transcript above. For more information about Certificates of Achievement and the effort required to become eligible, visit futurelearn.com/proof-of-learning/certificate-of-achievement.
This certificate represents proof of learning. It is not a formal qualification, degree, or part of a degree.