Predictive Analytics and Machine Learning
Machine learning concerns the study and application of algorithms and statistics in order to get machines to solve new problems that haven’t previously occurred, and then to ‘learn’ these problems and solve them in the future, should they return.
On this module, learners can expect an overview of the mathematical foundations of machine learning and its workflow. You will also learn about predictive analysis as this is the basis of machine learning.
You will learn by completing technical exercises and collaborating with fellow students on projects.
Key Facts
- Module from the Postgraduate Certificate in Data Science
- Accreditation: CPD - Continuing Professional Development
- Duration: 10 weeks, 1 evening class per week
- Mode of Study: Live evening online classes
- Intake Dates: 15 September
- Tuition Fees: £990
(Flexible payment plans and group discounts available)
Module Contents
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Differences between Data Science, Artificial Intelligence, Machine Learning, Deep Learning
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Types of machine learning
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ML lifecycle and design (obtain – clean – train – score – predict)
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ML Mathematical and statistical method overview: regression, k-means, trees and forests
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Python notebooks and libraries
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Two-class classification
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Multi-class classification
Key Benefits:
- Comprehend fundamental ML concepts: how data can reveal patterns, correlations, associations and, eventually, predictions
- Know the different types of ML, where each is applicable and their capabilities and limitations
- Grasp mathematical concepts from statistics that are closely related to machine learning
- ML in practice: code and evaluate algorithms
- Understand the design of a machine learning project, why this can optimise performance and increase business competitiveness. Identify cases where ML has offered automation and better decisions
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General mathematical background. Notions of statistics, probabilities and algebra.
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Basic understanding of computations Optional: familiarity with coding (python or R) Optional: Professional experience in management, finance, IT or other
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Fluency in English
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Personal Computer with minimum:
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Intel Atom® processor or Intel® Core™ i3 processor
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1GB RAM
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4GB Disk space
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Operating systems: Windows* 7, macOS, Linux
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*This course is planned to run in September. However, it is subject to student demand. For more information, speak to one of our advisors on: +44 (0) 20 3435 4644.
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LSBF Executive Education:
+44 (0) 20 3435 4644