Home Specialist skills Artificial Intelligence Introduction to Data Science for Data Professionals
Introduction to Data Science for Data Professionals
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Compare commonly used Data Science tools through practical activities in R and Python
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Create a simple Machine Learning model using a no-code drag and drop tool
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Develop ideas for Data Science projects
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Explain the importance of Data Governance in Machine Learning and AI systems
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Follow a typical Data Science project lifecycle to provide AI models
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Explore and visualize data for analysis
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Report AI and Machine Learning models to facilitate governance oversight.
Overview
Off the shelf (OTS)
This three day course is aimed at those who are familiar with the essentials when working with data and are interested in learning about how Data Science, Analytics, Machine Learning, and Artificial Intelligence (AI) can be used to yield value from data assets.
This course will be of interest if you are interested in developing your own skills to move from analytics to Data Science, or if you are supporting organisational digital change, or if you are working with Data Scientists and want to learn more about what’s possible.
You will be introduced to key concepts and tools for use in Data Science, including typical Data Science Project lifecycles, potential applications & project pitfalls, relevant aspects of data governance and ethics, roles and responsibilities, Machine Learning and AI model development, exploratory analysis and visualisation and strategies for working with Big Data.
Throughout the course you will engage with activities and discussions with one of our Data Science technical specialists. Two of the course modules will allow you to complete ‘low or no’-code practical labs in order to test and compare the capabilities of Python and R, and to see a Machine Learning or AI workflow using Orange – giving you enough to start some ideas flowing and try things in your workplace or continue learning on one of our technical training routes into Data Science, Machine Learning, and AI with a firm grounding in key Data Science concepts.
Delivery method
Face to face
Virtual
Course duration
21 hours
Competency level
Working

Delivery method
-
Face to face
-
Virtual
Course duration
21 hours
Competency level
-
Working
