Mandatory Professional Development Education

MPDE

Become industry certified and a member of the community after graduating. We help IT & non-IT professionals transition into the machine learning, cyber security, data science and artificial intelligence industry.

Mandatory Professional Development Education

Become industry certified and a member of the community after graduating. We help IT & non-IT professionals transition into the machine learning, cyber security, data science and artificial intelligence industry.

All organisations, roles and job functions are being impacted by information technology, at a faster pace and in more disruptive ways than ever before. Data is emerging from these changes as a new type of asset or resource that is required to achieve organisational goals, for corporate survival and competitive advantage. Every company and government needs access to data for advanced analytical decision-making, while at the same time addressing privacy and security related to its customers or citizens.

Professionals, companies and governments need to adapt to changing job requirements by developing coherent plans that address capability gaps. This is critical in order to ensure the future success of individual careers, companies and governments. Professionals now more than ever, require a focus on lifetime learning and a commitment to re-training for the industries of the future.

IDSA offers online courses that provide interested individuals with in-depth knowledge of various areas within data science, artificial intelligence and machine learning. The courses are available to members and non-members.

Data Analytics (DSDA)
Use appropriate data analytics and statistical techniques on available data to discover new relations and deliver insights into research problem or organizational processes and support decision-making.


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Data Science Engineering (DSENG)
Use engineering principles and modern computer technologies to research, design, implement new data analytics applications; develop experiments, processes, instruments, systems, infrastructures to support data handling during the whole data lifecycle.

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Data Management (DSDM)
Develop and implement data management strategy for data collection, storage, preservation, and availability for further processing.



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Research Methods and Project Management (DSRM)
Create new understandings and capabilities by using the scientific method (hypothesis, test/artefact, evaluation) or similar engineering methods to discover new approaches to create new knowledge and achieve research or organisational goals.

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Data Analytics (DSDA)
Use appropriate data analytics and statistical techniques on available data to discover new relations and deliver insights into research problem or organizational processes and support decision-making.



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Domain Related Competences (DSDK)
Use domain knowledge (scientific or business) to develop relevant data analytics applications; adopt general Data Science methods to domain specific data types and presentations, data and process models, organisational roles and relations.


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