Data Science Solution Implementation Course

About This Course

Data scientists are generally trained in algorithms and modelling skills. In today’s context, the expectation of the industry of the data scientists have far expanded beyond the scope of just creating models for prediction, optimisation, recommendation, etc. Data scientist are expected to be able to deploy such models or work with other teams within the organisation to implement Data Science and Artificial Intelligence (DSAI) models in real production environment. Desktop research on the various published job requirements of data scientists by global technology giants, SMEs, starts-ups, etc., revealed the need for solution implementation related skillsets, such as Continuous Integration/Continuous Development (CI/CD), Cloud Solutions implementation, etc. Appendix A provides the details of such job role requirements of various companies.

In addition to technical skills, Data Scientists are also required to report and present to the management and various business stakeholders who often are not familiar with Data Science theory and technical jargons. So as to ensure that the Data Science solutions are appropriately appreciated and adopted, it is of utmost importance that the Data Scientists are equipped with effective communication skills to enable effective key stakeholder engagement and buy-in.

This course is targeted at individuals who develop Data Science and Artificial Intelligence (DSAI) models and are looking to gain some hands-on knowledge of how to deploy such models. The course is also suitable for leaders of DSAI teams who want to be aware of what is required in a DSAI model deployment. As DSAI models can be used in almost all sectors, the audience can be diverse such as, data scientists, and data analysts, who are from any industry such as finance, healthcare and logistics etc.

Over a duration of four (4) days (26 hours) this course will provide attendees with a practical understanding of how to implement and deploy DSAI models in real world environment and also equip them with some effective communication skills.

The projected number of course participants over two years is 150. The participants may come from full time M.Tech students, part time M.Tech students or public attendees.