Course Description
Programming for Big Data Part I
Digital Skills Academy
The course on Programming for Big Data enables participants to analyse different languages to tackle Big Data projects and solve any emerging issues in a professional and creative manner. The course addresses Programming for Big Data by providing participants with an understanding of Big Data fundamentals and gaining technical proficiency in Python, Hadoop and R as Big Data tools.
Participants will explore the Big Data environment including storage, modern databases and data warehousing. Based on the skills gained in the Data Science course, they will develop a greater understanding of typical Big Data analysis including graph and image processing, text analytics and various supervised and unsupervised predictive methodologies. Additional topics that will be covered include data visualisation and Ethics.
This course is for participants looking to gain a range of advanced skills to structure and implement programming languages for Big Data tasks and solve basic Programming for Big Data problems. This delivers particular benefits for organisations that are looking to expand data analysis skills amongst their existing talent pool. While upskilling is a vital enabler of recognition and retention for critical staff, developing Programming for Big Data talent enables firms to approach digital projects more effectively.
College Name | Digital Skills Academy |
Course Category | Business, Data Analytics |
Course Type | Online Learning |
Course Location | Dublin, UK |
Location Postcode | Dublin 8 |
Course Start Date | 9th April 2018 |
Course End Date | 4th May 2018 |
Course Fee | POA |
Course Duration | 4 weeks plus final assessment |
Entry Requirements | Participants must have successfully completed the "Data Science" Online Short Course. As part of our application process, participants will take a simple, online suitability assessment for their chosen course. Based on their answers, this will confirm that participants have the skills and experience required for a successful outcome. |