Big Data has grown unprecedentedly rapidly with the spread of cloud infrastructure, in less than a decade. Big Data today has helped organisations who adopted a Big Data strategy to be at the forefront of research and development. This course aims to help to develop strategies to better leverage Big Data in today’s data-driven economy. This course refers to a wide range of techniques to address Big Data’s challenges with the aim to pave the way to more new opportunities. The course’s overall objective is to help in the application of different techniques and tools to address Big Data challenges and to scale Big Data Analytics with originality.
The course is intended for Data Engineers working on data integration and data preparation including ETL processes, Data Scientists working on scaling Big Data analytics, Researchers working on Big Data Discovery, Policy makers working on Big Data to address today’s challenges across sectors and all people who would like to learn different techniques to address Big Data challenges today to become new Big Data savvy professionals.
What am I going to get from this course?
At the end of this course attendees will be able to develop pertinent strategies to better leverage Big Data. They will be able to understand thoroughly and intuitively the new opportunities and the new challenges of Big Data. Learn the much-needed new skills to address these challenges spanning data integration, data preparation and analytics, including the emerging analytics. Implement different techniques and tools using one of the most powerful integrated programming environments (IDE) combing R and Spark that will help to integrate, prepare and analyze Big Data.
Prerequisites and Target Audience
What will students need to know or do before starting this course?
The following could help, but they are not totally a prerequisite for this course.
- Knowledge of relational database management systems (RDBMS) and/or SQL (Structured Query Language) or NoSQL (Not only SQL),
- Concepts and notions of algebra (inverse problems) and probability,
- Some familiarity with the development of algorithms and coding (Matlab or R).
Who should take this course? Who should not?
This course is intended for people working on Big Data across sectors and for people who are willing to become Big Data savvy professionals. It specifically designed for :
- Data Engineers working on data integration and data preparation including ETL/ELT (Extract, Transform and Load or Extract, Load and Transform) processes,
- Data Scientists working on scaling Big Data Processing and Big Data Analytics and developing Machine Learning (ML or AI) applications,
- Researchers and Scientists working on Big Data for Discovery (drug or gene discovery) or for testing new algorithms,
- Policy makers working on Big Data to address today’s challenges across sectors including education,
- People who would like to learn different techniques to address Big Data challenges spanning data integration, data preparation and data analytics, including emerging analytics.