Big Data Science Certified Professional
This five-day classroom course will cover the five modules needed to obtain the Big Data Scientist certification from the Arcitura™ Big Data School. The course will cover the analysis practices and technology concepts and mechanisms that comprise and are featured in contemporary Big Data environments and tools. By completing this course and the certification exams, attendees will have demonstrated proficiency in specialised areas of Big Data practice and technology. The course is broken into 5 key modules
- Module 1: Fundamental Big Data
- Module 2: Big Data Analysis & Technology Concepts
- Module 3: Fundamental Big Data Analysis and Science
- Module 4: Advanced Big Data Analysis and Science
- Module 5: Big Data Analysis and Science Lab
This course is delivered in partnership with Silver Platypus, the Certified Training Partner of Arcitura™ Education in Australia. Founded by best-selling author Thomas Erl, this curriculum enables IT professionals to develop real-world Big Data proficiency that is vendor and platform neutral. Arcitura™ has certified IT professionals around the world from a wide variety of industries including numerous Fortune 500 companies, international government agencies, financial services, IT Service Provides and many others.
Attendees will leave the course with the following benefits:
- Develop your skills and knowledge in a discipline that is becoming more and more of a high priority focus area for organisations around the world
- Develop real-world Big Data proficiency to help deliver tangible business outcomes through investment in Big Data technology, platforms and best practice
- The vendor-neutral focus of the course means the skills acquired are applicable to any vendor or Big Data platform
- Data Architects
- Data Professionals
- Big Data Specialists
- Solution Architects
- Business Analysts
- Business Intelligence Specialists
- Data Analysts
- Data Scientists
Each day covers one of the five modules required to obtain the Big Data Scientist certification:
Day 1 – Fundamental Big Data: This foundational course module provides a high-level overview of essential Big Data topic areas. A basic understanding of Big Data from business and technology perspectives is provided, along with an overview of common benefits, challenges and adoption issues.
Day 2 – Big Data Analysis & Technology Concepts: This course module explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments.
Day 3 – Fundamental Big Data Analysis & Science: This course module provides an in-depth overview of essential topic areas pertaining to data science and analysis techniques relevant and unique to Big Data, with an emphasis on how analysis and analytics need to be carried out individually and collectively in support of the distinct characteristics, requirements and challenges associated with Big Data datasets.
Day 4 – Advanced Big Data Analysis & Science: This course module delves into a range of advanced data analysis practices and analysis techniques that are explored within the context of Big Data. The course content focuses on topics that enable participants to develop a thorough understanding of statistical, modelling and analysis techniques for data patterns, clusters and text analytics, as well as the identification of outliers and errors that affect the significance and accuracy of predictions made on Big Data datasets.
Day 5 – Big Data Analysis & Science Lab: This course module covers a series of exercises and problems designed to test the participant’s ability to apply knowledge of topics covered previously in course modules 4 and 5. Completing this lab will help highlight areas that require further attention, and will further prove hands-on proficiency in Big Data analysis and science practices as they are applied and combined to solve real-world problems.