Certified Big Data Science Professional

The Big Data Science Professional track is comprised of BDSCP Modules 1, 2 and 3. The final course module consists of a series of lab exercises that require participants to apply their knowledge of the preceding courses in order to fulfill project requirements and solve real world problems. Completion of these courses as part of a virtual or on-site workshop results in each participant receiving an official digital Certificate of Completion, as well as a digital Training Badge from Acclaim/Credly.

Description

WHAT YOU WILL LEARN

A Certified Big Data Science Professional has demonstrated proficiency in fundamental Big Data technologies and practices, including analysis, analytics and mechanisms common to contemporary Big Data environments and tools. Depending on the exam format chosen, attaining the Big Data Science Professional Certification can require passing a single exam or multiple exams. Those who achieve this certification receive an official digital Certificate of Excellence, as well as a digital Certification Badge from Acclaim/Credly with an account that supports the online verification of certification status.

MODULE OVERVIEW

The Big Data Science Professional certification track is associated with the following courses and the courses can be delivered via instructor-led training.

BDSCP Module 1: Fundamental Big Data

This foundational course 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. The course content is divided into a series of modular sections, each of which is accompanied by one or more hands-on exercises.
The following primary topics are covered:
– Understanding Big Data
– Fundamental Terminology & Concepts
– Big Data Business & Technology Drivers
– Traditional Enterprise & Technologies Related to Big Data
– Characteristics of Data in Big Data Environments
– Dataset Types in Big Data Environments
– Fundamental Analysis and Analytics
– Machine Learning Types
– Business Intelligence & Big Data
– Data Visualization & Big Data
– Big Data Adoption & Planning Considerations
Duration: 1 Day

BDSCP Module 2: Big Data Analysis & Technology Concepts

This course explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments. The course content does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions, as well as a high-level understanding of the back-end components that enable these functions.
The following primary topics are covered:
– Big Data Analysis Lifecycle (from business case evaluation to data analysis and visualization)
– A/B Testing, Correlation
– Regression, Heat Maps
– Time Series Analysis
– Traditional Enterprise
– Network Analysis
– Spatial Data Analysis
– Classification, Clustering
– Filtering (including collaborative filtering & content-based filtering)
– Sentiment Analysis, Text Analytics
– Processing Workloads, Clusters
– Cloud Computing & Big Data
– Foundational Big Data Technology Mechanisms
Duration: 1 Day

BDSCP Module 3: Big Data Analysis & Technology Lab

This course module presents participants with a series of exercises and problems designed to test their ability to apply knowledge of topics covered previously in course modules 1 and 2. Completing this lab will help highlight areas that require further attention, and will further prove hands-on proficiency in Big Data analysis and technology and practices as they are applied and combined to solve real-world problems.
As a hands-on lab, this course provides a set of detailed exercises that require participants to solve a number of inter-related problems, with the goal of fostering a comprehensive understanding of how Big Data environments work from both front and back-ends, and how they are used to solve real-world analysis and analytics problems.
For instructor-led delivery of this lab course, the Certified Trainer works closely with participants to ensure that all exercises are carried out completely and accurately. Attendees can voluntarily have exercises reviewed and graded as part of the class completion. For individual completion of this course as part of the Module 3 Study Kit, a number of supplements are provided to help participants carry out exercises with guidance and numerous resource references.
Duration: 1 Day

PREREQUISITES
  • There are no formal prerequisites for the certification exam
EXAM & CERTIFICATION

You can take exams anywhere in the world via Pearson VUE testing centers, Pearson VUE online proctoring and Arcitura on-site exam proctoring at your location.

  • Complete Exam B90.BDP, a single combined exam for the entire Big Data Science Professional certification track. Recommended for those who want to only take a single exam that encompasses all course modules within this track.
  • Complete one module-specific exam for each course module in Big Data Science Professional Certification track. This is recommended for those who want to progress gradually through the track and who would like to be assessed after each course module before proceeding to the next.
CLASSROOM / INSTRUCTOR LED
  • High-impact learning with case studies
  • Delivered by certified instructors
  • Targeted learning for real projects

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