Description

Enterprise Big Data Scientist Syllabus

The Enterprise Big Data Scientist (EBDS®) Syllabus, is a comprehensive resource that elevates your skills and knowledge in the dynamic field of big data analytics. As a complimentary offering upon opening an account or becoming a member of Enterprise Big Data Framework, this syllabus seamlessly integrates into your personal library, granting you exclusive access to member discounts and engaging community activities.

About the Enterprise Big Data Scientist Certification Program

Elevate Your Big Data Skills: The Enterprise Big Data Scientist certification program is designed to empower professionals like you with the skills and knowledge needed to excel in the world of Big Data. This program is globally recognized and accredited by APMG-International, ensuring that your expertise is acknowledged worldwide.

What the Syllabus Covers

• Learning Outcomes: The Enterprise Big Data Scientist Syllabus documents the learning outcomes associated with the Enterprise Big Data Scientist certification course. It defines the scope of the requirements that candidates are expected to meet, demonstrating their achievement of these learning outcomes at each qualification level.

• Exam Design Insights: Gain insights into the design of the Enterprise Big Data Scientist certification exams. The syllabus provides a detailed breakdown of what the exams will assess, helping you prepare effectively for success.

Key Features

• Learning Outcomes and Certification Scope: Documenting the EBDS certification course, the syllabus outlines clear learning outcomes at each qualification level.Defines the scope of requirements for candidates to showcase mastery of data science principles and practices.

• Theoretical Foundation and Practical Application:Delve into a solid theoretical foundation of data science.Equip yourself with tools to design and develop algorithms for extracting value from massive datasets.Gain an in-depth overview of data communication, machine learning, and modeling.

• Statistical Modeling and Techniques:Explore statistical modeling and techniques tailored for complex enterprise problems.Receive practical, hands-on learning predominantly in Python, running parallel to theoretical concepts.

• Comprehensive Curriculum:Cover a wide range of topics, including statistical methods, supervised to deep learning, data communication & visualization, and applied data science in real-world scenarios.

• Practitioner Focus:Tailored for data analysts and aspiring data scientists seeking an in-depth understanding of cutting-edge data science methods.Emphasizes scientific aspects to empower participants with skills to design algorithmic solutions for enterprise problems.

• Python-Centric Approach:Practical techniques demonstrated in Python, with brief exposure to R and SQL.