Data Science Profession Recertification - Expert
Issued by
IBM
An IBM Expert Data Scientist leads works with business leaders to solve problems by understanding, preparing and analyzing data to predict emerging trends and provide recommendations to optimize business results. This badge holder applies and integrates a broad variety of products, technologies, and services including integration with legacy systems and processes. At Expert Level, the IBM Certified Data Scientist is recognized as a Subject Matter Expert and leads others in their work.
- Time Months
- Cost Free
Skills
- AI
- Analytics
- Artificial Intelligence
- Augmented Intelligence
- Cognitive Computing
- CRISP-DM
- Data Science
- Data Scientist
- Deep Learning
- Expert
- Linear Regression
- Machine Learning
- ML
- Model Validation
- Natural Language Processing
- NLP
- Optimization
- Prescriptive Analytics
- Python
- R
- Regression
- Scala
- Simulation
- SPSS
- Statistics
- Visualization
Earning Criteria
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Must be an employee of IBM.
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Must have a valid certification at Level 2 (Expert) in order to be able to apply for recertification.
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Two (2) valid/ up to date badge out of these: Blue Core Mentor, IBM Mentor, Intellectual Capital / Property Creator, Speaker/Presenter, Teacher/Educator, Profession Champion. Note:The give back badges should not have been used in your certification application. Other forms of giveback may be accepted as alternatives to the leadership badges. Examples include leading Women in Technology initiatives, participating in Academy of Technology studies and TLE Speaker/Challenge participation.
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One (1) Project summary (to be documented in the recertification form) from the last three years. Project summaries include a description of: Client engagement, Your role, Problem, Solution, Results. Note: Project summary should not have been used in your certification application.
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Completed formal training in the discipline of data science (such as statistics, operations research, machine learning, or econometrics) either through attendance at a taught course, or through self-study.