Description

A Data Scientist Specialist is professional withinside the use of IBM techniques and technology in fixing commercial enterprise issues with device mastering answers, withinside the layout questioning lens and methodology. This consists of the capacity to attach device mastering answers to agency necessities and commercial enterprise priorities and making use of an information while imposing an agency AI workflow.

Requirements

Exam C1000-059: IBM AI Enterprise Workflow V1 Data Science Specialist

Exam Objectives

Number of questions: 62

Number of inquiries to pass: 44

Time allowed: 90 minutes

Status: Live

Section 1: Scientific, Mathematical, and technical necessities for Data Science and AI

Explain the distinction among Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics

Describe and give an explanation for the important thing phrases withinside the area of synthetic intelligence (Analytics, Data Science, Machine Learning, Deep Learning, Artificial Intelligence etc.)

Distinguish special streams of labor inside Data Science and AI (Data Engineering, Data Science, Data Stewardship, Data Visualization etc.)

Describe the important thing ranges of a device mastering pipeline.

Explain the essential phrases and ideas of layout questioning

Explain the special kinds of essential Data Science

Distinguish and leverage key Open Source and IBM gear and technology that may be utilized by a Data Scientist to put in force AI answers

Explain the overall houses of not unusualplace opportunity distributions.

Explain and calculate special kinds of matrix operations

Section 2: Applications of Data Science and AI in Business

Identify use instances wherein synthetic intelligence answers can deal with commercial enterprise possibilities

Translate commercial enterprise possibilities right into a device mastering scenario

Differentiate the kinds of device mastering algorithms and the eventualities wherein they may be used

Show expertise of a way to speak technical consequences to commercial enterprise stakeholders

Demonstrate expertise of eventualities for software of device mastering

Section 3: Data information strategies in Data Science and AI

Demonstrate expertise of records series practices

Explain traits of various records types

Show expertise of records exploration strategies and records anomaly detection

Use records summarization and visualization strategies to locate applicable insight

Section 4: Data practise strategies in Data Science and AI

Demonstrate know-how cleansing records and addressing records anomalies

Show expertise of function engineering and dimensionality discount strategies

Demonstrate mastery getting ready and cleansing unstructured textual content records

Section 5: Application of Data Science and AI strategies and fashions

Explain device mastering algorithms and the theoretical foundation at the back of them

Demonstrate sensible revel in constructing device mastering fashions and the use of special device mastering algorithms

Section 6: Evaluation of AI fashions

Identify special assessment metrics for device mastering algorithms and a way to use them withinside the assessment of version performance

Demonstrate a success software of version validation and choice techniques

Show mastery of version consequences interpretation

Apply strategies for exceptional tuning and parameter optimization

Section 7: Deployment of AI fashions

Describe the important thing issues while deciding on a platform for AI version deployment

Demonstrate expertise of necessities for version monitoring, control and maintenance

Identify IBM era competencies for constructing, deploying, and dealing with AI fashions

Section 8: Technology Stack for Data Science and AI

Describe the variations among conventional programming and device mastering

Demonstrate foundational expertise of the use of python as a device for constructing AI answers

Show expertise of the blessings of cloud computing for constructing and deploying AI fashions

Show expertise of records garage alternatives

Demonstrate expertise on open supply technology for deployment of AI answers

Demonstrate primary information of herbal language processing

Demonstrate primary information of pc vision

Demonstrate primary information of IBM Watson AI services