IBM Certified Specialist – AI Enterprise Workflow V1
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IBM Certified Specialist – AI Enterprise Workflow V1
認證概述
數據科學家專家擅長使用 IBM 方法和技術，在設計思維視角和方法論中，通過機器學習解決方案解決業務問題。這包括將機器學習解決方案與企業要求和業務優先順序聯繫起來的能力，以及在實施企業 AI 工作流時應用理解。
要求
考試 C1000-059：IBM AI 企業工作流 V1 數據科學專家
考試目標
試題數量： 62 通
題數： 44
允許時間： 90 分鐘
狀態： 直播
第1部分：數據科學和人工智慧的科學，數學和技術要點
Explain the difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics
Describe and explain the key terms in the field of artificial intelligence (Analytics, Data Science, Machine Learning, Deep Learning, Artificial Intelligence etc.)
Distinguish different streams of work within Data Science and AI (Data Engineering, Data Science, Data Stewardship, Data Visualization etc.)
Describe the key stages of a machine learning pipeline.
Explain the fundamental terms and concepts of design thinking
Explain the different types of fundamental Data Science
Distinguish and leverage key Open Source and IBM tools and technologies that can be used by a Data Scientist to implement AI solutions
Explain the general properties of common probability distributions.
Explain and calculate different types of matrix operations
第2部分：數據科學和人工智慧在商業中的應用
Identify use cases where artificial intelligence solutions can address business opportunities
Translate business opportunities into a machine learning scenario
Differentiate the categories of machine learning algorithms and the scenarios where they can be used
Show knowledge of how to communicate technical results to business stakeholders
Demonstrate knowledge of scenarios for application of machine learning
第3部分：數據科學和AI中的數據理解技術
Demonstrate knowledge of data collection practices
Explain characteristics of different data types
Show knowledge of data exploration techniques and data anomaly detection
Use data summarization and visualization techniques to find relevant insight
第4部分：數據科學和AI中的數據準備技術
Demonstrate expertise cleaning data and addressing data anomalies
Show knowledge of feature engineering and dimensionality reduction techniques
Demonstrate mastery preparing and cleaning unstructured text data
第5部分：數據科學和AI技術與模型的應用
Explain machine learning algorithms and the theoretical basis behind them
Demonstrate practical experience building machine learning models and using different machine learning algorithms
第6章 AI模型的評估
Identify different evaluation metrics for machine learning algorithms and how to use them in the evaluation of model performance
Demonstrate successful application of model validation and selection methods
Show mastery of model results interpretation
Apply techniques for fine tuning and parameter optimization
第7章 AI模型的部署
Describe the key considerations when selecting a platform for AI model deployment
Demonstrate knowledge of requirements for model monitoring, management and maintenance
Identify IBM technology capabilities for building, deploying, and managing AI models
第8部分：數據科學和AI的技術堆疊
Describe the differences between traditional programming and machine learning
Demonstrate foundational knowledge of using python as a tool for building AI solutions
Show knowledge of the benefits of cloud computing for building and deploying AI models
Show knowledge of data storage alternatives
Demonstrate knowledge on open source technologies for deployment of AI solutions
Demonstrate basic understanding of natural language processing
Demonstrate basic understanding of computer vision
Demonstrate basic understanding of IBM Watson AI services
考試資源
提供課程和出版物以幫助您準備認證測試。在參加認證考試之前，建議但不是必需的課程。在準備認證測試時，請記住，需要現實世界的經驗才能有合理的機會通過認證測試。課件不能取代對經驗的要求。請注意，課程設置不斷添加和更新。
本考試提供以下語言版本：英語
每次考試價格：200 美元
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