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Suitable for learners seeking to delve into industry standard cognitive search and knowledge store techniques and practices
Provides hands-on experience through customer case studies and demonstrations
Introduces the latest features and advancements in cognitive search, including complex type, storage-optimized SKU, and the knowledge store
May require prerequisite knowledge in data science and machine learning concepts

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Activities

Coming soon We're preparing activities for Knowledge Mining: AI-driven Content Understanding with Cognitive Search on Azure. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Knowledge Mining: AI-driven Content Understanding with Cognitive Search on Azure will develop knowledge and skills that may be useful to these careers:
Cognitive Search Engineer
Cognitive Search Engineers design and implement cognitive search solutions for businesses. They use AI to understand business documents and extract entities and relationships from unstructured data. This course provides a foundation in cognitive search, including how to deploy a cognitive search solution and use the new knowledge store. This course can help you develop the skills you need to succeed as a Cognitive Search Engineer.
Data Scientist
Data Scientists use AI to solve business problems. They collect, clean, and analyze data to identify patterns and trends. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models. They use AI to solve business problems, such as predicting customer behavior or detecting fraud. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Machine Learning Engineer.
Information Architect
Information Architects design and organize information systems. They use AI to improve the findability and accessibility of information. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as an Information Architect.
Knowledge Manager
Knowledge Managers manage and share knowledge within an organization. They use AI to improve the findability and accessibility of knowledge. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Knowledge Manager.
Content Strategist
Content Strategists develop and execute content strategies for businesses. They use AI to improve the effectiveness of content. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Content Strategist.
Digital Marketing Manager
Digital Marketing Managers plan and execute digital marketing campaigns. They use AI to improve the effectiveness of marketing campaigns. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Digital Marketing Manager.
Product Manager
Product Managers develop and manage products. They use AI to improve the quality and effectiveness of products. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Product Manager.
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. They use AI to improve the efficiency and effectiveness of business processes. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Business Analyst.
Project Manager
Project Managers plan and execute projects. They use AI to improve the efficiency and effectiveness of projects. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Project Manager.
Analyst
Analysts collect, clean, and analyze data to identify patterns and trends. They use AI to improve the accuracy and effectiveness of analysis. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as an Analyst.
Consultant
Consultants provide advice and guidance to businesses. They use AI to improve the effectiveness of consulting services. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Consultant.
Researcher
Researchers conduct research to advance knowledge and understanding. They use AI to improve the efficiency and effectiveness of research. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Researcher.
Software Engineer
Software Engineers design, develop, and maintain software systems. They use AI to improve the quality and effectiveness of software systems. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Software Engineer.
Data Engineer
Data Engineers design, build, and maintain data pipelines. They use AI to improve the efficiency and effectiveness of data pipelines. This course provides a foundation in AI, including how to apply AI to understand business documents. This course can help you develop the skills you need to succeed as a Data Engineer.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Knowledge Mining: AI-driven Content Understanding with Cognitive Search on Azure.
Provides a comprehensive introduction to NLP with PyTorch, covering fundamental concepts such as text preprocessing, tokenization, and embedding. It also explores advanced topics such as transformers and deep learning models for NLP.
Provides a comprehensive overview of deep learning, covering both theoretical and practical aspects. It discusses topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of text mining, covering both theoretical and practical aspects. It discusses topics such as text preprocessing, text classification, and text clustering.
Provides a comprehensive overview of speech and language processing, covering both theoretical and practical aspects. It discusses topics such as speech recognition, natural language understanding, and speech synthesis.
Provides a comprehensive overview of natural language understanding, covering both theoretical and practical aspects. It discusses topics such as natural language parsing, natural language generation, and natural language dialogue.
Provides a comprehensive overview of information theory, inference, and learning algorithms. It covers topics such as entropy, information gain, and the Bayes theorem.
Provides a comprehensive overview of pattern recognition and machine learning, covering both theoretical and practical aspects. It discusses topics such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive overview of data structures and algorithms, covering both theoretical and practical aspects. It discusses topics such as linked lists, trees, and graphs.
Provides a comprehensive overview of data mining, covering both theoretical and practical aspects. It discusses topics such as data preprocessing, data mining algorithms, and data visualization.
Provides a practical guide to machine learning, with a focus on real-world applications. It covers topics such as supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive overview of information retrieval, covering both theoretical and practical aspects. It discusses topics such as text indexing, query processing, and evaluation.
Provides a practical guide to search engine design and implementation. It covers topics such as web crawling, indexing, and ranking.

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