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The Intel® AI Value
Intel
Intel
Learn how Intel helps accelerates our customers' AI journey
Register for this course and see more details by visiting:
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What's inside
Syllabus
The Intel AI Value
Learn how Intel helps accelerates our customers' AI journey
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
The core audience for whom this course is designed are those individuals who are interested in accelerating their AI journey, particularly those working with Intel technology
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Activities
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The Intel® AI Value.
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Career center
Learners who complete The Intel® AI Value will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist may work with deep learning models, neural networks, and big data, and designing and implementing AI solutions. This course may help build a foundation in the key concepts of AI and how to apply this knowledge in practical settings.
AI Researcher
AI Researcher
An AI Researcher develops new and innovative AI algorithms and techniques. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to conduct research in the field of AI.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops, builds, and maintains machine learning models and algorithms. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to develop machine learning models.
AI Engineer
AI Engineer
An AI Engineer develops and deploys AI systems and is responsible for the system's performance and reliability. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to build and maintain AI systems.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to manage and execute AI-powered projects.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products and features. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to develop AI-powered products and features.
Business Analyst
Business Analyst
A Business Analyst analyzes business needs and develops solutions to improve efficiency and effectiveness. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to analyze business needs and develop AI-powered solutions.
Software Engineer
Software Engineer
A Software Engineer develops and maintains software applications and systems. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to develop AI-powered software applications and systems.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to identify trends and patterns. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to analyze data and identify trends and patterns using AI techniques.
IT Manager
IT Manager
An IT Manager plans, implements, and manages an organization's IT infrastructure and systems. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to manage and maintain AI-powered IT infrastructure and systems.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data and makes recommendations on investments. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to analyze financial data and make recommendations on investments using AI techniques.
Technical Writer
Technical Writer
A Technical Writer creates and maintains technical documentation. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to create and maintain technical documentation for AI-powered systems and products.
Sales Engineer
Sales Engineer
A Sales Engineer provides technical expertise to customers and helps them select and implement products and services. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to provide technical expertise to customers on AI-powered products and services.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze data and make predictions. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to develop and use AI-powered mathematical and statistical models.
Risk Manager
Risk Manager
A Risk Manager identifies, assesses, and mitigates risks. This course may help build a foundation in the key concepts of AI and how to apply this knowledge to identify, assess, and mitigate risks associated with AI-powered systems and products.
For more career information including salaries, visit:
OpenCourser.com/course/bxwmr5/the
Reading list
We've selected ten 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
The Intel® AI Value.
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Comprehensive guide to computer vision, covering topics such as image processing, feature detection, and object recognition. It is written by a leading expert in the field.
Comprehensive guide to speech and language processing, covering topics such as speech recognition, natural language understanding, and speech synthesis. It is written by two leading experts in the field.
Save
Comprehensive guide to generative adversarial networks (GANs), covering topics such as the theory of GANs, the different types of GANs, and the applications of GANs. It is written by three leading experts in the field.
Save
Comprehensive guide to deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and transformers. It is written by three leading experts in the field.
Comprehensive guide to natural language processing, covering topics such as text preprocessing, machine learning for NLP, and deep learning for NLP. It is written by three leading experts in the field.
Comprehensive guide to deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and transformers. It is written by four leading experts in the field.
Practical guide to deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and transformers. It is written by an experienced deep learning practitioner.
Comprehensive introduction to reinforcement learning, covering topics such as Markov decision processes, value iteration, and policy gradient methods. It is written by two leading experts in the field.
Practical guide to machine learning, covering topics such as data preprocessing, model selection, and evaluation. It is written by an experienced machine learning practitioner.
Provides a comprehensive overview of artificial intelligence (AI), covering topics such as machine learning, deep learning, and natural language processing. It is written in a clear and concise style, making it easy to understand for beginners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/bxwmr5/the
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Level
Introductory
Via
Coursera
Institution
Intel
Instructor
Intel
Language
English
This course belongs to a
collection
called
Intel® AI Fundamentals. It's comprised of three courses:
- The Intel® AI Value (viewing)
- Intel® AI Win Recipes
- AI Essentials
Good to know
The core audience for whom this course is designed are those individuals who are interested in accelerating their AI journey, particularly those working with Intel technology
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