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Adrian Gonzalez Sanchez
Artificial Intelligence is everywhere. Organizations are increasingly adopting AI as a way to enable data-driven decision making, and as a great source of automated predictions that will potentially generate interesting savings or new sources of revenue. Even our personal devices such as smartphones or voice assistants are already leveraging AI technologies.
Read more
Artificial Intelligence is everywhere. Organizations are increasingly adopting AI as a way to enable data-driven decision making, and as a great source of automated predictions that will potentially generate interesting savings or new sources of revenue. Even our personal devices such as smartphones or voice assistants are already leveraging AI technologies.
Read more
Artificial Intelligence is everywhere. Organizations are increasingly adopting AI as a way to enable data-driven decision making, and as a great source of automated predictions that will potentially generate interesting savings or new sources of revenue. Even our personal devices such as smartphones or voice assistants are already leveraging AI technologies.
However, the level of AI maturity within the companies varies a lot, as well as the needs for AI-savvy professionals. Reality is that not everyone needs to be an AI expert or a data scientist. Companies need other kinds of profiles for which at least AI knowledge is required, such as product managers or top executives managing innovation initiatives.
This course is designed to give you an introduction to the amazing world of Artificial Intelligence. It offers a very pragmatic overview of AI fundamentals, accessible to both technical and non-technical audiences. This course provides an entrance to the amazing Linux Foundation AI & Data ecosystem, which will be very useful for people looking for relevant open source tools or areas to get involved to continue developing new data and AI skills.
Data and AI Fundamentals is geared towards professionals and students looking for new AI skills, including company executives, hiring managers, product managers, and developers. This course would also be beneficial for industry professionals coming from diverse industries such as finance, supply chain, manufacturing, and other verticals.
It examines the different kinds of AI technologies (e.g., machine learning, NLP). It discusses how to enumerate typical AI use cases for a variety of industries and identifies potential AI career opportunities. Learn to navigate the rich set of Linux Foundation AI & Data open source projects and tools throughout the course.
This course prepares students with the ability to identify the different options available from the family of AI technologies. Upon completing this course, you will be able to choose suitable AI techniques depending on the business needs and leverage existing AI projects and tools from the LF AI & Data ecosystem.
Register for this course and see more details by visiting:
OpenCourser.com/course/wmmzed/data
What's inside
Learning objectives
- Differentiate various kinds of ai technologies (e.g., machine learning, nlp)
- Enumerate typical ai use cases for a variety of industries
- Identify potential ai career opportunities
- Navigate the rich set of linux foundation ai & data open source projects and tools
- Differentiate various kinds of ai technologies (e.g., machine learning, nlp)
- Enumerate typical ai use cases for a variety of industries
- Identify potential ai career opportunities
- Navigate the rich set of linux foundation ai & data open source projects and tools
Syllabus
Welcome!
Chapter 1. Introduction to Artificial Intelligence
Chapter 2. Related AI Topics
Chapter 3. LF AI & Data Foundation
Read more
Syllabus
Welcome!
Chapter 1. Introduction to Artificial Intelligence
Chapter 2. Related AI Topics
Chapter 3. LF AI & Data Foundation
Read more
Final Exam (Verified Certificate track only)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Appropriate for students with diverse industry and academic backgrounds, including those in finance, supply-chain management, manufacturing, and other verticals
Teaches learners how to identify the right AI techniques for their business needs, which is a valuable skill in today's business environment
Provides learners with the opportunity to leverage existing AI projects and tools from the LF AI & Data ecosystem
Taught by instructors from the Linux Foundation AI and Data team, who have experience and expertise in AI technologies
Introduces learners to the field of AI with an overview of its fundamentals
Provides a practical overview of AI fundamentals that is accessible to non-technical audiences, which is a sought-after skill in the industry today
Save this course
Save Data and AI Fundamentals to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data and AI Fundamentals with these
activities:
Read 'Artificial Intelligence: A Modern Approach'
Show steps
Supplement your course material with a comprehensive text to deepen your understanding of AI principles and algorithms.
Show steps
-
Read chapters relevant to the topics covered in the course
-
Take notes and highlight important concepts
-
Solve practice problems and exercises
Follow tutorials to enhance your AI knowledge
Show steps
Complement your course material with tutorials to reinforce your understanding of AI concepts and techniques.
Browse courses on
AI Fundamentals
Show steps
-
Identify areas where you want to expand your knowledge
-
Search for tutorials on specific topics
-
Follow step-by-step instructions and practice examples
-
Complete quizzes or assignments to test your understanding
Practice exercises using the LF AI & Data tools
Show steps
Practice using the LF AI & Data tools to solidify your understanding of their capabilities.
Browse courses on
AI Tools
Show steps
-
Explore the LF AI & Data website and documentation
-
Select a tool or project that interests you
-
Follow tutorials or documentation to get started with the tool
-
Complete hands-on exercises or projects using the tool
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend an AI or data science workshop
Show steps
Enhance your skills and knowledge by participating in hands-on workshops led by industry experts.
Show steps
-
Identify and select a relevant workshop
-
Register and attend the workshop
-
Actively participate in exercises and discussions
-
Connect with instructors and fellow attendees
Create a blog or article summarizing key AI concepts
Show steps
Solidify your understanding by writing about key AI concepts and sharing your insights with others.
Browse courses on
AI Concepts
Show steps
-
Choose a specific topic or aspect of AI
-
Research and gather information from reliable sources
-
Organize your content into a clear and coherent structure
-
Write your blog or article, using simple and engaging language
Develop a presentation on an AI-related topic
Show steps
Apply your knowledge by creating a presentation that showcases your understanding of AI applications and use cases.
Browse courses on
AI Applications
Show steps
-
Select a specific AI application or use case
-
Research and gather information on the topic
-
Design your presentation with clear slides and visuals
-
Practice your presentation and get feedback
Participate in AI hackathons or challenges
Show steps
Challenge yourself and test your skills by participating in AI competitions or hackathons.
Show steps
-
Find an AI competition or hackathon that aligns with your interests
-
Form a team or work individually
-
Develop a solution to the challenge or competition
-
Submit your solution and compete for prizes or recognition
-
Network with other AI enthusiasts
Read 'Artificial Intelligence: A Modern Approach'
Show steps
Supplement your course material with a comprehensive text to deepen your understanding of AI principles and algorithms.
Show steps
Show steps
Show steps
- Read chapters relevant to the topics covered in the course
- Take notes and highlight important concepts
- Solve practice problems and exercises
Follow tutorials to enhance your AI knowledge
Show steps
Complement your course material with tutorials to reinforce your understanding of AI concepts and techniques.
Browse courses on
AI Fundamentals
Show steps
Show steps
Show steps
- Identify areas where you want to expand your knowledge
- Search for tutorials on specific topics
- Follow step-by-step instructions and practice examples
- Complete quizzes or assignments to test your understanding
Practice exercises using the LF AI & Data tools
Show steps
Practice using the LF AI & Data tools to solidify your understanding of their capabilities.
Browse courses on
AI Tools
Show steps
Show steps
Show steps
- Explore the LF AI & Data website and documentation
- Select a tool or project that interests you
- Follow tutorials or documentation to get started with the tool
- Complete hands-on exercises or projects using the tool
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend an AI or data science workshop
Show steps
Enhance your skills and knowledge by participating in hands-on workshops led by industry experts.
Show steps
Show steps
Show steps
- Identify and select a relevant workshop
- Register and attend the workshop
- Actively participate in exercises and discussions
- Connect with instructors and fellow attendees
Create a blog or article summarizing key AI concepts
Show steps
Solidify your understanding by writing about key AI concepts and sharing your insights with others.
Browse courses on
AI Concepts
Show steps
Show steps
Show steps
- Choose a specific topic or aspect of AI
- Research and gather information from reliable sources
- Organize your content into a clear and coherent structure
- Write your blog or article, using simple and engaging language
Develop a presentation on an AI-related topic
Show steps
Apply your knowledge by creating a presentation that showcases your understanding of AI applications and use cases.
Browse courses on
AI Applications
Show steps
Show steps
Show steps
- Select a specific AI application or use case
- Research and gather information on the topic
- Design your presentation with clear slides and visuals
- Practice your presentation and get feedback
Participate in AI hackathons or challenges
Show steps
Challenge yourself and test your skills by participating in AI competitions or hackathons.
Show steps
Show steps
Show steps
- Find an AI competition or hackathon that aligns with your interests
- Form a team or work individually
- Develop a solution to the challenge or competition
- Submit your solution and compete for prizes or recognition
- Network with other AI enthusiasts
Career center
Learners who complete Data and AI Fundamentals will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
**Data Scientists** use their knowledge of machine learning, statistics, and programming to extract insights and patterns from data. They develop and apply algorithms to analyze data and build predictive models. This course may be useful for aspiring Data Scientists, as it provides an introduction to machine learning and other AI technologies.
Machine Learning Engineer
Machine Learning Engineer
**Machine Learning Engineers** design, build, and deploy machine learning models. They work closely with Data Scientists to implement and maintain machine learning systems. This course may be useful for aspiring Machine Learning Engineers, as it provides an introduction to machine learning and other AI technologies.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
**Artificial Intelligence Engineers** design, develop, and implement AI systems. They work on a variety of projects, such as natural language processing, computer vision, and robotics. This course may be useful for aspiring Artificial Intelligence Engineers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Data Analyst
Data Analyst
**Data Analysts** collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations and improve business decisions. This course may be useful for aspiring Data Analysts, as it provides an introduction to data analysis and the Linux Foundation AI & Data ecosystem.
Business Analyst
Business Analyst
**Business Analysts** help organizations to improve their performance by analyzing data and identifying areas for improvement. They work with stakeholders to gather requirements, define problems, and develop solutions. This course may be useful for aspiring Business Analysts, as it provides an introduction to data analysis and the Linux Foundation AI & Data ecosystem.
Product Manager
Product Manager
**Product Managers** are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring new products to market. This course may be useful for aspiring Product Managers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Data Engineer
Data Engineer
**Data Engineers** design, build, and maintain data pipelines. They work with data to ensure that it is clean, consistent, and accessible. This course may be useful for aspiring Data Engineers, as it provides an introduction to data analysis and the Linux Foundation AI & Data ecosystem.
Software Engineer
Software Engineer
**Software Engineers** design, develop, and maintain software applications. They work on a variety of projects, such as web applications, mobile applications, and enterprise software. This course may be useful for aspiring Software Engineers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
IT Manager
IT Manager
**IT Managers** are responsible for the planning, implementation, and management of IT systems. They work with a variety of stakeholders to ensure that IT systems meet the needs of the organization. This course may be useful for aspiring IT Managers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Network Engineer
Network Engineer
**Network Engineers** design, build, and maintain computer networks. They work with a variety of technologies, such as routers, switches, and firewalls. This course may be useful for aspiring Network Engineers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Systems Administrator
Systems Administrator
**Systems Administrators** manage and maintain computer systems. They work with a variety of technologies, such as servers, operating systems, and applications. This course may be useful for aspiring Systems Administrators, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Mobile Developer
Mobile Developer
**Mobile Developers** design, develop, and maintain mobile applications. They work with a variety of technologies, such as Android, iOS, and React Native. This course may be useful for aspiring Mobile Developers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Computer Scientist
Computer Scientist
**Computer Scientists** conduct research in the field of computer science. They develop new algorithms and theories, and they work on a variety of projects, such as artificial intelligence, computer graphics, and operating systems. This course may be useful for aspiring Computer Scientists, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
Database Administrator
Database Administrator
**Database Administrators** manage and maintain databases. They work with data to ensure that it is secure, reliable, and performant. This course may be useful for aspiring Database Administrators, as it provides an introduction to data analysis and the Linux Foundation AI & Data ecosystem.
Web Developer
Web Developer
**Web Developers** design, develop, and maintain websites. They work with a variety of technologies, such as HTML, CSS, and JavaScript. This course may be useful for aspiring Web Developers, as it provides an introduction to AI technologies and the Linux Foundation AI & Data ecosystem.
For more career information including salaries, visit:
OpenCourser.com/course/wmmzed/data
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
Data and AI Fundamentals.
Save
Comprehensive guide to deep learning. It covers the basics of deep learning, such as convolutional neural networks, recurrent neural networks, and transformers. It also includes a number of case studies that show how deep learning can be used to solve real-world problems.
Provides a practical introduction to natural language processing. It covers the basics of NLP, such as tokenization, stemming, and lemmatization. It also includes a number of case studies that show how NLP can be used to solve real-world problems.
Concise and easy-to-read introduction to machine learning. It covers the basics of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning. It good resource for anyone who wants to learn more about AI without getting bogged down in the details.
Provides a practical introduction to data science. It covers the basics of data science, such as data cleaning, data analysis, and data visualization. It also includes a number of case studies that show how data science can be used to solve real-world problems.
Save
Provides a critical look at data science. It discusses the ethical and social implications of data science, and it argues that data science should be used to benefit society, not just to make money.
Save
Comprehensive guide to data science. It covers the basics of data science, as well as more advanced topics such as machine learning and deep learning. It good resource for anyone who wants to learn more about data science.
Provides a practical introduction to machine learning using Python. It covers the basics of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning. It also includes a number of case studies that show how machine learning can be used to solve real-world problems.
Provides a practical introduction to machine learning using R. It covers the basics of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning. It also includes a number of case studies that show how machine learning can be used to solve real-world problems.
Save
Provides a practical introduction to data mining using R. It covers the basics of data mining, such as data cleaning, data analysis, and data visualization. It also includes a number of case studies that show how data mining can be used to solve real-world problems.
Provides a practical introduction to deep learning using Python. It covers the basics of deep learning, such as convolutional neural networks, recurrent neural networks, and transformers. It also includes a number of case studies that show how deep learning can be used to solve real-world problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wmmzed/data
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Effort
1 to 2 hours per week for 10 weeks
Level
Introductory
Via
edX
Institution
The Linux Foundation
Instructor
Adrian Gonzalez Sanchez
Session
April 17, 2024
- October 15, 2025
Language
English
Transcript
English
Good to know
Appropriate for students with diverse industry and academic backgrounds, including those in finance, supply-chain management, manufacturing, and other verticals
Teaches learners how to identify the right AI techniques for their business needs, which is a valuable skill in today's business environment
Provides learners with the opportunity to leverage existing AI projects and tools from the LF AI & Data ecosystem
Taught by instructors from the Linux Foundation AI and Data team, who have experience and expertise in AI technologies
Introduces learners to the field of AI with an overview of its fundamentals
Provides a practical overview of AI fundamentals that is accessible to non-technical audiences, which is a sought-after skill in the industry today
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