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Matthew Renze
Learn about artificial intelligence and how it will impact you, your career, and our future. This course will teach you about the tools, technology, and trends driving the modern AI revolution.
Read more
Learn about artificial intelligence and how it will impact you, your career, and our future. This course will teach you about the tools, technology, and trends driving the modern AI revolution.
Read more
Learn about artificial intelligence and how it will impact you, your career, and our future. This course will teach you about the tools, technology, and trends driving the modern AI revolution.
Artificial Intelligence has the potential to radically transform your economy, your society, and your world. In this course, Artificial Intelligence: The Big Picture of AI, you will learn what AI is, why it's important, and how it will impact you, your career, and your future. First, you'll learn about modern data-driven AI technologies like machine learning, deep learning, and reinforcement learning. Next, you'll learn about building and using AI tools. Finally, you'll see how AI will impact the IT industry, your labor economy, and your society as a whole. By the end of this course, you'll understand artificial intelligence and the tools, technology, and trends driving the AI revolution.
Register for this course and see more details by visiting:
OpenCourser.com/course/tf19yl/artificial
What's inside
Syllabus
Course Overview
Introduction
Artificial Intelligence
History of A.I.
Read more
Syllabus
Course Overview
Introduction
Artificial Intelligence
History of A.I.
Read more
Modern A.I.
A.I. and I.T.
Future of A.I.
Conclusion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops an understanding of artificial intelligence, preparing you for a future shaped by it
Taught by Matthew Renze, an industry expert in AI
Introduces modern data-driven AI technologies, such as machine learning, deep learning, and reinforcement learning, which are in high demand in various industries
Provides insights into the impact AI will have on IT, the economy, and society as a whole, helping learners develop a broader perspective on the digital landscape
Examines the history and future of AI, providing a comprehensive overview of the field
Requires no prior knowledge in AI, making it accessible to learners from diverse backgrounds
Save this course
Save Artificial Intelligence: The Big Picture of AI 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 Artificial Intelligence: The Big Picture of AI with these
activities:
Introduction to Machine Learning, 4th Edition by Ethem Alpaydin
Show steps
Read the foundational concepts in the book to enhance your understanding of the course materials
View
Machine Learning, revised and updated edition
on Amazon
Show steps
-
Summarize the key ideas and concepts covered in each chapter of the book.
-
Identify the connections between the book's content and the course material.
Review Machine Learning Algorithms
Show steps
Review the key concepts and algorithms in machine learning to refresh your prior knowledge.
Browse courses on
Machine Learning
Show steps
-
Revisit the different types of machine learning algorithms, such as supervised, unsupervised, and reinforcement learning.
-
Identify the strengths and weaknesses of each type of algorithm and when to use them.
-
Practice implementing basic machine learning algorithms in a programming language of your choice.
Follow Online Tutorials on Deep Learning
Show steps
Supplementary resources can help solidify your understanding of the course concepts.
Show steps
-
Locate online tutorials that cover deep learning concepts and techniques relevant to the course.
-
Watch the tutorials and take notes to reinforce your understanding.
-
Try out the examples and exercises provided in the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Study Group or AI Discussion Forum
Show steps
Engaging with peers can provide different perspectives and reinforce your understanding.
Show steps
-
Identify and join a study group or online discussion forum focused on AI.
-
Actively participate in discussions, ask questions, and share your insights.
Solve Machine Learning Practice Problems
Show steps
Solving practice problems will help you improve your understanding and problem-solving skills.
Show steps
-
Find online resources or textbooks with practice problems related to machine learning.
-
Attempt to solve the problems on your own, focusing on understanding the concepts behind each problem.
-
Check your solutions against the provided answers or consult with others to identify any errors and improve your understanding.
Develop a Presentation on a Specific Aspect of AI
Show steps
Creating a presentation will allow you to synthesize your knowledge and demonstrate your understanding of AI.
Show steps
-
Choose a specific aspect of AI that interests you and aligns with the course content.
-
Research the topic thoroughly and gather relevant information.
-
Create a presentation that includes an introduction, background, discussion, and conclusion.
Attend an AI-Related Workshop or Conference
Show steps
Workshops and conferences provide opportunities to learn from experts and network with other professionals.
Show steps
-
Identify upcoming AI-related workshops or conferences in your area or online.
-
Register for the event and actively participate in the sessions.
Build a Machine Learning Project Using a Public Dataset
Show steps
Applying your knowledge to a real-world project will give you valuable practical experience.
Show steps
-
Identify a public dataset that interests you and aligns with the concepts covered in the course.
-
Choose a machine learning algorithm that is appropriate for the dataset and task you want to perform.
-
Implement the algorithm using a programming language and evaluate its performance.
Introduction to Machine Learning, 4th Edition by Ethem Alpaydin
Show steps
Read the foundational concepts in the book to enhance your understanding of the course materials
View
Machine Learning, revised and updated edition
on Amazon
Show steps
Show steps
Show steps
- Summarize the key ideas and concepts covered in each chapter of the book.
- Identify the connections between the book's content and the course material.
Review Machine Learning Algorithms
Show steps
Review the key concepts and algorithms in machine learning to refresh your prior knowledge.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Revisit the different types of machine learning algorithms, such as supervised, unsupervised, and reinforcement learning.
- Identify the strengths and weaknesses of each type of algorithm and when to use them.
- Practice implementing basic machine learning algorithms in a programming language of your choice.
Follow Online Tutorials on Deep Learning
Show steps
Supplementary resources can help solidify your understanding of the course concepts.
Show steps
Show steps
Show steps
- Locate online tutorials that cover deep learning concepts and techniques relevant to the course.
- Watch the tutorials and take notes to reinforce your understanding.
- Try out the examples and exercises provided in the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Study Group or AI Discussion Forum
Show steps
Engaging with peers can provide different perspectives and reinforce your understanding.
Show steps
Show steps
Show steps
- Identify and join a study group or online discussion forum focused on AI.
- Actively participate in discussions, ask questions, and share your insights.
Solve Machine Learning Practice Problems
Show steps
Solving practice problems will help you improve your understanding and problem-solving skills.
Show steps
Show steps
Show steps
- Find online resources or textbooks with practice problems related to machine learning.
- Attempt to solve the problems on your own, focusing on understanding the concepts behind each problem.
- Check your solutions against the provided answers or consult with others to identify any errors and improve your understanding.
Develop a Presentation on a Specific Aspect of AI
Show steps
Creating a presentation will allow you to synthesize your knowledge and demonstrate your understanding of AI.
Show steps
Show steps
Show steps
- Choose a specific aspect of AI that interests you and aligns with the course content.
- Research the topic thoroughly and gather relevant information.
- Create a presentation that includes an introduction, background, discussion, and conclusion.
Attend an AI-Related Workshop or Conference
Show steps
Workshops and conferences provide opportunities to learn from experts and network with other professionals.
Show steps
Show steps
Show steps
- Identify upcoming AI-related workshops or conferences in your area or online.
- Register for the event and actively participate in the sessions.
Build a Machine Learning Project Using a Public Dataset
Show steps
Applying your knowledge to a real-world project will give you valuable practical experience.
Show steps
Show steps
Show steps
- Identify a public dataset that interests you and aligns with the concepts covered in the course.
- Choose a machine learning algorithm that is appropriate for the dataset and task you want to perform.
- Implement the algorithm using a programming language and evaluate its performance.
Career center
Learners who complete Artificial Intelligence: The Big Picture of AI will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers will benefit from the course Artificial Intelligence: The Big Picture of AI. The course will help build a base in AI by teaching the basics of AI, such as machine learning, deep learning, and reinforcement learning. These teachings can help Machine Learning Engineers become well-rounded in AI and take on more challenging projects.
Data Scientist
Data Scientist
Data Scientists who wish to lead AI projects may benefit from taking the course Artificial Intelligence: The Big Picture of AI. The course will help Data Scientists gain a comprehensive background in AI tools, technology, and trends, which will inform their decision-making as a project lead.
Product Manager
Product Manager
Product Managers who wish to develop AI-based products may benefit from taking the course Artificial Intelligence: The Big Picture of AI. The course will help Product Managers learn about the tools, technology, and trends that affect AI products. This knowledge will assist them in making better decisions about product development.
Software Engineer
Software Engineer
Software Engineers looking to enter the field of AI should consider taking the course Artificial Intelligence: The Big Picture of AI. The course will lay a complete foundation for developing AI products and services by educating Software Engineers on the tools, technology, and trends of AI.
Systems Engineer
Systems Engineer
Systems Engineers may benefit from the course Artificial Intelligence: The Big Picture of AI. The course will provide a strong foundation for understanding AI tools, technology, and trends, which will be useful for designing and implementing AI systems.
Information Security Analyst
Information Security Analyst
Information Security Analysts may benefit from taking the course Artificial Intelligence: The Big Picture of AI. The course will help build a foundation in understanding AI tools, technology, and trends that are used in cybersecurity. This knowledge may help Information Security Analysts better protect their organizations from AI-based threats.
Data Analyst
Data Analyst
Data Analysts will benefit from taking the course Artificial Intelligence: The Big Picture of AI. The course will help them understand the AI technologies and trends that are shaping the modern world. With this new knowledge, Data Analysts can provide better insights into data and help businesses make better decisions.
Computer Systems Analyst
Computer Systems Analyst
Computer Systems Analysts may benefit from taking the course Artificial Intelligence: The Big Picture of AI. The course will help build a foundation for understanding AI tools, technology, and trends that shape the IT industry. This knowledge can help Computer Systems Analysts make more informed decisions about AI implementations.
Operations Research Analyst
Operations Research Analyst
The course Artificial Intelligence: The Big Picture of AI may be useful for Operations Research Analysts. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Operations Research Analysts make better decisions about how to optimize their operations.
IT Architect
IT Architect
The course Artificial Intelligence: The Big Picture of AI may be useful for IT Architects. It will help build a strong foundation for understanding AI tools, technology, and trends. This knowledge may help IT Architects make better decisions about how to integrate AI into their IT systems.
Financial Analyst
Financial Analyst
The course Artificial Intelligence: The Big Picture of AI may be useful for Financial Analysts. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Financial Analysts make better investment decisions.
Marketing Manager
Marketing Manager
The course Artificial Intelligence: The Big Picture of AI may be useful for Marketing Managers. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Marketing Managers develop more effective marketing campaigns.
Management Consultant
Management Consultant
The course Artificial Intelligence: The Big Picture of AI may be useful for Management Consultants. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Management Consultants better advise their clients.
Sales Manager
Sales Manager
The course Artificial Intelligence: The Big Picture of AI may be useful for Sales Managers. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Sales Managers better understand their customers and close more deals.
Business Analyst
Business Analyst
The course Artificial Intelligence: The Big Picture of AI may be useful for Business Analysts. Understanding the AI tools, technology, and trends that are transforming economies, societies, and the world can help Business Analysts make better recommendations to their clients.
For more career information including salaries, visit:
OpenCourser.com/course/tf19yl/artificial
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
Artificial Intelligence: The Big Picture of AI.
Comprehensive and widely used textbook on artificial intelligence. It covers a broad range of topics, from the basics of AI to the latest advancements in the field. It valuable resource for anyone who wants to learn more about AI.
Save
Comprehensive guide to deep learning. It covers the basics of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone who wants to learn more about deep learning.
Is an introduction to reinforcement learning. It covers the basics of reinforcement learning, including value functions, policy gradients, and actor-critic methods. It valuable resource for anyone who wants to learn more about reinforcement learning.
Comprehensive guide to statistical learning. It covers a broad range of topics, from the basics of statistical learning to the latest advancements in the field. It valuable resource for anyone who wants to learn more about statistical learning.
Save
Comprehensive guide to pattern recognition and machine learning. It covers a broad range of topics, from the basics of pattern recognition and machine learning to the latest advancements in the field. It valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
Provides a probabilistic perspective on machine learning. It covers the basics of machine learning, including supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning from a probabilistic perspective.
Provides a Bayesian perspective on machine learning. It covers the basics of Bayesian inference, including probability theory, Bayesian networks, and Markov chain Monte Carlo. It valuable resource for anyone who wants to learn more about machine learning from a Bayesian perspective.
Provides an introduction to automated machine learning. It covers the basics of automated machine learning, including hyperparameter optimization, feature engineering, and model selection. It valuable resource for anyone who wants to learn more about automated machine learning.
Save
Provides a broad overview of AI. It covers a wide range of topics, from the history of AI to the latest advancements in the field. It valuable resource for anyone who wants to learn more about AI.
Save
Explores the potential risks and benefits of artificial intelligence. It discusses the possibility of artificial intelligence surpassing human intelligence and the implications of this for humanity. It valuable resource for anyone who is interested in the future of AI.
Save
Explores the potential impact of AI on society. It discusses the possibility of AI transforming the economy, healthcare, and education. It valuable resource for anyone who is interested in the future of AI and its impact on society.
Save
Provides a comprehensive overview of AI. It covers a wide range of topics, from the history of AI to the latest advancements in the field. It valuable resource for anyone who wants to learn more about AI.
Save
Provides an introduction to AI. It covers the basics of AI, including machine learning, deep learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/tf19yl/artificial
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Time
74 hours
Level
Introductory
Via
Pluralsight
Instructor
Matthew Renze
Language
English
Good to know
Develops an understanding of artificial intelligence, preparing you for a future shaped by it
Taught by Matthew Renze, an industry expert in AI
Introduces modern data-driven AI technologies, such as machine learning, deep learning, and reinforcement learning, which are in high demand in various industries
Provides insights into the impact AI will have on IT, the economy, and society as a whole, helping learners develop a broader perspective on the digital landscape
Examines the history and future of AI, providing a comprehensive overview of the field
Requires no prior knowledge in AI, making it accessible to learners from diverse backgrounds
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