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Renée Cummings
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.
Read more
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.
Read more
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.
This is the first of four courses in the Certified Artificial Intelligence Practitioner (CAIP) professional certification. This course is meant as an entry point into the world of AI/ML. You'll learn about the business problems that AI/ML can solve, as well as the specific AI/ML technologies that can solve them. In addition, you'll get an overview of the general workflow involved in machine learning, as well as the tools and other resources that support it. This course also promotes the importance of ethics in AI/ML, and provides you with techniques for addressing ethical challenges.
Ultimately, this course will get you thinking about the "why?" of AI/ML, and it will ensure that your more technical work in later courses is done with clear business goals in mind.
Register for this course and see more details by visiting:
OpenCourser.com/course/vpgcb7/solve
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What's inside
Syllabus
Apply AI and ML to Business Problems
Deep learning, machine learning (ML), and other forms of artificial intelligence (AI) are on the rise. Organizations use these technologies to inform business decisions and guide operations—often with profound results. However, it can be challenging to identify which business problems are most amenable to these technologies. In this first module, you'll begin exploring AI and ML as solutions to these problems.
Read more
Syllabus
Apply AI and ML to Business Problems
Deep learning, machine learning (ML), and other forms of artificial intelligence (AI) are on the rise. Organizations use these technologies to inform business decisions and guide operations—often with profound results. However, it can be challenging to identify which business problems are most amenable to these technologies. In this first module, you'll begin exploring AI and ML as solutions to these problems.
Read more
Select Appropriate Tools
The second module in this course provides an overview of software and hardware tools that are commonly used to implement and/or support AI and machine learning techniques. Even if you won't end up trying every tool out there, it's important to be informed about your options so that you'll make better decisions when it comes time to select tools for your own environment.
Promote Data Privacy and Ethical Practices
As AI and machine learning have the potential to revolutionize business, so too will they bring significant changes to society and the individuals in that society. It's vital that anyone involved in developing such technologies, including practitioners, is prepared to handle the ethical risks that arise. In this module, you'll explore those ethical risks, as well as strategies for mitigating such risks.
Apply What You've Learned
You'll work on a project in which you'll apply your knowledge of the material in this course to practical scenarios.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Helps learners understand advanced concepts, such as deep learning and machine learning, that are transforming industry
Develops skills and knowledge that can drive critical decisions, create innovative products and services, and enable organizations to stay competitive
Provides a strong foundation for learners who are new to AI/ML
Taught by Renée Cummings, who is an experienced professional in the field of AI/ML
Covers ethical and responsible practices in AI/ML, which is becoming increasingly important as these technologies become more widespread
Requires learners to have some prior knowledge of statistics and programming, which may be a barrier for some
Save this course
Save Solve Business Problems with AI and Machine Learning to your list so you can find it easily later:
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Reviews summary
Mixed ai and machine learning course
Learners say this intro business AI and Machine Learning course is good and enjoyable with a nice structure. However, they say that readings are too long and that the instructor relies too heavily on a single textbook.
Content is easy to follow with a good structure.
"content was easy and very well structured"
"Good intro course."
Defines lots of terms.
"All this course is defining terms."
Readings are too long.
"I can read the transcript faster than the audio, so I often ended up putting the video on mute while I read the transcript."
"It's really an effort to overcome the monotony of the speech."
Reads textbooks aloud.
"Teacher reads the content all the time. "
"Without any intention to offend anybody and without being in the possesion of the absolute truth, I can’t see the point of having somebody read a text out loud on the screen."
"I am confident that the written text would be clearer. Just let me download the pdf that she is reading and I would go through it withot having to stand the videos."
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 Solve Business Problems with AI and Machine Learning with these
activities:
Review Artificial Intelligence: A Modern Approach
Show steps
This book will give you a good foundation in the fundamentals of artificial intelligence and machine learning, which will be helpful for your studies in this course.
View
Melania
on Amazon
Show steps
-
Read the first three chapters of the book.
-
Summarize the main ideas in each chapter.
Organize and Summarize Course Materials
Show steps
Supports knowledge retention and understanding by organizing and summarizing course materials.
Show steps
-
Take notes during lectures and while reading course materials.
-
Review notes after each class or study session.
-
Create summaries or outlines of key concepts.
Follow Tutorials on AI Tools and Techniques
Show steps
Provides a guided approach to learning and experimenting with AI tools and techniques.
Browse courses on
AI Tools
Show steps
-
Identify tutorials relevant to course topics (e.g., YouTube channels, online courses).
-
Watch or read through tutorials and follow instructions.
-
Apply what you learn to small projects or practice problems.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Review 'Artificial Intelligence: A Modern Approach'
Show steps
Provides a strong theoretical foundation for understanding the concepts and algorithms in the course.
View
Melania
on Amazon
Show steps
-
Read Chapters 1-3 to gain an overview of AI and its applications.
-
Focus on Chapters 6-8 to understand machine learning techniques and algorithms.
Start a project involving image recognition
Show steps
Starting a project involving image recognition will give you practical experience applying the concepts you learn in this course.
Browse courses on
Image Recognition
Show steps
-
Choose a dataset of images to use.
-
Build a model to recognize the images in the dataset.
-
Evaluate the performance of your model.
Follow a tutorial on how to apply AI/ML to a business problem
Show steps
Following a tutorial on how to apply AI/ML to a business problem will give you practical experience applying the concepts you learn in this course.
Browse courses on
Artificial Intelligence
Show steps
-
Choose a tutorial that is relevant to your interests.
-
Follow the steps in the tutorial.
-
Test the results of your work.
Attend a meetup or conference on AI or ML
Show steps
Attending a meetup or conference on AI or ML will allow you to connect with other professionals in the field and to learn about the latest trends.
Browse courses on
Artificial Intelligence
Show steps
-
Find a meetup or conference on AI or ML that is relevant to your interests.
-
Register for the event.
-
Attend the event and network with other attendees.
Participate in a workshop on AI or ML
Show steps
Participating in a workshop on AI or ML will give you an opportunity to learn from experts in the field and to get hands-on experience with AI/ML technologies.
Browse courses on
Artificial Intelligence
Show steps
-
Find a workshop on AI or ML that is relevant to your interests.
-
Register for the workshop.
-
Participate in the workshop and learn from the experts.
Solve Machine Learning Practice Problems
Show steps
Provides focused practice in applying machine learning concepts and algorithms.
Browse courses on
Machine Learning Algorithms
Show steps
-
Find a platform with machine learning practice problems (e.g., LeetCode, HackerRank).
-
Choose problems aligned with course topics and difficulty level.
-
Attempt to solve problems on your own.
-
Review solutions and identify areas for improvement.
Create a blog post on a topic related to AI or ML
Show steps
Creating a blog post will help you to solidify your understanding of the concepts you learn in this course and to communicate them to others.
Browse courses on
Artificial Intelligence
Show steps
-
Choose a topic related to AI or ML.
-
Research the topic.
-
Write a blog post on the topic.
Contribute to an open-source AI/ML project
Show steps
Contributing to an open-source AI/ML project will give you practical experience working with AI/ML technologies and will help you to build your portfolio.
Browse courses on
Artificial Intelligence
Show steps
-
Find an open-source AI/ML project that is relevant to your interests.
-
Read the project documentation.
-
Contribute to the project by fixing bugs or adding new features.
Build a Simple AI-powered Chatbot
Show steps
Provides hands-on experience in applying AI techniques to solve a practical problem.
Browse courses on
Chatbot
Show steps
-
Choose a chatbot platform (e.g., Dialogflow, Botsify).
-
Design a conversation flow and create training data.
-
Train and deploy the chatbot.
Write a Blog Post on AI Trends
Show steps
Encourages critical thinking and research skills by exploring current developments in AI.
Browse courses on
AI Trends
Show steps
-
Research recent advancements in AI from credible sources.
-
Identify key trends and their implications.
-
Write a well-structured blog post summarizing your findings.
Review Artificial Intelligence: A Modern Approach
Show steps
This book will give you a good foundation in the fundamentals of artificial intelligence and machine learning, which will be helpful for your studies in this course.
View
Melania
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters of the book.
- Summarize the main ideas in each chapter.
Organize and Summarize Course Materials
Show steps
Supports knowledge retention and understanding by organizing and summarizing course materials.
Show steps
Show steps
Show steps
- Take notes during lectures and while reading course materials.
- Review notes after each class or study session.
- Create summaries or outlines of key concepts.
Follow Tutorials on AI Tools and Techniques
Show steps
Provides a guided approach to learning and experimenting with AI tools and techniques.
Browse courses on
AI Tools
Show steps
Show steps
Show steps
- Identify tutorials relevant to course topics (e.g., YouTube channels, online courses).
- Watch or read through tutorials and follow instructions.
- Apply what you learn to small projects or practice problems.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Review 'Artificial Intelligence: A Modern Approach'
Show steps
Provides a strong theoretical foundation for understanding the concepts and algorithms in the course.
View
Melania
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3 to gain an overview of AI and its applications.
- Focus on Chapters 6-8 to understand machine learning techniques and algorithms.
Start a project involving image recognition
Show steps
Starting a project involving image recognition will give you practical experience applying the concepts you learn in this course.
Browse courses on
Image Recognition
Show steps
Show steps
Show steps
- Choose a dataset of images to use.
- Build a model to recognize the images in the dataset.
- Evaluate the performance of your model.
Follow a tutorial on how to apply AI/ML to a business problem
Show steps
Following a tutorial on how to apply AI/ML to a business problem will give you practical experience applying the concepts you learn in this course.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Choose a tutorial that is relevant to your interests.
- Follow the steps in the tutorial.
- Test the results of your work.
Attend a meetup or conference on AI or ML
Show steps
Attending a meetup or conference on AI or ML will allow you to connect with other professionals in the field and to learn about the latest trends.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Find a meetup or conference on AI or ML that is relevant to your interests.
- Register for the event.
- Attend the event and network with other attendees.
Participate in a workshop on AI or ML
Show steps
Participating in a workshop on AI or ML will give you an opportunity to learn from experts in the field and to get hands-on experience with AI/ML technologies.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Find a workshop on AI or ML that is relevant to your interests.
- Register for the workshop.
- Participate in the workshop and learn from the experts.
Solve Machine Learning Practice Problems
Show steps
Provides focused practice in applying machine learning concepts and algorithms.
Browse courses on
Machine Learning Algorithms
Show steps
Show steps
Show steps
- Find a platform with machine learning practice problems (e.g., LeetCode, HackerRank).
- Choose problems aligned with course topics and difficulty level.
- Attempt to solve problems on your own.
- Review solutions and identify areas for improvement.
Create a blog post on a topic related to AI or ML
Show steps
Creating a blog post will help you to solidify your understanding of the concepts you learn in this course and to communicate them to others.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Choose a topic related to AI or ML.
- Research the topic.
- Write a blog post on the topic.
Contribute to an open-source AI/ML project
Show steps
Contributing to an open-source AI/ML project will give you practical experience working with AI/ML technologies and will help you to build your portfolio.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Find an open-source AI/ML project that is relevant to your interests.
- Read the project documentation.
- Contribute to the project by fixing bugs or adding new features.
Build a Simple AI-powered Chatbot
Show steps
Provides hands-on experience in applying AI techniques to solve a practical problem.
Browse courses on
Chatbot
Show steps
Show steps
Show steps
- Choose a chatbot platform (e.g., Dialogflow, Botsify).
- Design a conversation flow and create training data.
- Train and deploy the chatbot.
Write a Blog Post on AI Trends
Show steps
Encourages critical thinking and research skills by exploring current developments in AI.
Browse courses on
AI Trends
Show steps
Show steps
Show steps
- Research recent advancements in AI from credible sources.
- Identify key trends and their implications.
- Write a well-structured blog post summarizing your findings.
Career center
Learners who complete Solve Business Problems with AI and Machine Learning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, deploying, and maintaining machine learning models. They collaborate with data scientists to understand the business problem and translate it into a technical solution. This course helps build a solid foundation in AI/ML technologies. It also provides an overview of tools commonly used to implement and support AI and ML techniques.
AI Engineer
AI Engineer
AI Engineers design, develop, and implement AI systems. They collaborate with data scientists and machine learning engineers to bring AI solutions to life. This course provides an introduction to AI/ML technologies and their applications to business problems. It also promotes the importance of ethics in AI/ML, which is crucial for AI Engineers.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course introduces AI/ML as solutions to business problems, examines AI and ML technologies, provides an overview of machine learning workflow, and promotes the importance of ethics in AI/ML. These topics equip practitioners and professionals with the understanding needed to apply knowledge of AI/ML to solve complex business problems in the role of Data Scientist.
Business Analyst
Business Analyst
Business Analysts identify and analyze business needs and requirements, and design solutions to address those needs. By understanding the business problems that AI/ML can solve, Business Analysts can better identify opportunities to leverage these technologies. This course also covers ethical practices in AI/ML, which is important for Business Analysts to consider when making recommendations.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use analytical techniques to solve complex business problems. This course introduces AI/ML technologies and their applications to business problems. This knowledge can help Operations Research Analysts expand their toolkit and solve problems more efficiently.
Strategy Consultant
Strategy Consultant
Strategy Consultants help organizations develop and implement strategies to achieve their goals. This course provides an overview of business problems suitable for AI/ML solutions. This knowledge can help Strategy Consultants identify opportunities to leverage AI/ML to develop innovative strategies for their clients.
Data Analyst
Data Analyst
Data Analysts collect, transform, and analyze data to extract meaningful insights that inform decision-making. This course introduces practical problems suitable for AI/ML solutions and provides an overview of machine learning workflow. These topics can help Data Analysts understand the potential of AI/ML and how to apply these technologies to business problems.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and services. This course provides an introduction to AI/ML technologies and their applications to business problems. This knowledge can help Product Managers identify opportunities to leverage AI/ML to create innovative products and services.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course introduces AI/ML technologies, their applications, and ethical considerations. This knowledge can be valuable for Quantitative Analysts who want to explore the use of AI/ML in their work.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides an overview of software and hardware tools commonly used to implement AI and ML techniques. While not all Software Engineers will work directly with AI/ML, this knowledge can be valuable for those who do.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course provides an overview of the general workflow involved in machine learning. This knowledge can help Project Managers better understand AI/ML projects and manage them effectively.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks. This course promotes the importance of ethics in AI/ML. This knowledge can help Risk Managers understand the ethical risks associated with AI/ML and develop strategies to mitigate those risks.
Information Technology Manager
Information Technology Manager
Information Technology Managers plan, implement, and manage IT systems and services within an organization. This course provides an overview of ethical practices in AI/ML, which IT Managers should consider when making decisions about AI/ML adoption and implementation.
Data Architect
Data Architect
Data Architects design and manage data systems and infrastructure. This course provides an overview of ethical practices in AI/ML, which Data Architects should consider when designing and managing data systems that support AI/ML applications.
Compliance Manager
Compliance Manager
Compliance Managers ensure that organizations comply with laws and regulations. This course promotes the importance of ethics in AI/ML. This knowledge can help Compliance Managers understand the ethical risks associated with AI/ML and develop strategies to ensure compliance with ethical guidelines.
For more career information including salaries, visit:
OpenCourser.com/course/vpgcb7/solve
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
Solve Business Problems with AI and Machine Learning.
Save
Provides a comprehensive overview of the potential risks and benefits of superintelligence. It great resource for those who want to learn more about the big picture of AI.
Save
Provides a comprehensive overview of the potential impact of artificial intelligence on humanity. It great resource for those who want to learn more about the big picture of AI.
Provides a comprehensive overview of deep learning with Python, including its different libraries and techniques. It great resource for those who want to learn more about the technical aspects of deep learning with Python.
Provides a comprehensive overview of statistical learning, including its different algorithms and techniques. It great resource for those who want to learn more about the technical aspects of statistical learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It great resource for those who want to learn more about the theoretical foundations of machine learning.
Provides a comprehensive overview of deep learning for natural language processing. It great resource for those who want to learn more about the technical aspects of deep learning for NLP.
Provides a comprehensive overview of reinforcement learning, including its different algorithms and techniques. It great resource for those who want to learn more about the technical aspects of reinforcement learning.
Save
Provides a comprehensive overview of deep learning, including its different architectures and techniques. It great resource for those who want to learn more about the technical aspects of deep learning.
Provides a comprehensive overview of the ethical issues that arise with the development and use of algorithms. It great resource for those who want to learn more about the ethical implications of AI.
Provides a comprehensive overview of machine learning, including its different algorithms and techniques. It great starting point for those who are new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vpgcb7/solve
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Effort
3 weeks of study, 1–3 hours per week
Level
Intermediate
Via
Coursera
Institution
CertNexus
Instructor
Renée Cummings
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
Bahasa Indonesia
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қазақша
This course belongs to a
collection
called
CertNexus Certified Artificial Intelligence Practitioner. It's comprised of five courses:
- Preparing for Your CertNexus Certification Exam
- Solve Business Problems with AI and Machine Learning (viewing)
- Follow a Machine Learning Workflow
- Build Decision Trees, SVMs, and Artificial Neural Networks
- Build Regression, Classification, and Clustering Models
Good to know
Helps learners understand advanced concepts, such as deep learning and machine learning, that are transforming industry
Develops skills and knowledge that can drive critical decisions, create innovative products and services, and enable organizations to stay competitive
Provides a strong foundation for learners who are new to AI/ML
Taught by Renée Cummings, who is an experienced professional in the field of AI/ML
Covers ethical and responsible practices in AI/ML, which is becoming increasingly important as these technologies become more widespread
Requires learners to have some prior knowledge of statistics and programming, which may be a barrier for some
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