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Solve Business Problems with AI and Machine Learning

4.3 Filled star Filled star Filled star Filled star Empty star
Based on 78 ratings
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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.

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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.

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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.
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Traffic lights

Read about what's good
what should give you pause
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

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Reviews summary

Ai/ml for business strategy overview

According to students, this course offers a largely positive and accessible entry point into the application of AI and Machine Learning for business. Learners frequently praise its strong focus on strategic thinking and the 'why' behind AI/ML, making it particularly valuable for business professionals and those without a deep technical background. The course effectively covers how to identify business problems solvable by AI, provides an overview of tools, and crucially emphasizes ethical considerations. While some advanced learners found it too foundational, the consistent feedback highlights its utility as a clear, non-technical introduction that grounds AI concepts in practical business scenarios.
Offers a helpful survey of common AI/ML tools.
"The segment on selecting appropriate tools gave me a much clearer picture of the AI/ML ecosystem."
"It was helpful to learn about the various software and hardware options without getting bogged down in specifics."
"I appreciated the general knowledge about different tools, even if I didn't try them all myself."
Perfect for business roles or those new to AI/ML.
"This is a perfect entry point into AI/ML for someone with a non-technical background like mine."
"I needed a course that was less about coding and more about strategic understanding, and this delivered."
"For business leaders trying to grasp AI's potential, this course offers a clear and concise overview without overwhelming technical jargon."
Provides crucial insights into ethical AI/ML practices.
"The module on ethics in AI/ML was incredibly insightful and a topic often overlooked in similar courses."
"I now feel better equipped to handle the ethical risks that arise when developing and deploying AI technologies."
"Understanding data privacy and ethical considerations was a vital takeaway for me."
Connects AI/ML to real-world business challenges.
"This course helped me understand how AI and ML can actually solve problems in my organization, not just what they are."
"I really appreciated the emphasis on the 'why' of AI/ML, and how to identify business problems amenable to these technologies."
"As a manager, I found the strategic approach to AI application incredibly relevant to my work."
Conceptual overview, not hands-on coding focused.
"I was hoping for more hands-on coding or specific tool walkthroughs, but it was mostly conceptual and high-level."
"For those with a technical background, the course might feel a bit too introductory and lacks deep dives into implementation."
"It's a great overview, but don't expect to become an AI/ML practitioner from this course alone; it's truly foundational."

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
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
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
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'
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
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
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
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
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
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
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
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
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
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.

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 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.
See salaries and explore the career path for Machine Learning 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.
See salaries and explore the career path for AI Engineer
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.
See salaries and explore the career path for Operations Research Analyst
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.
See salaries and explore the career path for Data Scientist
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.
See salaries and explore the career path for Business 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.
See salaries and explore the career path for Quantitative 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.
See salaries and explore the career path for Data Analyst
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.
See salaries and explore the career path for Product Manager
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.
See salaries and explore the career path for Strategy Consultant
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.
See salaries and explore the career path for Software Engineer
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.
See salaries and explore the career path for Compliance Manager
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.
See salaries and explore the career path for Data Architect
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.
See salaries and explore the career path for Project 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.
See salaries and explore the career path for Information Technology 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.
See salaries and explore the career path for Risk Manager

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.
Cover image
Deep Utopia
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.
Deep Utopia: Life and Meaning in a Solved World
Hardcover
$$
Deep Utopia: Life and Meaning in a Solved World
Kindle Edition
$
Cover image
Life 3.0
Save
Provides a comprehensive overview of the potential impact of artificial intelligence on humanity. It great resource for those who want to learn more about the big picture of AI.
Life 3.0: Being Human in the Age of Artificial...
Paperback
$$
(Español) Vida 3.0/Life 3.0: Being Human in the Age of...
Paperback
$$
Our Mathematical Universe & Life 3.0 Being Human in...
Paperback
$$$
(Deutsch) Leben 3.0: Mensch sein im Zeitalter Künstlicher...
Kindle Edition
$$
Life 3.0 (Lead Title)
Hardcover
$$
(中文) Life 3.0: being human in the age of artificial...
Hardcover
$$
Life 3.0: mens zijn in het tijdperk van kunstmatige...
Paperback
$$
(Português) Life 3.0 Ser-se Humano na Era da Inteligência...
Paperback
$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive overview of deep learning with Python, including its different libraries and techniques. It great resource for those who want to learn more about the technical aspects of deep learning with Python.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive overview of statistical learning, including its different algorithms and techniques. It great resource for those who want to learn more about the technical aspects of statistical learning.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Probabilistic Machine Learning
Save
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.
Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Cover image
Cross-Lingual Word Embeddings
Save
Provides a comprehensive overview of deep learning for natural language processing. It great resource for those who want to learn more about the technical aspects of deep learning for NLP.
Cross-Lingual Word Embeddings (Synthesis Lectures...
Paperback
$$
Cover image
Reinforcement Learning, second edition
Save
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.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
Deep 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.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
The Ethical Algorithm
Save
Provides a comprehensive overview of the ethical issues that arise with the development and use of algorithms. It great resource for those who want to learn more about the ethical implications of AI.
The Ethical Algorithm: The Science of Socially...
Hardcover
$$
(Español) El algoritmo ético. La ciencia del diseño de...
Kindle Edition
$$
Cover image
Data Analytics & Visualization All-in-One For...
Save
Provides a comprehensive overview of machine learning, including its different algorithms and techniques. It great starting point for those who are new to the field.
Data Analytics & Visualization All-in-One For...
Paperback
$$
Data Analytics & Visualization All-in-One For...
Kindle Edition
$$

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Course image
Rating
4.3 Filled star Filled star Filled star Filled star Empty star
Effort
11 hours to complete
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 ไทย қазақша
This course belongs to a collection called CertNexus Certified Artificial Intelligence Practitioner. It's comprised of five courses:
  1. Build Regression, Classification, and Clustering Models
  2. Build Decision Trees, SVMs, and Artificial Neural Networks
  3. Solve Business Problems with AI and Machine Learning (viewing)
  4. Follow a Machine Learning Workflow
  5. Preparing for Your CertNexus Certification Exam
Traffic lights
Read about what's good
what should give you pause
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
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