Solve Business Problems with AI and Machine Learning
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Solve Business Problems with AI and Machine Learning
This course is part of CertNexus Certified Artificial Intelligence Practitioner Professional Certificate
Instructor: Stacey McBrine
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What you'll learn
Identify appropriate applications of AI and machine learning within a given business situation.
Formulate a machine learning approach to solve specific business problems.
Select appropriate tools to solve given machine learning problems.
Protect data privacy and promote ethical practices when developing and deploying AI and machine learning projects.
Skills you'll gain
- Project Implementation
- Artificial Intelligence
- Compliance Training
- Regulatory Compliance
- Business Solutions
- Applied Machine Learning
- Compliance Management
- Data Ethics
- Machine Learning
- Ethical Standards And Conduct
- Responsible AI
- Business Ethics
- AI literacy
- Machine Learning Software
- Artificial Intelligence and Machine Learning (AI/ML)
- Data-Driven Decision-Making
- Machine Learning Methods
- Model Evaluation
- AI Product Strategy
- Model Training
Details to know
See how employees at top companies are mastering in-demand skills
Build your Machine Learning expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from CertNexus
There are 4 modules in this course
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.
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.
What's included
18 videos4 readings1 assignment4 peer reviews1 discussion prompt
18 videos•Total 60 minutes
- CAIP Specialization Introduction•4 minutes
- Solve Business Problems with AI and Machine Learning Course Introduction•2 minutes
- Identify Data-Driven Emerging Technologies Module Introduction•1 minute
- The Data Hierarchy•3 minutes
- Big Data•3 minutes
- Data Mining•3 minutes
- Applied AI and ML in Business•7 minutes
- Appropriate Business Problems•5 minutes
- Challenges of AI/ML•4 minutes
- Machine Learning Model•1 minute
- Machine Learning Workflow•2 minutes
- Useful Skillsets•4 minutes
- Concept Drift and Transfer Learning•3 minutes
- Problem Formulation•5 minutes
- Differences Between Traditional Programming and Machine Learning•3 minutes
- Differences Between Supervised and Unsupervised Learning•3 minutes
- Randomness and Uncertainty•5 minutes
- Machine Learning Outcomes•3 minutes
4 readings•Total 17 minutes
- Overview•2 minutes
- Get help and meet other learners. Join your Community!•5 minutes
- Guidelines for Following the Machine Learning Workflow•5 minutes
- Guidelines for Formulating a Machine Learning Outcome •5 minutes
1 assignment•Total 30 minutes
- Applying AI and ML to Business Problems•30 minutes
4 peer reviews•Total 125 minutes
- Identifying Appropriate Business Applications for AI and ML•30 minutes
- Planning the Machine Learning Workflow•30 minutes
- Framing a Machine Learning Problem•45 minutes
- Selecting a Machine Learning Outcome•20 minutes
1 discussion prompt•Total 5 minutes
- Reflect on What You've Learned•5 minutes
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.
What's included
4 videos6 readings2 assignments1 discussion prompt
4 videos•Total 8 minutes
- Select Appropriate Tools Module Introduction•1 minute
- New Tools and Technologies•1 minute
- Hardware Requirements•4 minutes
- Cloud Platforms•2 minutes
6 readings•Total 52 minutes
- Overview•2 minutes
- Open Source AI Tools•15 minutes
- Proprietary AI Tools•15 minutes
- GPU Platforms•5 minutes
- Guidelines for Configuring a Machine Learning Toolset•5 minutes
- Machine Learning Tools•10 minutes
2 assignments•Total 45 minutes
- Selecting Appropriate Tools•30 minutes
- Open Source and Proprietary AI Tools Quiz•15 minutes
1 discussion prompt•Total 5 minutes
- Reflect on What You've Learned•5 minutes
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.
What's included
16 videos5 readings1 assignment4 peer reviews1 discussion prompt
16 videos•Total 56 minutes
- Promote Data Privacy and Ethical Practices Module Introduction•2 minutes
- Data Protection•4 minutes
- Data Privacy Laws•3 minutes
- Privacy by Design•3 minutes
- Data Privacy Principles at Odds with Machine Learning•3 minutes
- Compliance with Data Privacy Laws and Standards•5 minutes
- Data Sharing and Privacy•3 minutes
- The Big Data Challenge•3 minutes
- Preconceived Notions•2 minutes
- The Black Box Challenge•3 minutes
- Bias, Prejudice, and Discrimination•5 minutes
- Ethics in NLP•2 minutes
- Use of Data for Unintended Purposes•2 minutes
- Intellectual Property•4 minutes
- Humanitarian Principles•6 minutes
- Asilomar AI Principles•5 minutes
5 readings•Total 32 minutes
- Overview•2 minutes
- Guidelines for Protecting Data Privacy•10 minutes
- Guidelines for Promoting Ethical Practices•3 minutes
- Privacy and Data Governance for AI and ML•2 minutes
- Guidelines for Establishing Policies Covering Data Privacy and Ethics•15 minutes
1 assignment•Total 30 minutes
- Promoting Data Privacy and Ethical Practices•30 minutes
4 peer reviews•Total 90 minutes
- Complying with Applicable Laws and Standards•30 minutes
- Protecting Data Privacy•20 minutes
- Promoting Ethical Practices•20 minutes
- Establishing Policies Covering Data Privacy and Ethics•20 minutes
1 discussion prompt•Total 5 minutes
- Reflect on What You've Learned•5 minutes
You'll work on a project in which you'll apply your knowledge of the material in this course to practical scenarios.
What's included
1 peer review
1 peer review•Total 120 minutes
- AI Project Outline•120 minutes
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Reviewed on Jun 1, 2021
I had fun and i enjoyed it and i am hungry for more!
Reviewed on Oct 1, 2023
content was easy and very well structured, Presentation was good, looking forward to learn more courses
Reviewed on Apr 13, 2025
First proper course on AI and ML. Love the fact that the videos are super short and digestible. Managed to complete 5 modules of the first course with ease.
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