Solve Business Problems with AI and Machine Learning

This course is part of CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

Instructor: Stacey McBrine

Access provided by Universitas Indonesia

13,004 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

111 reviews

Intermediate level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

111 reviews

Intermediate level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

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

Details to know

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Assessments

4 assignments¹

AI Graded see disclaimer

Taught in English

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Build your Machine Learning expertise

This course is part of the CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

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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

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Instructor

Instructor ratings

(35 ratings)

Stacey McBrine

8 Courses 25,009 learners

Offered by

CertNexus

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Showing 3 of 111

Reviewed on Jun 1, 2021

I had fun and i enjoyed it and i am hungry for more!

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.

Reviewed on Dec 27, 2025

Excellent course. A lot of useful material that you will be able to use in you work.

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