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Solve Business Problems with AI and Machine Learning
  • Level Professional
  • Duration 11 hours
  • Course by CertNexus
  • Offered by

About

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.

Modules

Overview

    • 3 Videos
    • 2 Readings
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3 Videos

  • CAIP Specialization Introduction
  • Solve Business Problems with AI and Machine Learning Course Introduction
  • Identify Data-Driven Emerging Technologies Module Introduction

2 Readings

  • Overview
  • Get help and meet other learners. Join your Community!

Identify AI and ML Solutions for Business Problems

    • 6 Videos
    • 1 PeerReview
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1 Peer Review

  • Identifying Appropriate Business Applications for AI and ML

6 Videos

  • The Data Hierarchy
  • Big Data
  • Data Mining
  • Applied AI and ML in Business
  • Appropriate Business Problems
  • Challenges of AI/ML

Follow a Machine Learning Workflow

    • 4 Videos
    • 1 Readings
    • 1 PeerReview
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1 Peer Review

  • Planning the Machine Learning Workflow

4 Videos

  • Machine Learning Model
  • Machine Learning Workflow
  • Useful Skillsets
  • Concept Drift and Transfer Learning

1 Readings

  • Guidelines for Following the Machine Learning Workflow

Formulate a Machine Learning Problem

    • 5 Videos
    • 1 Readings
    • 2 PeerReview
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2 Peer Review

  • Framing a Machine Learning Problem
  • Selecting a Machine Learning Outcome

5 Videos

  • Problem Formulation
  • Differences Between Traditional Programming and Machine Learning
  • Differences Between Supervised and Unsupervised Learning
  • Randomness and Uncertainty
  • Machine Learning Outcomes

1 Readings

  • Guidelines for Formulating a Machine Learning Outcome

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Applying AI and ML to Business Problems

1 Discussions

  • Reflect on What You've Learned

Overview

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Select Appropriate Tools Module Introduction

1 Readings

  • Overview

AI and ML Toolsets

    • 3 Videos
    • 5 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Open Source and Proprietary AI Tools Quiz

3 Videos

  • New Tools and Technologies
  • Hardware Requirements
  • Cloud Platforms

5 Readings

  • Open Source AI Tools
  • Proprietary AI Tools
  • GPU Platforms
  • Guidelines for Configuring a Machine Learning Toolset
  • Machine Learning Tools

Evaluate What You’ve Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Selecting Appropriate Tools

1 Discussions

  • Reflect on What You've Learned

Overview

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Promote Data Privacy and Ethical Practices Module Introduction

1 Readings

  • Overview

Protect Data Privacy

    • 7 Videos
    • 1 Readings
    • 2 PeerReview
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2 Peer Review

  • Complying with Applicable Laws and Standards
  • Protecting Data Privacy

7 Videos

  • Data Protection
  • Data Privacy Laws
  • Privacy by Design
  • Data Privacy Principles at Odds with Machine Learning
  • Compliance with Data Privacy Laws and Standards
  • Data Sharing and Privacy
  • The Big Data Challenge

1 Readings

  • Guidelines for Protecting Data Privacy

Promote Ethical Practices

    • 5 Videos
    • 1 Readings
    • 1 PeerReview
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1 Peer Review

  • Promoting Ethical Practices

5 Videos

  • Preconceived Notions
  • The Black Box Challenge
  • Bias, Prejudice, and Discrimination
  • Ethics in NLP
  • Use of Data for Unintended Purposes

1 Readings

  • Guidelines for Promoting Ethical Practices

Establish Data Privacy and Ethics Policies

    • 3 Videos
    • 2 Readings
    • 1 PeerReview
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1 Peer Review

  • Establishing Policies Covering Data Privacy and Ethics

3 Videos

  • Intellectual Property
  • Humanitarian Principles
  • Asilomar AI Principles

2 Readings

  • Privacy and Data Governance for AI and ML
  • Guidelines for Establishing Policies Covering Data Privacy and Ethics

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Promoting Data Privacy and Ethical Practices

1 Discussions

  • Reflect on What You've Learned

Project

    • 1 PeerReview
Show info about module content

1 Peer Review

  • AI Project Outline

Auto Summary

Dive into the world of AI and Machine Learning with this professional course designed for data science enthusiasts. Led by Coursera, this entry-level course focuses on solving business problems using AI/ML, covering essential technologies, workflows, and ethical considerations. Spanning 660 minutes, it forms part of the Certified Artificial Intelligence Practitioner (CAIP) certification. Subscription options include Starter and Professional, making it ideal for professionals seeking to integrate AI/ML into innovative business solutions.

Renée Cummings
Instructor

Renée Cummings