Online Course free
The Machine Learning Algorithms A-Z

Master the core concepts of popular ML algorithms: understand when and how to apply different machine learning techniques effectively

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  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Advanced

Duration:

5 hours
  • Lessons (5 hours)

CPE credits:

0.5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited:

certificate

What You Learn

  • Acquire ML skills that connect theory with practical application.
  • Understand the strengths and limitations of ML models.
  • Select the optimal algorithm for specific use cases.
  • Gain business intuition to identify ML-appropriate problems.
  • Boost your career with in-demand machine learning expertise.

Topics & tools

random forestxgboostk nearest neighborshierarchical clusteringgradient boosted treesgradient descentk-means clusteringsupport vector machinesmachine learningnaïve bayescollaborative filteringartificial intelligencedecision treesmachine and deep learningpython

Your instructor

Course OVERVIEW

Description

CPE Credits: 0.5 Field of Study: Information Technology
Delivery Method: QAS Self Study
Looking to break into machine learning? Need to review the ins and outs of each algorithm? Preparing for an interview? Curious to see how these algorithms are applied to business? As ML practitioners, the true value of ML is not in memorizing complicated formulas. It’s not using the latest, greatest deep learning architecture. It’s knowing when to use an algorithm and how to maximize the impact of that model. It’s knowing how to use them to solve REAL business problems. The true value of ML is not ML. It’s solving important business problems. Whether you need to build a forecasting model that forms the backbone of the ads business, builld a recommender system powering millions of purchases or build a fraud detection system that catches bad apples, this course will arm you with both the ML knowledge AND the know-how on how to apply it to your business problem. We don’t want you to leave this course just knowing ML. We want you to leave this course to leave as ML practitioners.

Prerequisites

  • Basic understanding of machine learning concepts.

Curriculum

189 lessons 106 exercises 1 exam

Free preview

Introduction

1.1 Introduction

2 min

ML Algorithms course - GitHub repository

1.2 ML Algorithms course - GitHub repository

1 min

How to Use this Course

1.3 How to Use this Course

1 min

Types of ML Problems

1.4 Types of ML Problems

1 min

Additional Resources

1.6 Additional Resources

1 min

Linear Regression

2.1 Linear Regression

1 min

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ACCREDITED certificates

Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners
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How it WORKS

  • Lessons
  • Exercises
  • Projects
  • Practice Exams
  • AI Mock Interviews

Lessons

Learn through short, simple lessons—no prior experience in AI or data science needed.

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Exercises

Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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Projects

Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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Practice Exams

Track your progress and solidify your knowledge with regular practice exams.

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AI Mock Interviews

Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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Student REVIEWS

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