Online Course popular free
Mathematics

Acquire the fundamental math skills needed to become a data scientist and work on machine learning models and AI

4.9

808 reviews on
23498 students already have enrolled
  • 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:

Basic

Duration:

1 hour
  • Lessons (1 hour)
  • Practice exams (9 minutes)

CPE credits:

3
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

  • Apply foundational math skills essential for data science and ML.
  • Become familiar with key linear algebra terms and ideas.
  • Build a solid foundation in both calculus and linear algebra.
  • Operate confidently with scalars, vectors, matrices, and tensors.
  • Leverage theoretical math concepts directly in practical contexts.

Topics & tools

theorymathematicslinear algebravectorsmatriciestensorsmath & statisticspython

Your instructor

Course OVERVIEW

Description

CPE Credits: 3 Field of Study: Specialized Knowledge
Delivery Method: QAS Self Study
Mathematics is a broad subject, but there are two specific math subfields that are heavily employed in data science – calculus and linear algebra. Therefore, to thrive in data science, you need to build a solid foundation – acquire the numerical tools that will help you understand even the most complicated machine learning algorithms. The Math for data science course is here to help you do that. It equips you with the right tools to continue your data science journey with confidence and clarity. Through this essential math for data science training you will gain a comprehensive understanding of the mathematical principles that form the basis of data science. Many people are afraid to learn math, and some might think that math for data science will be even more complicated. However, this isn’t necessarily true. It really depends how you want to learn math for data science. Are you going to read hundreds of pages of theory from a textbook? Or you will watch a collection of random YouTube videos? We have a better solution for you. Our data science math course is the perfect tool you have been looking for. It is concise, to the point, and easy-to-understand. Through step-by-step dynamic and beautifully animated pre-scripted tutorials, we ensure that you will have the best learning experience. We rely on storytelling and real-world examples to ensure you will get hooked and will complete the math for data science training. The interactive exercises in our mathematics course will ensure that you have a chance to practice what has been explained in the lessons hands-on. This self-paced online course is the best way to learn math for data science and ensure you obtain the desired results. This training is suitable for university students who need math for their studies. It is also highly recommended for graduates and young professionals who want to learn data science and pursue a career in the fields of AI and machine learning. The course is beginner-friendly, but it still requires your knowledge of high school math concepts. Join us on a journey that will introduce you to linear algebra, calculus, matrices, and tensors. Gain the math skills that will allow you to understand how machine learning and AI models have been built. By completing the course, you will be able to work with various math operators and comprehend how linear algebra is used in practice. How is this math for data science course different than the rest? 1. Content quality This is a well-structured math course that aims to make complex topics easy to understand. In a few hours, you will be able to build a solid foundation of linear algebra and calculus skills that will prove invaluable throughout your data science and AI learning journey. The course curriculum is well-organized and contains video lectures that are pre-scripted, to the point, dynamic, and well engaging. Our platform offers numerous interactive math exercises that ensure high quality learning with hands-on exercises. 2. Downloadable materials Gain access to valuable downloadable resources you can always use as a reference. The math for data science course comes with a full set of materials – complete linear algebra course notes, practice exercises, and a course exam – everything is included inside. 3. Certificate of achievement If you compete the Math for data science course and pass successfully its course exam, you will be awarded a verifiable certificate of achievement, which is a testament to your dedication and hard work. Click the ‘Buy now’ button and start this amazing learning journey today! Make an investment to acquire linear algebra and calculus skills that will ensure smooth sailing on your data science journey.

Prerequisites

  • A basic knowledge of high school math is required

Advanced preparation

  • None

Curriculum

12 lessons 38 exercises 2 exams

Free preview

Welcome to the course

1.1 Welcome to the course

4 min

Scalars and Vectors

1.3 Scalars and Vectors

3 min

Linear Algebra and Geometry

1.5 Linear Algebra and Geometry

3 min

Setting up the Environment

1.7 Setting up the Environment

1 min

Scalars, Vectors, and Matrices as Python Arrays

1.8 Scalars, Vectors, and Matrices as Python Arrays

5 min

What is a Tensor?

1.11 What is a Tensor?

3 min

Start for free

9 in 10

people walk away career-ready

with practical data and AI skills.

96%

of our students recommend

365 Data Science.

9 in 10

of our graduates landed a new AI & data job

after enrollment

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
A LinkedIn profile mockup on a mobile screen showing Parker Maxwell, a Certified Data Analyst, with credentials from 365 Data Science listed under Licenses & Certification. A 365 Data Science Certificate of Achievement awarded to Parker Maxwell for completing the Data Analyst career track, featuring accreditation badges and a gold “Verified Certificate” seal.

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

A collage of student testimonials from 365 Data Science learners, featuring profile photos, names, job titles, and quotes or video play icons, showcasing diverse backgrounds and successful career transitions into AI and data science roles.