Mathematics

with Iliya Valchanov
4.8/5
(2,544)

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

1 hour of content 21775 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 1 hour of content
  • 33 Interactive exercises
  • 9 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

Mathematics

A course by Iliya Valchanov

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 1 hour of content
  • 33 Interactive exercises
  • 9 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 1 hour of content
  • 33 Interactive exercises
  • 9 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

What You Learn

  • Acquire foundational math for data science knowledge
  • Become familiar with key linear algebra terms and ideas
  • Build a solid foundation when it comes to calculus and linear algebra
  • Learn to operate with scalars, vectors, matrices, and tensors
  • Apply theoretical math knowledge into practice
  • Understand why linear algebra is useful

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

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.

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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

Curriculum

  • 1. Introduction to Linear Algebra
    12 Lessons 52 Min

    In this section, you'll learn the basics of linear algebra, including scalars, vectors, matrices, and tensors. We'll cover essential operations such as addition, subtraction, transposition, and dot products. You'll also explore the relationship between linear algebra and geometry, and see how to implement these concepts using Python. Finally, we'll discuss the practical applications of linear algebra.

    Welcome to the course
    4 min
    Scalars and Vectors
    3 min
    Linear Algebra and Geometry
    3 min
    Setting up the Environment Read now
    1 min
    Scalars, Vectors, and Matrices as Python Arrays
    5 min
    What is a Tensor?
    3 min
    Adding and Subtraction
    4 min
    Errors when Adding Matrices
    2 min
    Transpose of a Matrix
    5 min
    Dot Product
    4 min
    Dot Product of Matrices
    8 min
    Why is Linear Algebra Useful
    10 min

Topics

TheoryMathematicsLinear AlgebraVectorsMatriciesTensors

Tools & Technologies

python

Course Requirements

  • A basic knowledge of high school math is required

Who Should Take This Course?

Level of difficulty: Beginner

  • People who want to improve their math for data science
  • Aspiring data analysts, data scientists, business analysts
  • Graduate students who need linear algebra and calculus for their studies

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Exams and certification

Meet Your Instructor

Iliya Valchanov

Iliya Valchanov

Co-founder at

7 Courses

26815 Reviews

420365 Students

Iliya Valchanov is a co-founder of 365 Data Science and 3veta. He is a Finance graduate with a wide range of expertise in the fields of mathematics, statistics, programming, machine learning, and deep learning. In his courses, Iliya shares his extensive experience in predictive modeling, complex analysis techniques, and optimization algorithms. He has a BA in International Economics, Management and Finance from Bocconi University, where he was Founder and President of the Bocconi Students Mathematics and Logics Association. In 2016, he created his first online course (Statistics) and realized he enjoyed the process of content creation so much that he co-founded 365 Data Science together with a group of friends from university.

What Our Learners Say

02.12.2024

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