Online Course – Certified Data Professional Internship: Google Essential Math Methodology

Learn the mathematical foundations of data science. Review key concepts in algebra, infinitesimal calculus, linear algebra, and numerical analysis, which are critical to data science.

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קורס אונליין - התמחות מקצועית מוסמכת בנתונים: מתודולוגיית מתמטיקה חיונית של Google

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Basic understanding of mathematics in data science
  • Knowledge of algebra
  • Knowledge of arithmetic
  • Knowledge of linear algebra
  • Ability to perform relevant numerical analyses
  • Preparation for the Statistical Model for Data Science Applications course
  • Preparation for a Master’s Degree Program in Data Science

What you will learn in the course

Courses for which the course is suitable

  • Data Scientist
  • Data Analyst
  • Data programmer
  • Statistician
  • Data scientist
  • Data Engineer
  • Data Project Manager
  • Statistical Modeling Expert
  • Master’s student in data science

Internship – Series of 3 courses

Data science is rapidly evolving and creating career opportunities in various fields. This specialization is designed for learners who are interested in starting a career in data science.

Learners will receive a concise overview of the fundamental mathematics required in data science. Topics include:

  • algebra
  • invoice
  • Linear algebra
  • Relevant numerical analyses

Fast Track to Data Science is also excellent preparation for students preparing to complete the Master of Science in Data Science program at CU Boulder.

This specialization prepares learners for success in the Statistical Modeling for Data Science Applications course, which is part of the Master of Science in Data Science (MS-DS) program at CU Boulder.

Learners will take tests in each course to test their understanding of the content as they progress. This specialization does not include projects or final exams, as it is intended to be a quick review of the content to prepare learners for the higher-level mathematics required in data science.

Details of the courses that make up the specialization

Algebra and Differential Calculus for Data Science

Course 1
8 hours
4.5 (223 ratings)

Course Details

What will you learn?

  • Practice working with logarithmic properties and how logarithmic functions behave graphically.
  • Know the difference between a continuous function and a non-continuous function.
  • Strengthen your understanding of what calculating the derivative does.
  • Understanding how to use derivatives to graph functions.

Skills you will develop

  • Category: Integrals
  • Category: Matrix algebra
  • Category: Numerical Analysis
  • Category: Algebra
  • Category: Derivatives

Linear algebra is essential for data science

Course 2
7 hours
4.4 (152 ratings)

Course Details

What will you learn?

  • Solve real-world problems using the basic concept of matrices.
  • Recognize what a matrix represents in n-dimensional space.
  • Identify key features of each system of equations.
  • Demonstrate your understanding of low-dimensional projections.

Skills you will develop

  • Category: Integrals
  • Category: Matrix algebra
  • Category: Numerical Analysis
  • Category: Derivatives
  • Category: Algebra

Integral Calculus and Numerical Analysis for Data Science

Course 3
3 hours
4.6 (91 ratings)

Course Details

What will you learn?

  • Practice integration by parts for more complex problems.
  • Identify how a crossing works after being given an initial guess.
  • Diagonalization of a matrix by hand.
  • Calculate the partial derivatives of a function.

Skills you will develop

  • Category: Integrals
  • Category: Partial derivative
  • Category: Root Finding
  • Category: Singular Value Derivation (SVD)
  • Category: Matrix diagonalization

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