TOP Online courses in statistics
Miscellaneous / / November 27, 2023
Generalized Linear Models
This program will help you learn how to build models with random factors for quantities with different types of distributions. To make it easier to master the course materials, you will need a basic understanding of linear models (general and generalized), basic knowledge of R and the ability to create simple .html documents using rmarkdown and knitr.
4,2
Business calculations and advanced data analysis in spreadsheets
Trainings, seminars and certification. The program volume is 32 hours. The goal of the program is to acquire theoretical knowledge in the field of functionality of calculations and analysis information, as well as practical skills in analyzing large volumes of data, statistical data processing, solving optimization problems, generating macros for the purpose of using them for frequently repeated operations and automating work using spreadsheets MS Excel.
Part-time study
2,7
Mixed Linear Models
This course is suitable for people who need to analyze data in which observations are not independent of each other (for example, families, repeated measures, etc.). The course is designed for those who have mastered the basic techniques of regression analysis using the R language, are familiar with the maximum likelihood method and generalized linear models.
4,2
Linear models with discrete predictors
This course is aimed at people who want to learn how to describe patterns of behavior of quantitative quantities depending on discrete factors. The course is designed for those who have mastered the basic techniques of regression analysis using the R language.
4,2
Introduction to Data Science
Data science includes a wide range of approaches and methods for collecting, processing, analyzing and visualizing data sets of any size. A separate practically important area of this science is working with big data using new principles mathematical and computational modeling, when classical methods stop working due to their impossibility scaling. This course is designed to help the student learn the basics of the subject area through formulation and solving typical problems that a data science researcher may encounter in his or her work. To teach the student to solve such problems, the authors of the course provide the student with the necessary theoretical minimum and show how to use the tool base in practice.
4,2
Econometrics: time series analysis
The purpose of the course is to train students in modern methods of econometric modeling of univariate time series. The objectives of the course are: to develop students’ understanding of the methodology of empirical research and the possibilities of econometric models and the limits of their application, as well as developing skills in working with real economic data.
4,2
Data Analyst from scratch to Junior
You will learn to solve business problems using data. First, get the necessary training, improve your mathematics and statistics, and then study SQL, Python, Power BI and in a year you will become a data analyst.
4,2
Math statistics
The course introduces students to the main sections of mathematical statistics: descriptive statistics, interval estimation, statistical hypothesis testing, regression analysis and correlation analysis.
4
Probability theory is the science of chance. Part 2
In the second part of the course "Probability Theory - the science of randomness" continuous probability spaces are considered, which significantly expands the analytical capabilities of the theory and allows you to build interesting models using more advanced mathematical apparatus.
3,8
Big data processing and analysis
The program is dedicated to technologies for working with large volumes of data. Currently, ICT has changed our entire lives - both personal and industrial spheres. First of all, this is due to the accumulation in all areas of human detail of huge amounts of data that need to be able to find, extract, structure, save in a compact form, quickly find the necessary elements, aggregate and analyze. Data analysis can help solve many professional problems, such as: what is the expected demand for a particular product? When was this demand greatest? What are the trends in price changes in the market? Etc. Data science deals with a wide range of topics.
4,2
Macroeconomics
The originality of the proposed Macroeconomics course lies in the fact that it combines elements of introductory and intermediate levels. It is aimed at master's students who do not have a basic economic education, who will have to study advanced macroeconomics. Master's students who have already studied Macroeconomics as an undergraduate with the help of this course will be able to refresh their basic competencies in this discipline.
4,2
Linear algebra
A basic online course in linear algebra, containing all the key applications and algorithms for statistics and multivariate analysis, although not always containing detailed proofs.
4,2