The course very gradually from simple to complex immerses professionals from non-technical sciences (management, business, humanities, linguists, psychologists, sociologists, culturologists, economists, political scientists, criminologists, etc.) in the exciting digital world of statistics and probability - and will help to easily navigate it, use and not be afraid.

The course is based on the most modern materials, which were read at MBA programs and used in various projects (marketing and sociological research, personnel research, opinion polls, development of psychodiagnostic tools and tests, analysis and forecasting, reorganizations, staffing, remuneration, etc.).

The material is intended for a wide range of students specializing in data processing both humanitarian and socio-economic (management, business, marketing, sociology, psychology, forensics....) and engineering and natural professions (biology, medicine, IT, physics...). A very engaging course about numbers and data that seem so boring, bland and incomprehensible to many non-technical professionals.

Who this course is for:
For those who need a chance to get a "taste and feel" of the seemingly so unimaginably complex and incomprehensible world of numbers and statistical analysis
The course is designed for anyone who wants to learn how to work with data - whether you are a beginner eager to learn statistics or a professional who wants to systematize knowledge or refresh your memory.
Professionals and experts from non-technical sciences (humanities, psychologists, sociologists, culturologists, economists, political scientists, etc.).
The analysis methods covered in the course are universal and suitable for computer science, industry, quality assessment, risk prediction, medicine, physics, chemistry, pharmacology, biomedicine, biotechnology, genetics, etc.
From managers of organizations or departments working with large amounts of data - and to scientists, teachers and students from various disciplines

What you will learn
Combine business and professional intuition with data analysis, hypothesis building and testing
Modern methods of statistical analysis in practice and real data
Find and see hidden patterns in data
Analyze large volumes (arrays) of data
Make probabilistic predictions and build predictive models
Extract knowledge and information from numbers to make decisions

Course content 12 sections - 83 lectures - Total duration 4 h 36 min