This beginner-friendly course introduces the fundamental concepts of probability theory and statistics, focusing on both descriptive and inferential methods. Designed for individuals with little to no prior experience in statistics, it serves as a foundation for further studies in data analysis across various fields, including bioinformatics. The curriculum emphasizes practical applications, enabling students to summarize data, make data-driven decisions, and understand the principles behind statistical inference. This course is particularly beneficial for those preparing to work with data in research, business, or public health contexts. Additionally, it serves as a key bridge course for applicants preparing for the upcoming OMICSS-26 Genome Bioinformatics Summer School.
Alisa Davtyan holds a master’s degree in Mathematics from Yerevan State University. She currently works as an Associate ML Researcher at the Institute of Physics at Yerevan State University, where her research focuses on studying the mechanisms of long-term memory at the single-molecule level. In parallel, she works as a Data Scientist at Digitain.
Upon completing this course, students will develop essential statistical skills applicable to various domains. The course consists of theoretical and practical parts. The theoretical aspects of the theory of probability and statistics are developed by Dr. Vahan Huroyan, and available in our Bioinformatics Guide. The practicals will be conducted in Python and will be based on the University of Michigan's course "Inferential Statistical Analysis with Python" on Coursera. Key topics include:
Descriptive Statistics: Understanding types of variables, common distributions, and methods to summarize data.
Probability Theory: Introduction to basic probability concepts and their applications.
Inferential Statistics: Constructing confidence intervals, performing hypothesis tests, and interpreting p-values.
Data Analysis with Python: Utilizing Python libraries such as Statsmodels, Pandas, and Seaborn for statistical analysis.
This course is tailored for beginners who want to acquire statistical skills for data analysis in various fields.
To successfully complete the course, students must have a good command of English to read and comprehend the course material. Applicants must be enrolled in at least the first year of a Bachelor’s program (or higher). Additionally, participants must be available to attend lessons in person, as the course is offered exclusively offline.
Location: Armenian Bioinformatics Institute, Ezras Hasratyan 7, Yerevan, Armenia
Start date: April 16
End date: May 7
Schedule: Twice a week - Tuesday, Thursday - 19:00-20:30
The course is free of charge.
The courses have maximum capacity of 20 seats and will be filled on a first-come, first-served basis. Priority will be given to applicants who intend to apply to the OMICSS-26 Genome Bioinformatics Summer School.
Those who wish to enroll must complete the application form. The registration deadline is April 12nd at 23:59 Yerevan time.
Should you have any questions, feel free to contact us via the following means:
