Data Analysis and Artificial Intelligence

Machine learning is the base of the Data Science specialization. The course includes simple ML algorithms, ensembles and an introduction to neural networks. It's balanced between the theoretical foundation of the algorithms and practice. 

Advanced Machine Learning gives deeper knowledge in the area. It covers autoencoders, generative models, recurrent neural networks and LSTM, graphical models, bayesian machine learning and other topics. You will learn practical aspects of training neural networks. 

High-Dimensional Data Analysis gives you a much deeper understanding of clustering algorithms, distribution estimation, and strategies of preprocessing data. 

Big Data Technologies and Analytics cover distributed file systems, MapReduce, Spark, NoSQL databases and distributed machine learning. 

In Metrics and empirical methods, you will recall statistics, construct experiments and apply it in the domain of Software Engineering. 

Mathematical courses Advanced Statistics and Optimization are fundamental in Machine learning. 

The course Managing Software Development is about the predictable process of developing software that is needed by the customer. In ML projects correct assumptions about conditions in which the system will be used are crucial. You will also learn how to organize the teamwork, those skills will be useful when you will achieve the team lead level. 

During the study, you will select Technical electives. There is a wide range of courses, from specializations inside ML, - DS application in applying DS in specific domains like finances, or you can get an additional specialization beyond ML. 

In Humanitarian electives, you will develop your soft skills like communication or public speaking, learn to pass and conduct interviews, understand what is important in launching your startup and cover a lot of other interesting nontechnical aspects. 

In Thesis, you will practice all your acquired knowledge, introduce new approaches in ML. Many students publish papers in the top conferences during the work on their thesis. 

The Center for Artificial Intelligence is one of the six technology centers of Innopolis University

The center's competencies in the field of AI: 

— machine learning (neural networks, deep learning); 

— computer vision; 

— natural language processing;  

— big data analysis; 

— systems of advice and assistance in making decisions.

Innopolis University stays in touch with alumni, continuing to advise and assist in solving engineering and business tasks. 

In 2018, 100 % of the students have been offered jobs by the well-known and reputable organizations, and Innopolis University partner companies: Yandex Technologies, ICL, Tinkoff, Kontur Innovation and others. A number of students created their start-ups aimed to solve machine learning tasks. 

The graduates are employed as: 

— Senior developer; 

— Data Science specialist; 

— Specialist in data analysis; 

— Analysts.