The demand for skilled data analysts both in science and industry is constantly growing. Data processing and analysis Professional Certificate Program gives you the necessary knowledge base and useful skills to face data analysis challenges in your professional field.
The first course of the Program covers such concepts of data analytics as data preprocessing and visualization, large datasets management and storage by means of SQL and NoSQL database management systems, data series analysis.
The second course of the program discusses what machine learning is and mainly focuses on the regression problem (linear regression, polynomial and multivariable regression), classification methods (logistic regression, Naïve Bayes and K-nearest neighbors) and clustering methods (hierarchical and k-means clustering).
The last course covers advanced methods of machine learning. You will learn how to analyze large datasets, find regularities in your data, and apply more complicated clusterization and classification techniques. More precisely, you will face with the concept of the factor analysis under the Principal Component Analysis (PCA), learn about support vector machines (SVM) and decision trees for classification, get familiar with some popular resampling methods and apply them to the so-called Ensemble Learning. Finally, you will deal with the problem of reinforcement learning and learn some useful algorithms.
In all courses, practical tasks of each week will refine your understanding of main concepts and enhance your abilities in data engineering.
The program helps you to develop skills that include Excel data analysis, MS Azure Machine Learning Studio and Python Notebooks, Oracle Apex and Mongo DB. MS Excel and database management systems are used in the first course. Two learning tracks are provided in machine learning courses, one for those who have coding experience in Python, while the tasks in the other track are realized in MS Azure for students with no coding experience.
Founded in 1900, ITMO University is the top higher education institution in computer science in Russia, it is a trailblazer shaping national education and research policy in Russia. Higher School of Digital Culture is delighted to share with you its experience in the field of data science as well as in interdisciplinary research.
Courses under this program: Course 1: Data Storage and Processing
Master the culture of data representation, interpretation and outcomes evaluation. Learn the fundamentals of relational and NoSQL database management systems.
Course 2: Introduction to Machine Learning
Learn the essentials of machine learning and algorithms of statistical data analysis.
Course 3: Advanced Machine Learning
An advanced course on machine learning. You will learn specific techniques and methods to analyze big amounts of data.
Want to learn data processing and interpreting the result you’ve got? This course is for you! Get acquainted with preparing and analyzing large amount of data, as well as data storage fundamentals.
This course is an introduction to initial data processing. We will start with data types and sources, methods of data preparation: cleaning, filling in the missing values, data smoothing and normalization. The course will familiarize you with the descriptive statistics and data visualization methods. You will also learn how to analyze time series and find trends.
Get acquainted with the fundamentals of data storage and access: databases types, relational and NoSQL databases, big data initials.
Want to learn how to analyze the huge amounts of data? In this course you will learn modern methods of machine learning to help you choose the right methods to analyze your data and interpret the results correctly.
This course is an introduction to machine learning. It will cover the modern methods of statistics and machine learning as well as mathematical prerequisites for them. We will discuss the methods used in classification and clustering problems. You will learn different regression methods.
Various examples and different software applications are considered in the course. You will get not only the theoretical prerequisites, but also practical hints on how to work with your data in MS Azure.
Advanced methods of machine learning. You will learn how to analyze big amounts of data, to find regularities in your data, to cluster or classify your data.
In this course you will learn specific concepts and techniques of machine learning, such as factor analysis, multiclass logistic regression, resampling and decision trees, support vector machines and reinforced machine learning.
Various examples and different software applications are considered in the course. You will get not only the theoretical prerequisites, but also practical hints how to work with your data in MS Azure.
Natalia Grafeeva, Elena Mikhailova, Olga Egorova, Anton Boitsev, Aleksei Romanov and Dmitry Volchek