Real-Time Backend

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We created this program for those of you, who want to learn how to work with large amounts of information in real-time.

During the first semester, we focus on the essential fundamentals, such as basic concepts of math and programming, which are the same for all programs.

In the Math & Statistic course, students will learn about discrete mathematics and the basics of probability theory. Algorithms & Data Structures covers the basic algorithms on graphs, data structures, and recurrence relations. Also, during the first semester, students learn how to process and analyze data, and build simple models based on this data in the Data Science course. In the Advanced Programming Languages course, students will learn about programming languages and their fundamental differences.

During the second semester, in the Operating Systems course, students will learn about various operating systems and their features. Networks & Clouds course goes over the basics of networking and security. The Systems Architecture course will cover the features of system architecture for different operating systems.

Real-Time Backend is the major course of this program, where students will be offered a real-life project example to work with a large amount of data.

Semester 1

Math & Statistics

  • Number theory

  • Sets, functions, and sequences

  • Generalized Mobius function and asymptotics

  • Relations

  • Recurrence relations

  • Counting techniques

  • Logic and techniques of proof

  • Trees and graphs

  • Partitioning numbers into terms

  • Algorithms

  • Mathematical theory of sampling

  • Normal populations and distributions

  • Chi-square, t, and F distributions

  • Hypothesis testing

  • Estimation

  • Confidence intervals

  • Sequential Analysis

  • Correlation, regression

  • Analysis of variance

  • Limit theorems

  • Chromatic numbers of graphs and Kneser graph

Algorithms and Data Structures

  • Simple data structures

  • Sorting

  • Binary and ternary search

  • Divide and conquer method

  • Recursion

  • Hash functions and hash tables

  • Graphs

  • Dynamic programming

  • Greedy algorithms

  • Tree data structures

  • Balanced trees

  • Heap, priority queue, and more

  • String algorithms

  • Segment tree, Fenwick tree, SQRT-decomposition, Cartesian tree, and more

  • Iterating over all subsets for som sets

  • Optimizations

  • Enumeration of all combinations, permutations, other combinations

Data Science

  • Basic tools for data analysis

  • Simple data collection and analysis

  • Probability and expected values

  • Variability, distribution, and asymptotics

  • Intervals, testing, and Pvalues

  • Power, bootstrapping, and permutation tests

  • Logistic regression & Poisson regression

  • Prediction, errors, cross-validation

  • Caret package

  • Predicting with trees, random forests, and model-based predictions

  • Regularized regression and combining predictions

  • Exploratory data analysis & modeling

  • Prediction model

  • Creative exploration

  • Least-squares, linear regression, multivariable regression, residuals, and diagnostics

Advanced Programming Languages

  • Language design principles

  • Programming languages

  • Syntax description

  • Semantic description

  • Lexical and syntax analysis

  • Variables

  • Data types and assignment statements

  • Expressions and assignments

  • Parallel and concurrent programming

  • Functional programming

  • Logic programming

Semester 2

Networks & Clouds

  • IoT (Business and Products, Architecture and Technologies, Networks)

  • Wi-Fi and Bluetooth

  • Cloud technology

  • Key security concepts and security tools

  • Authentication and access control

  • Windows/Linux/MacOS operating system security basics

  • Virtualization

  • Compliance frameworks and industry standards

  • Client system administration

  • Server and user administration

  • Cryptography and compliance Pitfalls

  • TCP/IP Framework, IP adressing and the OSI Model

  • Security (injection vulnerability, penetration testing, incident response, digital forensics, threat intelligence, thread hunting

  • Application security and testing

  • Phishing scams and more

Systems Architecture

  • System calls and interrupt handling

  • The concept of process, stream, and thread

  • Multitasking

  • Stream synchronization

  • Classification of types of memory

  • Pointers

  • Process memory

  • Disk storage device

  • File systems

  • Architecture: scheduler, memory manager, IPC

  • Basic elements of the operating system

Real-Time Backend (Architecture)

  • Processing and storage of large amounts of data

  • Data storage methods

  • Databases and their use

  • Implementation of an individual project for the course

Operating Systems

  • Processes and execution

  • Scheduling

  • Concurrency and Threads

  • Data structures and variables

  • I/O and directions

  • File systems

  • Data integrity and protection

  • Distributed systems

  • Memory, segmentation, paging, swapping

Check admissions to learn if you are eligible and enrol.