Explore the essentials of SQL, from retrieving and filtering data with SELECT and WHERE to sorting results with ORDER BY and summarizing them with aggregate functions like COUNT, AVG, and SUM. Through hands-on challenges, you'll build the skills to query real datasets with confidence.

Take your knowledge to the next level with advanced SQL techniques for real-world data work. Learn to group and filter data using GROUP BY and HAVING, write nested subqueries, and join tables using INNER, LEFT, RIGHT, and FULL JOIN types. You will also create, alter, and modify tables with DDL statements, and insert, update, and delete records with DML statements.



This course delves into the theory behind relational databases. You'll learn what they are and see how they differ from non-relational databases. Throughout the course, we'll walk you through the ins and outs of database design and familiarize you with various types of relationships. Additionally, you'll explore the concepts of normalization and normal forms, equipping you with the knowledge to craft efficient and optimized databases.

This is a brief overview of all the courses in the track, and thanks to this course, you will understand what SQL is and why you need it

Python is a high-level, interpreted, general-purpose programming
language. Distinguished from languages such as HTML, CSS, and JavaScript, which are mainly
utilized in web development, Python boasts versatility across multiple domains, including
software development, data science, and back-end development. This course will guide you
through Python's fundamental concepts, equipping you with the skills to create your own
functions by the conclusion of the program.

Gain a solid understanding of Python's core data types and learn how to work with them effectively. Explore numbers, booleans, strings, and how to convert and compare values safely across types. Build confidence performing arithmetic, logical, and string operations, and develop the foundational skills needed to write clean, reliable Python code.

Explore the essentials of Python's core data structures: lists, dictionaries, tuples, and sets. Learn to create, index, modify, and combine these collections using built-in methods such as append(), pop(), and update(), building a solid foundation for organizing and manipulating data in your programs.

Build decision-making logic in Python with if, if-else, and if-elif-else statements. Use comparison and logical operators, understand operator precedence, and write cleaner code with the ternary operator.

Build confidence in mastering Python loops. Start with the fundamentals of for and while loops, then move into nested loops, break and continue statements, and list and dictionary comprehensions. Through hands-on challenges, you will learn to write efficient, concise Python code for real-world tasks.


Gain a solid understanding of how functions shape Python programming. Master defining and calling functions, working with arguments, and handling return values, including generator functions that yield values lazily. Explore recursion and lambda expressions to write flexible, efficient code.


After completing this track, you will be able to write basic Python code, understand its syntax, and set up a Python development environment. You'll have the skills to start your programming journey and build a strong foundation for further learning.

Master the art of SQL joins with engaging, real-world examples and hands-on challenges. This course takes you from foundational join concepts to advanced multi-table queries, ensuring you can confidently analyze and combine data from multiple sources.

Master the use of built-in SQL functions to manipulate strings, dates, numbers, logical values, nulls, and JSON data. This course provides a hands-on approach to understanding and applying SQL functions in real-world scenarios, enhancing your data querying and transformation skills.

Begin an exciting journey through SQL with Advanced Techniques in SQL. Learn about the important ACID properties that help keep data accurate in database transactions. Discover advanced ways to optimize your queries to improve database performance. Explore special SQL features like window functions, triggers, Data Control Language (DCL), and NoSQL databases. This will help you handle modern database management confidently and effectively.

Master the art of analyzing data with SQL window functions. This course guides you through the core concepts, syntax, and practical applications of window functions, empowering you to perform advanced analytics and reporting directly in SQL.

This track covers both fundamental and advanced SQL techniques, enabling confident data management, query optimization, and data analysis. It explores key principles of relational databases, including filtering, sorting, aggregation, data joins, indexing, transactions, and other essential mechanisms. The acquired skills will help efficiently process data and extract valuable insights.

Here we will briefly describe all the courses on the track and consider how you can apply the gained knowledge in practice.

NumPy is one of the basic packages for scientific computing in Python. The 'NumPy in a Nutshell' course will introduce you to such a powerful tool as NumPy, which is convenient for working with arrays of different sizes. After completing this course, you will be able to easily work with matrices, using various functions. In addition, during the course, you will learn basic methods for working with arrays that simplify code writing.

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing. By understanding its architecture and capabilities, we will grasp why it is considered an essential tool for data scientists, researchers, and developers working in the realm of data analysis, machine learning, and beyond.

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

In this project, we are going to understand what Pandas is and why it is so powerful.

To study many applied disciplines, it is necessary to have basic knowledge of higher mathematics and linear algebra. Mathematics is often used in data analysis, system modeling, building machine learning models, etc. Let's look at some of the most important topics and learn how to use the mathematical apparatus to solve real problems.

Probability theory is a fundamental branch of mathematics that deals with the study of uncertainty and randomness. It provides a framework for understanding and quantifying uncertainty in various fields, including statistics, data analysis, machine learning, finance, physics, and more.

Build a strong foundation in statistics using Python. Learn essential statistical concepts and apply them through NumPy and pandas. Move from basic measures like mean and variance to hypothesis testing, confidence intervals, and data-driven insights with hands-on practice.

Statistics and probability theory are fundamental tools in data analysis, decision-making, and scientific research. They provide a systematic and quantitative way to understand and interpret data, make predictions, and draw conclusions based on evidence. Now we will consider all additional topics necessary for Data Science and Data Analytics.

Track curriculum encompasses a collection of pivotal courses that provide foundational knowledge and skills essential for a successful journey in the field of data science. These courses encompass the comprehensive study of key concepts, tools, and methodologies integral to the realm of data analysis and modeling. By delving into courses centered around numpy, pandas, statistics, probability theory, as well as mathematics tailored for data analysis and modeling, learners are equipped with a well-rounded toolkit to seamlessly navigate the intricacies of data-driven exploration, manipulation, and inference. The curriculum's diverse content ensures a robust understanding of critical elements in data science, cultivating a solid base for individuals venturing into this dynamic and ever-evolving domain.

Dive into the world of the most popular language for front-end development – JavaScript. JavaScript is a language built into almost every browser and can be used for a wide variety of tasks. Learn the basic functionality and prepare yourself for the challenges and more advanced programming techniques.

Learn the essentials of HTML, the backbone of every website. Structure content with tags and attributes, build clear document layouts, and add images, links, and tables. Create accessible, user-friendly forms for capturing input and interaction. Practice crafting well-structured, functional web pages while following best practices. Start your web development journey by mastering HTML.

Master the essentials of CSS, the styling language that transforms the look and feel of web pages. Explore core concepts such as text styles, colors, spacing, the box model, Flexbox, and decorative effects. Build the skills to create visually engaging and well-structured web pages.

Level up your styling skills by mastering advanced CSS techniques for modern web design. Position and manage elements with precision using advanced positioning strategies. Create smooth transitions and engaging animations to enhance user experience. Transform and manipulate elements for dynamic visual effects. Build responsive designs that adapt across devices and learn to streamline your workflow with CSS preprocessors like Sass.

Explore the fundamentals of building user interfaces with React. Focus on components, JSX, data flow, state, and side effects used in everyday React applications.

Learn to manage navigation in React applications using React Router. Understand the structure of URLs and the role of routing in web apps. Set up React Router to create multi-page applications with dynamic content based on URL paths. Work with advanced features like query strings and URL parameters to handle application state and user navigation.

Discover the power to create captivating websites by harnessing HTML, CSS, and JavaScript. Immerse yourself in building dynamic web applications enhanced with cutting-edge frameworks and libraries. With these skills at your disposal, you can become an expert in crafting engaging user experiences and laying the foundation for a successful career in web development.

Machine learning is now used everywhere. Want to learn it yourself? This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project.
This course is intended for students with a basic knowledge of Python, Pandas, and Numpy.

Master the mathematical foundations essential for data science. Explore core concepts in functions, calculus, linear algebra, probability, and dimensionality reduction. Build both theoretical understanding and practical coding experience to strengthen your ability to analyze data, model complex systems, and apply advanced techniques in machine learning.

Learn practical techniques to clean, transform, and engineer data for machine learning using Python. This course covers essential preprocessing steps, feature creation, and hands-on challenges to prepare data for modeling.

Linear Regression is a crucial concept in predictive analytics. It is widely used by data scientists, data analytics, and statisticians as it is easy to build and interpret but powerful enough for many tasks.

Master the core classification algorithms that power modern machine learning. Explore how models like k-NN, logistic regression, decision trees, and random forests make predictions, evaluate their accuracy, and understand when to use each. Build the skills to compare models and choose the best one for your data.

Gain a solid understanding of cluster analysis, a key unsupervised learning technique for uncovering patterns in unlabeled data. Explore the essentials of K-Means, Hierarchical Clustering, DBSCAN, and GMMs, and get hands-on experience with real datasets to build confidence in applying clustering to real-world problems.

A comprehensive course for intermediate learners to master the key evaluation metrics used in machine learning, covering both supervised and unsupervised tasks. The course progresses from foundational concepts to practical Python implementations, interpretation of results, and a comparative overview of metric types and their trade-offs.

Master the full spectrum of machine learning with Python, combining practical skills with strong theoretical foundations. Build models quickly with scikit-learn and strengthen your understanding of probability, linear algebra, and optimization. Apply regression, classification, and clustering techniques to uncover insights from data. Explore how to evaluate models using the right metrics to ensure practical, reliable performance.

Unlock the full potential of Python's most essential library for numerical computing, NumPy. This comprehensive course is designed to take you from a beginner's understanding to an advanced level of proficiency in NumPy. Whether you're a data scientist, engineer, researcher, or developer, mastering NumPy is essential for efficient data manipulation, scientific computing, and machine learning.

Data is everywhere around us, and making sense of it is extremely important. Visualization helps you deal with data by finding certain patterns and insights in it. You will develop a solid foundation of data visualization using Python and its libraries, such as matplotlib and seaborn, to get as much information from data as possible in a neat and concise way.

Power BI is an essential tool for any aspiring data analyst or business professional. Learn how to transform raw data into insightful visualizations and interactive dashboards, connect to various data sources, and create compelling reports for informed decision-making.

This corse provides a comprehensive introduction to Tableau's core features, empowering learners to create impactful data visualizations and dashboards. We will cover essential topics such as working with charts, filters, calculated fields, and parameters, as well as advanced techniques like combining data and creating interactive dashboards. By the end, you will have the skills to transform raw data into actionable insights with ease and confidence.

This track helps master key data visualization techniques. It covers NumPy and Pandas for data preparation and processing, Python libraries for creating detailed graphs, and Power BI and Tableau for interactive dashboards and analytics. These tools enable effective data analysis and presentation in a clear and insightful way.

Learn to extract valuable data from websites automatically. Master techniques to gather information efficiently, enabling you to perform in-depth analysis, make data-driven decisions, and unlock new insights from the vast ocean of online information.

Visualization is one of the most common ways of representing data. By using different kinds of plots (like scatter-plot, histogram, bar charts, and so on) you can find some insights in your data, or approve/reject some assumption/hypothesis. In this course, you will be introduced to the matplotlib library, and learn how to build different charts.

Together we will make the first dive into visualization based on a seaborn library. We will learn how to build simple plots and how to customize them. You will cope faster with tasks if you know something about pandas. Do not hesitate, and let's go!

Upon completing this course, you will be able to create basic data visualizations using tools like charts and graphs. You'll understand the importance of visualizing data and how to convey meaningful insights effectively.

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