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.

Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.

In this course, you will learn advanced topics such as function arguments, iterators, generators, closures, and decorators. Dozens of practice exercises will help you grasp these topics.

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.

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.

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.

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.

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.


Celebrate the world of conversational AI with our 'Intro to ChatGPT' course. Dive into the fundamentals of AI-driven chatbots, understand how ChatGPT works, and explore its exciting possibilities. Join us on a journey into the future of human-AI interaction!

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.


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.

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.

Git is the most popular version control system used by millions of developers around the globe. Whether you're a seasoned developer or a beginner, this course will equip you with the knowledge and skills needed to efficiently manage your software projects, collaborate with others, and master the art of version control.

Hangman is a classic word-guessing game where players aim to uncover a hidden word by suggesting letters within a limited number of attempts. The game progresses with each incorrect guess, drawing parts of a hangman figure, leading to a loss if the figure is completed before the word is fully guessed. 

In this project, participants will methodically build a digital version of Hangman. We will start by loading a word list from a file, then move on to develop functions for handling guesses, updating the game state, and managing the game's flow, culminating in a complete, playable game.

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.

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.

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.

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.

As a data scientist or analyst, you will have to deal with different data types. The first thing that comes to mind - is numerical data, of course. But also you will have to deal with textual data often. In this course, you will dive into strings, that represent textual data in Python, and learn how to perform different manipulations with them.

This course covers Object-Oriented Programming (OOP) in Python, starting with the basics and progressing to advanced concepts. You will implement a User model to gain practical experience and understanding of OOP features. By the end of the course, you will have a strong foundation in OOP and a deeper knowledge of Python's inner workings.

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.

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.

The understanding of data structures and algorithms: this is what sets advanced professionals apart from the rest. In the modern world of growing data, it is very important to be able to process large amounts of data efficiently. 

In this course, you will study the most basic data structures that help us to deal with huge amounts of data as well as implement the most basic and crucial concepts on your own so you’ll get a deeper understanding of how each data structure works and you'll be able to decide what data structure best suited for your task.

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.

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.

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 to work confidently with data in JavaScript by mastering objects and arrays. Understand how to create, access, and manage object properties and methods effectively. Dive into advanced object manipulation techniques, including iteration, cloning, and destructuring for cleaner code. Build a strong foundation in working with arrays and learn to manage, iterate, and modify array elements efficiently. Master advanced array methods like map, filter, find, and sort to transform and handle data effectively in your applications.

Master essential JavaScript concepts, including classes, DOM manipulation, event handling, and asynchronous programming. Learn to create dynamic and interactive web applications by managing user interactions, fetching and displaying data, and handling asynchronous operations efficiently. Through a blend of theory, hands-on challenges, and real-world examples, this course equips you with the practical skills needed for modern web development.

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 build backend applications with Node.js and Express.js. Set up your environment and create your first Node.js apps. Work with the file system and build simple console tools. Use Express.js to build web apps, handle routes, and manage requests.

Learn to build complete web applications from start to finish. This track takes you from structuring and styling websites with HTML and CSS to adding interactivity with JavaScript. Master React to create dynamic user interfaces, and use Node.js with Express.js to build backend systems. Explore how frontend and backend technologies work together in real-world web development.

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.

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.

This is a hands-on course that will help you understand the basics of object-oriented programming in Python. You will learn how to create classes, work with objects, use inheritance, and extend the capabilities of your programs.

You will acquire practical skills in Python's modules and imports for efficient code management. Master advanced Error Handling techniques for more reliable applications, automate file operations with File Handling, and learn robust testing strategies with Pytest and Unittest to ensure your code's integrity.

Embark on an intense and rewarding journey to become a proficient Python programmer. Prepare for a challenging yet fulfilling experience that equips you with complex programming tasks.

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.

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