Ready to try your hand at data science? This course is designed to challenge your existing knowledge and hands-on skills, ensuring you are fully prepared for any twists and turns a data science interview might present. We'll push your understanding of critical topics to the limit, assessing your readiness for real-life scenarios.

Algorithms and Data structures are the basements of computer programming. Moreover, you will learn this topic with easy examples. After the course, you will be filled with ADS knowledge, analytical thinging and a perfect mood!

Dates and(or) times are one of the most common things in modern data: often we need to deal with observations containing dates and times. In this course, you will learn about datetime, pytz libraries, and how they help to deal with different formats of dates and times. Also, you will learn how to implement this knowledge to work with dirty or missing date/time values.

This course provides a comprehensive introduction to Generative AI, covering its theoretical foundations, practical applications, and ethical considerations. Learners will explore various generative models, their training methods, and real-world use cases while also addressing the challenges and risks associated with AI-generated content.

Design shapes how people see, understand, and interact with the world. This learning path introduces the foundations needed to create clear, engaging, and meaningful visuals. From the basics of layout and structure to the nuances of typography and color, every element works together to communicate effectively. Along the way, you’ll discover how psychology, perception, and creative principles influence design decisions. By the end, you’ll have the tools to craft work that is both visually appealing and purpose-driven.

This project teaches practical fraud detection using machine learning, focusing on data preprocessing, model training, evaluation, and threshold optimization.

Build a machine learning system to detect fraudulent job postings using text analysis and structured metadata for robust automated screening.

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The Django Framework is the best choice to start learning Backend Development using Python! Here you will dive into the Backend, learn how to handle HTTP requests, pass and extract data, and create HTML pages using Templates. In particular, you will learn how to use Python to interact with a database in a very convenient way without using SQL.

This course introduces a Dynamic Programming approach for users familiar with the syntax and data structures of the Python programming language. Dynamic programming is a necessary topic for a technical interview, as are Binary Search, Sorting Algorithms, etc. Be prepared to solve a few problems on your own. Use the hints or Solutions section if you get stuck.

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Project for e2e testing

Have you encountered errors in Python when running the program? No programmers prevent this. If you want to learn how to perceive, process, and use errors correctly - this course is for you. Here is information about the types of errors, how to deal with them, and how to use them to your advantage! Ready? Let's start!

In this project, we will study how to create, modify, and extract data from Excel spreadsheets using Python code.