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Data Analysis with AI is a hands-on course designed for professionals who want to simplify and supercharge their data workflows using artificial intelligence—without needing advanced technical skills. This course walks you through real-world scenarios where AI helps clean, structure, and interpret data effortlessly. You'll learn how to summarize datasets, identify trends, extract insights from spreadsheets. With intuitive tools and step-by-step guidance, Data Analysis with AI empowers you to turn complex data into clear, actionable intelligence—saving time and improving decision-making across any industry.

Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.

Data Analytics with AI: Bank Marketing Data

If you're an expert in creating queries for a single table, improve your knowledge! Let's start accessing and manipulating two and more tables. During the course, you'll learn how to work with special statements, what is the join and how to use it, and also will practice a lot!

This course covers intermediate topics on pandas, a must-have tool for each data analyst. During the course, you will learn how to prepare data for further interactions and how to group it using different techniques. You will learn the easiest data visualization and be acquainted with data joining.

Creating a machine learning model seems to be your most challenging and essential task. But first, we have to work with data! Learn how to process datasets and fully prepare them for use. Numerical, categorical, and temporal data await you in our course.

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.