Data Processing Fundamentals

This course will provide you with essential knowledge of one of the most popular programming languages, along with practical examples of its use for data collection, processing, and analysis. The skills you gain are valuable not only in artificial intelligence projects but also in any other field that requires handling large datasets.

Course Duration: 12 lessons, 1 lesson per week

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WHO IS THIS COURSE FOR?

Anyone Looking to Master a New Profession

If you're exploring new career paths and seeking a role that brings both fulfillment and a competitive salary, or if you're ready to make a major career change, this course will guide you in the right direction. 

People with Analytical or Mathematical Thinking

If you have a strong grasp of logic, basic mathematical operations, and data structures, you’ll find it easier to tackle topics related to data analysis and processing. 

Anyone with Basic Programming Skills

If you already know programming languages such as Python or R, you’ll quickly familiarize yourself with data processing tools and techniques, giving you a solid foundation for this course.

Technical Specialists or Those Familiar with Excel 

If you enjoy working with large datasets, finding patterns, and analyzing information, this course will provide you with both new insights and practical skills.

Instructors

Mykhailo Odintsov

Software Engineer with 15 years of experience, including 9 years working on machine learning and artificial intelligence projects.

Петро Шопін

Працює над комплексними Digital стратегіями.
Займається використанням чат-ботів для бізнесу.
Запускає курси в агентстві ADS Wind
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Modules

Module 1
Module 2
Module 3

Introduction to Python Programming
(6 lessons)

• Introduction to Python: Understanding interpreted programming languages, installation, execution environment, constants, and variables
• Control flow, conditional statements, and loops

• Functions and modules
• Data structures and collections
• Working with text data

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Data Collection and Storage
(3 lessons)

• Error handling and working with files
• Fundamentals of OOP (Object-Oriented Programming) and its application for structured data storage
• Automating data collection from the web (web scraping)


Data Processing, Visualization, and Modeling
(3 lessons)

• Data analysis using Pandas
• Data visualization techniques
• Basic concepts of data science and an introduction to data modeling with Scikit-learn


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