Coding, Data Science & AI
Python Basics:¶
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Python Functions: Reusable blocks of code that perform specific tasks, enabling modular programming. They encapsulate functionality and promote code reuse.
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Python Classes: Blueprints for creating objects and facilitating object-oriented programming. They define properties (attributes) and behaviors (methods) of objects.
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Python Packages: Collections of modules and resources that enhance functionality and simplify application development. They provide pre-built code and tools for specific
Data Science:¶
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Data Cleaning: Process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in datasets to ensure data quality.
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Data Analysis: Techniques for exploring, transforming, and deriving insights from data to support decision-making and problem-solving.
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Machine Learning: Algorithms and models that enable systems to learn from data and make predictions or decisions without explicit programming.
Web Development:¶
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HTML: Markup language used for structuring the content and layout of web pages.
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CSS: Stylesheet language used for describing the presentation and visual styling of web pages.
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JavaScript: Programming language that adds interactivity and dynamic behavior to websites.
Artificial Intelligence (AI):¶
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Machine Learning: Subset of AI that focuses on developing algorithms and models that enable systems to learn from data and make predictions or decisions without explicit programming.
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Natural Language Processing (NLP): AI technique that enables computers to understand, interpret, and generate human language.
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Computer Vision: AI field that deals with enabling computers to see, interpret, and understand visual information.