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Basics of Data Science Interview Prep
Education & Learning Analytics
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About
A focused collection of 200 frequently asked questions and their respective answers covering the essential fundamentals of Data Science. This resource is valuable for understanding core terminology, such as the distinction between concepts like precision and recall, or the difference between classification and regression tasks in supervised learning. The questions also delve into algorithm comparisons, including the relationship between k-means and hierarchical clustering. The content is suitable for building knowledge bases and educational tools centered on foundational Data Science and AI concepts.
Columns
- Id: A unique numerical identifier for each entry in the dataset.
- Questions: Contains text prompts relating to Data Science and AI subjects.
- Answers: Provides the corresponding text response to the associated Data Science question.
Distribution
The structure includes 200 total records across three primary columns. All entries are valid across all columns. The 'Id' column, which serves as the unique identifier, spans values from 1 to 200, with 20 entries distributed across ten specific ranges. The dataset contains 193 unique questions and 191 unique answers. This collection is expected to receive annual updates. The file format associated with this data is CSV (DataScienceBasics_QandA - Sheet1.csv, 57.18 kB).
Usage
- Education and Training: Developing quizzes, self-assessment tools, or study guides for foundational Data Science courses.
- Interview Preparation: Serving as a knowledge bank for preparing for or conducting interviews focused on Data Science basics.
- NLP Model Development: Training machine learning models, specifically question-answering systems or knowledge extraction tools, given the distinct Q&A pairings.
- Content Generation: Creating educational content or tutorials centered on frequently misunderstood Data Science concepts.
Coverage
This resource is purely conceptual and technical, focusing entirely on the subject matter of Data Science and AI. Therefore, it lacks specific geographic, time range, or demographic scope. It covers core academic and industry concepts in the field.
License
CC0: Public Domain
Who Can Use It
- Students and Novices: Gaining familiarity with essential Data Science terms and definitions before examinations or project work.
- Data Professionals: Quickly reviewing fundamental concepts or using the Q&A pairs to onboard new team members.
- Platform Developers: Integrating foundational knowledge into chatbots or automated educational applications.
Dataset Name Suggestions
- Data Science Core Q&A Resource
- AI Fundamentals Question Set
- Basics of Data Science Interview Prep
- Essential Data Science Concepts
Attributes
Original Data Source: Basics of Data Science Interview Prep
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