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Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
€ 64
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Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass the entire data science lifecycle.
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Produkta informācija
| Item Weight | 2 lbs (910 grams) |
Who Should Buy?
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Aspiring Data Scientists
Perfect for beginners looking to understand core data science principles using Python through hands-on projects and examples.
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Students and Academics
Ideal for students studying data analytics or data science who require structured learning and practical applications.
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Professionals Transitioning Careers
Beneficial for professionals seeking to shift into data-focused roles needing foundational knowledge in data manipulation and analysis.
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Complete Beginners
Not suitable for those with no prior programming experience as it assumes basic knowledge of Python.
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Advanced Data Practitioners
Less beneficial for experienced data scientists looking for in-depth techniques or niche specializations beyond foundational concepts.
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Non-technical Users
Not recommended for individuals without technical skills or interest in programming, as content is code-centric and analytical.
PRODUKTA APRAKSTS
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
Klientu jautājumi un atbildes
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jautājums:
Do I need prior programming experience to benefit from this book?
atbildi: A basic knowledge of Python programming is recommended but not mandatory. -
jautājums:
What kind of tools will I learn to use in this book?
atbildi: You will learn to use industry-standard tools such as pandas for data analysis. -
jautājums:
Is this book suitable for someone working in a non-technical role?
atbildi: Yes, it is designed for both aspiring data scientists and those in non-technical roles looking to understand data science.
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€ 64
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Funkcijas un priekšrocības
- Master data science skills to transform raw data into actionable insights.
- Learn programming and statistics foundational skills essential for data scientists.
- Ideal for aspiring data scientists and data analysts seeking to bridge technical gaps.
- Gain proficiency in industry-standard tools like pandas for data manipulation.
- Explore data collection techniques including text processing and web scraping.
- Visualize and model data to draw generalized conclusions and insights.
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