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- Principles of Data Science with Python: Intro...
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Toote nr:
45560432
Principles of Data Science with Python: Introduction to Scientific Computing, Data Analysis, and Data Visualization
Toote nr:
45560432
€ 39
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Unlock the power of data with practical Python programming for scientific computing, data analysis, and visualization.
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What Stands Out
Comprehensive Curriculum
Offers a thorough grounding in scientific computing, data analysis, and visualization, making it ideal for beginners and experienced learners seeking to deepen their Python skillset effectively.
Hands-On Approach
Emphasizes practical applications through exercises and projects, allowing users to immediately apply concepts and gain real-world experience in data science.
Up-to-Date Resources
Incorporates the latest tools and techniques in Python data science, ensuring learners are equipped with relevant skills needed in today’s fast-evolving job market.
Toote üksikasjad
| Publisher | Arash Karimpour |
| Publication date | July 31, 2020 |
| Language | English |
| Print length | 544 pages |
| ISBN-10 | 1735241008 |
| ISBN-13 | 978-1735241005 |
| Item Weight | 2.53 pounds (1.15 kg) |
| Dimensions | 7.5 x 1.23 x 9.25 inches (19.1 x 3.1 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners seeking foundational knowledge in data science using Python for practical applications and theoretical insights.
-
Students and Educators
Perfect for academic settings, providing structured lessons and exercises in data analysis and visualization techniques.
-
Professionals Transitioning Fields
Beneficial for individuals switching to data-centric careers, offering essential skills applicable in various industries.
-
Advanced Data Scientists
Not suitable for experts as it may lack advanced techniques and depth required for seasoned professionals.
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Principles of Data Science with Python: Introduction to Scientific Computing, Data Analysis, and Data Visualization
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€ 39
Kui tellid kohe, saad toote kätte Teisipäev, August 25
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Omadused ja eelised
- Learn Python programming for data science applications.
- Master scientific computing and data visualization techniques.
- Explore the functionalities of libraries like NumPy, Pandas, and Matplotlib.
- Understand statistical functions and time-series analysis.
- Gain hands-on experience with interpolation, curve fitting, and numerical integration.
- Focus on practical data manipulation without machine learning or AI content.
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