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Item #:
46000762
Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data
88% of respondents would recommend this to a friend
Item #:
46000762
MVR 320
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Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course.
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What Stands Out
Industry-standard Tools
Leverage leading data analysis tools like Python and Jupyter to efficiently handle and analyze data, ensuring relevancy and effectiveness in modern data-driven decisions.
Actionable Insights
Transform complex data sets into clear, actionable insights that inform strategic decision-making, empowering organizations to optimize performance and achieve their goals.
Beginner Friendly
Designed for newcomers, this guide simplifies data analysis principles, making it accessible for all skill levels and fostering confidence in using powerful analytical techniques.
Product Details
| Publisher | Packt Publishing |
| Publication date | June 5, 2018 |
| Language | English |
| Print length | 194 pages |
| ISBN-10 | 1789532027 |
| ISBN-13 | 978-1789532029 |
| Item Weight | 12.2 ounces (345.87 grams) |
| Dimensions | 7.5 x 0.44 x 9.25 inches (19.1 x 1.1 x 23.5 cm) |
Who Should Buy?
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Aspiring Data Analysts
Individuals starting their journey in data analysis who want to learn Python and Jupyter.
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Business Professionals
Professionals looking to derive insights from existing data to enhance decision-making in their organizations.
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Students in Data Science
Students studying data science or related fields and need foundational skills in Python for analytics.
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Advanced Data Scientists
Experienced data scientists might find the content too basic and not challenging enough for their needs.
Product Description
Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data
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Data Processing Editorial Review
"Beginning Data Science with Python and Jupyter" is a book that promises to help readers use powerful tools to unlock actionable insights from data. While some readers found the book's organization to be poor and the concepts not fully explained, others found it to be an excellent resource for beginners. The book appears to be best suited for those with basic knowledge of Python who want to get started with data science without going over all of the basics of the language again. The book shows readers step-by-step how to get up and running with Jupyter and then works through Python data science libraries that are commonly used in the industry. The book has a lot of step-by-step examples and activities, which works quite well given the subject matter.
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Pros
- Excellent for beginners
- Focused on Jupyter and Python data science libraries
- Step-by-step examples and activities
Cons
- Poorly organized
Product Price History
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MVR 320
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Features & Benefits
- Ideal for beginners with some Python knowledge
- Learn about key machine learning concepts and models
- Hands-on practice with real datasets and web scraping
- Create interactive visualizations for data communication
- Suitable for professionals in various industries
- Prior experience with Python and related libraries recommended
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