Python for Pharmaceutical Data Science From Fundamentals to Predictive

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Bol The Python for Pharmaceutical Data Science course serves as a comprehensive guide for leveraging Python programming in the pharmaceutical domain. It bridges the gap between data science and pharmaceutical applications, offering both foundational knowledge and advanced analytical techniques. The syllabus spans core Python programming, data handling with Pandas, data visualization, statistical analysis, and machine learning.* Foundations of Python Programming* Data Handling with Pandas* Data Visualization with Matplotlib * Intermediate Data Analysis and Statistical Techniques* Machine Learning Applications in Pharmacy* Practical Applications and ProjectsConclusionThe book concludes by highlighting the importance of continuous learning, staying updated with evolving libraries, and participating in data science communities. It equips learners with skills that are not only technical but also industry-relevant, emphasizing ethical data handling and effective communication of insights.

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The Python for Pharmaceutical Data Science course serves as a comprehensive guide for leveraging Python programming in the pharmaceutical domain. It bridges the gap between data science and pharmaceutical applications, offering both foundational knowledge and advanced analytical techniques. The syllabus spans core Python programming, data handling with Pandas, data visualization, statistical analysis, and machine learning.* Foundations of Python Programming* Data Handling with Pandas* Data Visualization with Matplotlib * Intermediate Data Analysis and Statistical Techniques* Machine Learning Applications in Pharmacy* Practical Applications and ProjectsConclusionThe book concludes by highlighting the importance of continuous learning, staying updated with evolving libraries, and participating in data science communities. It equips learners with skills that are not only technical but also industry-relevant, emphasizing ethical data handling and effective communication of insights.

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Pages: 84, Paperback, LAP Lambert Academic Publishing


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Merk LAP LAMBERT Academic Publishing
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  • 9786208421137
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