Unleash the power of Python and its robust data science capabilitiesKey Features: * Unleash the power of Python 3 objects * Learn to use powerful Python libraries for effective data processing and analysis * Harness t...
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ISBN:
(数字)9781786465160
ISBN:
(纸本)9781786465160
Unleash the power of Python and its robust data science capabilities
Key Features:
* Unleash the power of Python 3 objects
* Learn to use powerful Python libraries for effective data processing and analysis
* Harness the power of Python to analyze data and create insightful predictive models
* Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics
Book Description:
The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you’ll have gained key skills and be ready for the material in the next module.
The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it’s time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls.
What you will learn:
* Install and setup Python
* Implement objects in Python by creating classes and defining methods
* Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis
* Create effective visualizations for presenting your data using M
This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as t...
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This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities, and media with an understanding of variation theory and the ways in which students learn to program. We outline the implementation of the course, and discuss the findings from the first cycle of an action research study with a small sample of undergraduate students. An investigation of the preferred (deep/surface) learning approaches of the students led us to believe that these approaches can be influenced through course design. Personal constructs of the students, elicited through the repertory grid technique, revealed that rich inventories of learning resources are highly valued. We comment on the transformational processes of the experience of the participants, and identify areas for further refinement and investigation in the next action research cycle.
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