Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox by Meitiner, Philip
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Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox by Meitiner, Philip

Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox

Apress
Price:
$69.99

Description

Chapter 1: Introduction to Data Science in the ClassroomChapter Goal: After reading this chapter, readers will understand the importance of measurement - they will able to measure air temperature using a thermometer and they will understand how it works. We will introduce a number of core data science concepts and how to apply them to build an experiment. We'll cover some basic how-to skills for gathering and tabulating data, and we will undertake some analysis on our results. The reader will get an overview of a complete and meaningful example of applied data science, and they will be ready to explore more deeply.
  1. Data is everywhere: Why do we measure things and what does 'measuring things' even mean? How is this related to data science?
  2. Using Temperature: How is temperature used in the world?
  3. Measuring temperature: What does a thermometer do and how does it work?
  4. Designing an experiment: We will begin to design an experiment using our thermometers to measure the temperature at different locations. We will look at factors that might have a negative impact on our experiment and we'll look at controlling them. We we will see the importance of validity and reliability.
  5. Data capturing: Before our experiment commences, we will introduce the reader to the concept of data capturing - recording (tabulating) data.
  6. Experimenting with temperature: Here we will outline the classroom activity (experiment) to collect and analyse data. We will introduce the concept of experimental design and see how it can help address issues of reliability and validity.
  7. Analysing our results: We will introduce the concept of 'interrogating' the data by listing a series of questions that the data set might provide insights into. In a later chapter we will look at more sophisticated analysis, for now we show how to extract some meaning / insights from the data we just collected.
  8. Summary: Brings together all the new concepts introduced in this chapter and sets the stage for the next chapter.

Chapter 2: Data Science Goes DigitalChapter Goal: After reading this chapter, readers will understand why there is a tendency to 'go digital' and what it means to read data digitally. We will introduce technology and coding to replicate our experiment and we will begin to explore ways that the digital approach can expand our capabilities and potential as data scientists. We'll use a BBC micro: bit (or any similar device) to measure temperature, all the while looking at our experimental design and how to improve it. By the end of the chapter we will have identified the sort of hardware we need in our data science toolkit.
  1. Making it digital: Why is everything digital? What are the types of thermometers? Explain about digital thermometers and show how they are different to analogue. How can introducing digital improve our temperature experiment from Chapter 1
  2. Using a microprocessor to measure temperature digitally: We will use micro: bit - brief intro to microbit, including sensors that can be used for measure things causing GW (only the ambient temperature sensor).
  3. Using the BBC micro: bit as a thermometer: Programming the micro: bit for reading the air temperature of the classroom. Use MakeCode (or MicroPython) for programming.
  4. Analogue and digital thermometers: Reading temperature simultaneously from a micro: bit and a thermometer. Discuss differences between methods. In particular the difficulties of manual reading, need to read two things same time (thermometer or micro: bit and the clock)
  5. Limitations of micro: bit as a standalone tool: We've seen some limitations with microbit. By itself it provides us with too few tools. What are -ons and how are add-ons used with microprocessors, and what abou

    Author: Philip Meitiner, Pradeeka Seneviratne
    Publisher: Apress
    Published: 07/18/2020
    Pages: 316
    Binding Type: Paperback
    Weight: 1.03lbs
    Size: 9.21h x 6.14w x 0.69d
    ISBN13: 9781484257654
    ISBN10: 1484257650
    BISAC Categories:
    - Computers | Hardware | General
    - Computers | Networking | Hardware

    About the Author
    Pradeeka Seneviratne, a graduate from the Sri Lanka Institute of Information Technology (SLIIT), has almost two decades of experience working on large and complex IT projects related to the industrial world in a variety of fields, in a variety of roles (programmer, analyst, architect, and team leader) with different technologies and software. Pradeeka has also authored several books related to the maker category including Beginning BBC micro: bit (Apress), Beginning LoRa Radio Networks with Arduino (Apress) and Building Arduino PLCs (Apress).
    Philip Meitiner has a background in applied mathematics, psychology, market research, and ed-tech. Philip was was on the original founding members of the Micro: bit Education Foundation where he helped establish the Foundation and is responsible for creating and nurturing the ecosystem, building the reseller and peripheral network and managing the sponsorship scheme (which saw more than 30,000 micro: bits donated to disadvantaged schools in 55 counties). Philip continues to work in the ed-tech sector as a consultant providing services to companies involved with micro: bit. This eclectic mix of careers and experience has instilled in Philip a deep understanding of what it is like to embark on a new learning journey. In addition, his experiences in teaching, market research and IT have given him the perfect mix of skills and knowledge necessary to craft this book.