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  • Format: PDF

This handbook provides a hands-on experience based on the underlying topics, and assists students and faculty members in developing their algorithmic thought process and programs for given computational problems. It can also be used by professionals who possess the necessary theoretical and computational thinking background but are presently making their transition to Python.
Key Features:
Discusses concepts such as basic programming principles, OOP principles, database programming, GUI programming, application development, data analytics and visualization, statistical analysis,
…mehr

  • Geräte: PC
  • ohne Kopierschutz
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  • Größe: 45.44MB
Produktbeschreibung
This handbook provides a hands-on experience based on the underlying topics, and assists students and faculty members in developing their algorithmic thought process and programs for given computational problems. It can also be used by professionals who possess the necessary theoretical and computational thinking background but are presently making their transition to Python.

Key Features:

  • Discusses concepts such as basic programming principles, OOP principles, database programming, GUI programming, application development, data analytics and visualization, statistical analysis, virtual reality, data structures and algorithms, machine learning, and deep learning
  • Provides the code and the output for all the concepts discussed
  • Includes a case study at the end of each chapter


This handbook will benefit students of computer science, information systems, and information technology, or anyone who is involved in computer programming (entry-to-intermediate level), data analytics, HCI-GUI, and related disciplines.


Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Dimitrios Xanthidis holds a PhD in Information Systems from University College London. For the past 25 years, he has been teaching computer science subjects with a focus on programming and software development, and data structures and databases in various tertiary education institutions. Currently, he is working in Higher Colleges of Technology in Dubai, U.A.E. Dimitrios' research interests and work revolve around the topics of data science, machine learning/deep learning, virtual/augmented reality, and emerging technologies. Christos Manolas holds a PhD in Stereoscopic 3D Media (University of York, UK), and degrees and qualifications in Postproduction (MA), Music Technology (MSc), Music Performance, Software Development, and Media Production. Christos' career includes work as a software developer, musician, audio producer, and educator for over 20 years. His research interests include multimodal (audiovisual) perception, spatial audio, interactive and immersive media (VR/AR/XR), and generally the impact and role of digital technologies on media production. Ourania K. Xanthidou is a PhD researcher at Brunel University, London. She holds an MSc in Computer Science from the University of Malaya, Kuala Lumpur, Malaysia. She has more than 15 years of involvement with the IT industry in the form of supporting IT departments of SMEs and more than 5 years of teaching experience in tertiary education. Ourania's research interests are in the areas of eHealth, smart health, databases, web application development, and object-oriented programming with a focus on application development for VR/AR/XR. Han-I Wang holds a PhD in Health Economics from the University of York, UK. Han-I has been working as a research fellow for over 10 years, starting at the Epidemiology & Cancer Statistics Group (ECSG) before joining the Mental Health and Addiction Research Group (MHARG) at the University of York, UK. Her area of expertise spans across cost analysis, health outcome research, and decision modeling using complex patient-level data, and her main research interests are related with the exploration of different decision-modeling techniques and their application to predict healthcare expenditure, patients' quality of life, and life expectancy.