CHRIST (Deemed to University), Bangalore

DEPARTMENT OF COMPUTER SCIENCE

School of Sciences

Syllabus for
Doctor of Philosophy (Data Science)
Academic Year  (2020)

 
3 Semester - 2019 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
RES131 FOUNDATIONS OF RESEARCH - 4 4 100
RES132 RESEARCH PUBLICATION - 4 4 100
RSC131 METHODS IN RESEARCH FOR SCIENCE - 4 4 100

RES131 - FOUNDATIONS OF RESEARCH (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

  

Philosophical foundations of research are the scenario of higher education provided. Various approaches to research,  review of literature and application of theory are also included.

Course Outcome

  • Reflections on the hilosophical foundations of research
  • Knowledge of the history and context of higher education
  • Knkowledge about various approaches to research
  • Review of literature
  • Application of theory
Unit-1
Teaching Hours:14
Philosophical foundations of Research
  

Ethics and values in Research, Scope of Interdisciplinary, multi-disciplinary and cross disciplinary research, Doctoral Supervision and supervisory styles, Types of Doctoral Research and implications, Pedagogy and Research: Research Informed teaching and Problem Based learning

Unit-2
Teaching Hours:16
Higher Education
  

History of Higher Education, The notion of University, Disciplines and Domain knowledge, Accreditations and Educational Policy, The Public Intellectual

Unit-3
Teaching Hours:16
Approaches to Research & Review of literature
  

Quantitative, Qualitative and mixed methods, Relationship between Research Paradigms, Designs and methods, Research Designs and its types, Research methods, Conceptualisation of Research problem in different research approaches, Research questions, Review of literature: Research Topic, Review of Literature in quantitative, qualitative and mixed methods, Steps in conducting Literature Review, Literature map, Abstracting studies, Literature Summary matrix, , Types of Reviews, Identification of Research Gap, Overview of Style manuals, Operational and Theoretical Definitions

Unit-4
Teaching Hours:14
Application of theory
  

Theory in quantitative research, Writing a Quantitative theoretical framework, Theory in Qualitative and mixed methods, Research proposals format for quantitative, Qualitative and mixed methods (Practical)

Text Books And Reference Books:

Creswel, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches. Los angeles: University of Nebraska–Lincoln.

Essential Reading / Recommended Reading
  • Altbach, P. G., Reisberg, L., & Rumbley, L. E. (2019). Trends in global higher education: Tracking an academic revolution. BRILL.
  • Denzin, N.K. and Lincoln, Y.S. (eds.). (2011). The Sage handbook of qualitative research. Thousand Oaks: Sage.
  • Fink, A. (2019). Conducting research literature reviews: From the internet to paper. Sage
  • Fuller, S. (2019). Philosophy of science and its discontents. Routledge.
  • Herr, K. and Anderson, G.L. (2005). The action research dissertation. Thousand Oaks, CA: Sage.
  • Johnson, A.P. (2005). A short guide to action research. Boston: Pearson Education. 
  • Kindon, S., Pain, R., and Kesby, M. (eds). (2007). Participatory action research approaches and methods. NY: Routledge.
  • McNiff, J. and Whitehead, J. (2006). All you need to know about action research. Thousand Oaks, CA: Sage. 
  • Reason, P. and Bradbury, H. (eds.). (2006). Handbook of action research. Thousand Oaks, CA: Sage. 
  • Stringer, E.T. (2007). Action Research. Thousand Oaks, CA: Sage. 
Evaluation Pattern
  • Internal Assessements are designed to improve knowledge of and skill in all sections of the course
  • Each unit is evaluated separately and all units have equal weightage
  • Not attending more than four hours of lectures of each unit will require the scholar to repeat the unit

RES132 - RESEARCH PUBLICATION (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

  

This course introduces the candidates to various journals, proceedings, books and conferences. It also helps them in collaborating with the scholars of various fields.

Learning Objectives

  • To provide the researchers the information, knowledge, and skills to identify academic journals of various quality
  • To be able to know about the industry of publishing journals 
  • To teach the researchers how to submit articles to journals
  • To understand the advantages, disadvantages, responsibilities and ethics of collaborative publishing

Course Outcome

On Successful completion of this course, research scholars will be able to:

  • choose journals based on their quality
  • work in different processes in journal publishing
  • submit research articles independently
  • collaborate with scholars and researchers
Unit-1
Teaching Hours:15
Quality Measures of Journals
  
  • The concept and history of indexing
  • Indexing Agencies
  • Various Review Methods
  • Indexing Parameters
  • Open Access Publications,
Unit-2
Teaching Hours:15
Journal Publishing
  
  • Types of Journals
    • Domain based Journals
    • University Publications
    • Private Publications
    • Individual Publications
    • Regional Publications
    • Society/Association Publications
  • Economics of Journal Publishing
  • Article Processing Charges
Unit-3
Teaching Hours:15
Article Submission
  
  • Journal Databases
  • Journal Template
  • Plagiarism
  • Submission Processes: Editorial Manager, OJS, Referee List
Unit-4
Teaching Hours:15
Academic Collaboration
  
  • Collaboration in Research
  • Collaboration in Research Publication
  • Merits of Collaboration
  • Authorship preferences
  • Tools of Collaboration
  • Types of Authors
Text Books And Reference Books:

Coser, L. A., Kadushin, C., & Powell, W. W. (1982). Books: The culture and commerce of publishing (p. 22). New York: Basic Books.

Essential Reading / Recommended Reading
  • Cross, R., Taylor, S & Zehner, D (2018). Collaboration Without Burnout,  Harvard Business Review, July–August,  pp.134–137.
  • Ferris LE & Winker MA, (2017). Ethical issues in publishing in predatory journals, Biochem Med (Zagreb). 27(2):279-284. doi: 10.11613/BM.2017.030.
  • Habibzadeh, F., & Simundic, A.-M. (2017). Predatory journals and their effects on scientific research community. Biochemia Medica, 27(2), 270–272. http://doi.org/10.11613/BM.2017.028
  • Laine, C., & Winker, M. A. (2017). Identifying predatory or pseudo-journals. Biochemia Medica, 27(2), 285–291. http://doi.org/10.11613/BM.2017.031
  • Lippi, G. (2017). How do I write a scientific article?—A personal perspective. Annals of Translational Medicine, 5(20), 416. http://doi.org/10.21037/atm.2017.07.43
  • Prater, C. 8 Ways to Identify a Questionable Open Access Journal, https://www.aje.com/en/arc/8-ways-identify-questionable-open-access-journal/ accessed on July 3, 2018
  • Saha, I & Paul, B (2017). Research submission: Some technicalities and vital links, Med J Armed Forces India. 74(2): 165–168. doi: 10.1016/j.mjafi.2017.10.006
  • Shewan, L. G., & Coats, A. J. (2010). Ethics in the authorship and publishing of scientific articles.
Evaluation Pattern
  • Internal Assessements are designed to improve knowledge of and skill in all sections of the course
  • Each unit is evaluated separately and all units have equal weightage
  • Each unit has about 12 lecture hours and 3 library/practical hours
  • Not attending more than four hours of lectures of each unit will require the scholar to repeat the unit

RSC131 - METHODS IN RESEARCH FOR SCIENCE (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

  

This course introduces scholars to the Python Programming, MATLAB, Origin, Tikz and LaTeX Draw, thus enabling them to develop skills of numeric computation, data analysis and visualization, programming and algorithm development and application development. 

Course Learning Objectives

  • To provide the knowledge of MathLab, Origin and Python. 
  • To explore the possibilities of using Python language as a tool for learning Mathematics. 
  • To develop the skill of preparing documents using LaTeX also to develop the skill of drawing  figures using Tikz

Course Outcome

On successful completion of the course, the students should be able to:

  • Explore and visualize data using MATLAB and ORIGIN commands and functions
  • Import data from heterogeneous sources
  • Build predictive models using MATLAB and ORIGIN Toolbox
  • Prepare documents using LaTeX
  • Draw mathematical figures using Tikz
Unit-1
Teaching Hours:16
Origin: Data Analysis and Technical Graphics Software
  

Introduction to ORIGIN, Introduction to ORIGIN Graphing Elements, Creating Simple Graphs, Graph Customization and Technicalities, Workbook, Worksheets and Columns, Graphical Exploration of Data, Themes and Templates, Graphing Data from multiple sheets, Row Statistics, Data Analysis [Peak Analysis, Curve Fitting, Statistics].

Unit-2
Teaching Hours:14
Python Programming
  

Installation, IDES, Introduction, Hardware components, Software components, The Operating system, Programming in Python, formatted printing, Visualizing data with graphs, Algebra and symbolic math with Symphy, Graphs as a python class, Graph Density, Distance and diameter of a graph, The complete python graph class.

Unit-3
Teaching Hours:14
Data analysis using MATLAB
  

Introduction to MATLAB [Variables, Matrices, Built-in Functions, Arrays, Structure, Cell], MATLAB Programming [Inline functions, control structures, Programming syntax, Script files and Functions files], solution of Differential equations, Data Visualization and Data Exploration Techniques [Data import/export, Plots, Statistics basics], Models for Data Analysis [Regression Models, Classification Models [Using of Statistic Toolbox].

Unit-4
Teaching Hours:16
Latex and Tikz
  

Introduction, Preparing an input file, The document, Document class, The title page, Changing the type style, Mathematical formulas, Mathematical Symbols, Defining commands and environments, Other document classes, Pictures and colors, Erros, The bibliography database, Reference manual, Drawing lines and curves using Tikz, Filling up areas, Putting labels in Pictures, Integration with beamer.

Text Books And Reference Books:
  • A very minimal introduction to TikZ, Jacques Cremer, Toulouse School of Economics.
  • D. M. Etter, Introduction to MATLAB, 3rd ed., Prentice Hall, 2014.
  • Doing Maths with Python Amit Saha, no starch press:San Fransisco, 2015.
  • Origin 9.1 User Guide – OriginLab.

 

Essential Reading / Recommended Reading
  • Deng, E., & Huang, L. (2019). An Elegant LATEX Template for Books.
  • Johansson, R. (2019). Introduction to computing with python. In Numerical Python (pp. 1-41). Apress, Berkeley, CA.
  • Lode, C. (2019). Better Books with LaTeX: Self-Publish Your Book on Amazon and Google. Clemens Lode Verlag eK.
  • Origin: Data Analysis and Technical Graphics Software, Microcal Software, Microcal Software Incorporated, 1999
  • Payne, J. R. (2019). Introduction to Computer Programming and Python. In Python for Teenagers (pp. 1-16). Apress, Berkeley, CA.
  • S. Attaway, MATLAB: A Practical Introduction to Programming and Problem Solving, 3rd Edition, 3rd ed., Elsevier Inc., 2013.
  • W. L. Martinez et. al., Exploratory Data Analysis with MATLAB, 2nd ed., CRC Press, 2010.
Evaluation Pattern
  • Internal Assessements are designed to improve knowledge of and skill in all sections of the course
  • Each unit is evaluated separately and all units have equal weightage
  • Not attending more than four hours of lectures of each unit will require the scholar to repeat the unit