CHRIST (Deemed to University), Bangalore

DEPARTMENT OF life-sciences

sciences

Syllabus for
Master of Philosophy ( Botany)
Academic Year  (2019)

 
1 Semester - 2019 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
RSC131 METHODS IN RESEARCH FOR SCIENCE - 4 4 100

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