Back close

Course Detail

Course Name Introduction to Scientific Computing Using Python
Course Code 25CSA205
Semester 3
Credits 3
Campus

Syllabus

UNIT 1: Introduction to Python ProgrammingHistory of Python Programming Language, Thrust areas of Python in physics, Integrated Development Environments, installation and use of python distribution: Anaconda, Spyder, Jupiter notebooksFundamental programming with Python : Designing a Program, identifiers, keywords, operators, and expressions. Arithmetic, Logical and Assignment operators, Precedence, Data types: Basic data types: Strings and numbers, displaying an output, type conversion, basic string operations& methods, format specifiersUNIT 2: Tuples, Lists & DictionariesTuples: immutable sequences, creating tuple, basic tuple operations. Lists: mutable sequences, basic list operations, List methods Dictionaries: basic dictionary operations, dictionary methodUser input variable.UNIT 3: Control structuresDecision Structures: If ,If —-else, if .elif..else, nested if decision flow statements.Repetition Structures: condition controlled: while loop. Count controlled: for loop, sentinals, continue and break statements, try and except statementsUNIT 4: Functions & FilesBuilt in function, modules, void function, flow charting, hierarchy charts, Local variables and scope, passing an argument function, value returning functions, Random number generationFiles: introduction to file input and outputUNIT 5: Scientific computing packagesNumpy: -Array object, creating array, matrix, indexing, slicing, resizing, reshaping, arithmetic operations, functions, matrices and vector operations Matplotlib: basic plotting, Scipy: Linear algebra operations, equation solving

Objectives and Outcomes

PrerequisitesThe students should have studied any basic computer language as a prerequisite for the course.Objective of the courseIn this course students are introduced to use Python as a tool to solve Physics problems. The emphasis is to learn using a high level programming language without actually going through the logic behind the equations that are to be coded. A minimal understanding of the basic mathematics is assumed. This develops familiarity and equips them to code a large number of physics problems and learn how to obtain results and plots using the software.At the end of the course students will be able to:CO1 : Master the fundamentals of writing Python scripts.CO2 : Use basic mathematical methods in Python to solve physical problemsCO3 : Write Python functions to facilitate code reuse.CO4 : Discover how to work with lists and sequence data.CO5 : Use python libraries like NumPy, SciPy etc to mathematically evaluate physical systems

Text Books / References

Text Book1.Mark Lutz, Learning Python O’Reilly Media,2013.Reference Books1.Robert Johansson, Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Apress, 2019.2.Rubin H. Landu, Manuel J. Paez, and Cristian C.Bordeianu, Computational Physics Problem solving with Python – Third Edition, Wiley VCH, 2015.

DISCLAIMER: The appearance of external links on this web site does not constitute endorsement by the School of Biotechnology/Amrita Vishwa Vidyapeetham or the information, products or services contained therein. For other than authorized activities, the Amrita Vishwa Vidyapeetham does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this web site.

Admissions Apply Now