Python Programming for Biomedical Engineering (3150312)

Course Files for Complete Python 3 Course

Semester – V Python Programming for Biomedical Engineers

Type of course: Open elective

PrerequisiteComputer Concepts and C Programming

Rationale: Python is a modern language useful for writing compact codes specifically for programming in the area of Data Analytics, AI and scientific computing as well as processing tool for Signal and Image Processing. This course covers the basics and modular Python programming to harness its potential for development of modern Biomedical Equipment.

Teaching and Examination Scheme:

Teaching Scheme Credits Examination Marks Total Marks L T P C Theory Marks Practical Marks ESE (E) PA (M) ESE (V) PA (I) 2 0 2 3 70 30 30 20 150

Content:

Overview of Python

Programming languages, Software development, thrust area of Python, Installing Python Jupyter notebook Parts of Python Programming Language: Identifiers, Keywords, statements and expressions, variables, Operators, Precedence and Associativity, Data types, Indentation, comments, reading input, print output, Type conversions, type () function and Is Operator, Dynamic and strongly typed language Control Flow Statements: If decision control flow, if..else decision control flow, if..elif..else decision control, Nested if statement, while loop, for loop, continue and break statements

Functions:

Built in functions, commonly used modules, definition and calling the function, return statement and void function, scope and lifetime of variables, Default Parameters, Keyword Arguments, *args and **kwargs, Command Line Arguments String: Creating and Storing Strings, Basic String Operations, Accessing Characters in String by Index Number, String Slicing and Joining, String Methods, Formatting Strings Lists: Creating Lists, Basic List Operations, Indexing and Slicing in Lists, Built-In Functions Used on Lists, List Methods, The del Statement.

Dictionaries:

Creating Dictionary, Accessing and Modifying key, value Pairs in Dictionaries, Built-In Functions used on Dictionaries, Dictionary Methods, The del Statement,

Tuples and Sets:

Creating Tuples, Basic Tuple Operations, Indexing and Slicing in Tuples, Built-In Functions Used on Tuples, Relation between Tuples and Lists, Relation between Tuples and Dictionaries, Tuple Methods, Using zip () Function, Sets, Set Methods, Traversing of Sets, Frozenset

Files:

Types of Files, Creating and Reading Text Data, File Methods to Read and Write Data, Reading and Writing Binary Files, The Pickle Module, Reading and Writing CSV Files, Python os and os.path Modules 04 15

Introduction to Data science:

NumPy and Pandas with Python, Graphing with Matplotlib pyplot: Line Graphs, Scatter Graph, Pie Charts, Bar Charts,Figures and Subplot, 3D Graphs Case Study: Bio-Signal Plotting using Matplotlib/Pandas Library.

Note: This specification table shall be treated as a general guideline for students and teachers. The actual distribution of marks in the question paper may vary slightly from the above table.

Reference Books:

Gowrishankar S, Veena A, “Introduction to Python Programming”, 1st Edition, CRC Press/Taylor & Francis, 2018. ISBN-13: 978-0815394372
Mark Summerfield, “Programming in Python 3: A Complete Introduction to the Python Language”, Pearson Education
Zed A. Shaw, “Learn Python The Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code, 3rd edition” , Adisson-Wesley
Erik Westra, “Modular Programming with Python: introducing modular techniques for building sophisticated programs using Python”, Packt Publishing
David Love, “Tkinter GUI Programming by Example”, Packt Publishing Ltd.
John Hunt “Advanced Guide to Python 3 Programming”, Springer

Course Outcomes:

Sr.No. CO statement Marks % weightage CO-1 Understand the fundamental of Python syntax and be fluent in the use of Python control flow statements. 15% CO-2 Express proficiency in the handling of strings, functions and lists. 15% CO-3 Learn methods to create and manipulate Python programs by utilizing the data structures like dictionaries, tuples and sets. 20% CO-4 Recognize the commonly used operations involving file systems. 25% CO-5 Understand the Pandas and Numpy library for data science operation and plotting various Biosignal using Matplotlib. 25%

List of Experiments:

Introduction to Jupyter Notebook and python script in CMD.
Introduction to basic operations in python.
Develop programs to understand the control structures of python.
Develop programs to learn functions, string and lists in python.
Develop programs to learn Dictionaries, Tuples and sets in python.
Develop programs to learn Files operators in python.
Introduction to data science in python
Learn to plot different types of graphs using PyPlot.

List of Open Source Software/learning website:

● https://docs.spyder-ide.org/ ● https://wiki.python.org/moin/BeginnersGuide ● https://www.programiz.com/python-programming

Thanks!

bhparmar/3150312