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Python is a programming language with a simple syntax, and a wide set of useful libraries. It is an interpreted language, with a rich programming environment, including a robust debugger and profiler. While it is easy for beginners to learn, it is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types, Python data types, Python program conditional flow control, Python program loop flow control, Python functions, modules and packages, list and dictionary manipulations, Python file handling, Python regular expression, Python exception handling, introduction to R

2. Student Learning Outcomes
By the end of the course, the student should be able to:

· Illustrate the process of writing, compiling and executing programs using appropriate predefined functions
· Identify and apply the language features and constructs to write program(s).
· Model engineering problems in a computation framework. Demonstrate the ability to use flowcharts and programming language in real world problem-solving
· Demonstrate an understanding of tools and techniques used in software and sustain with the changing technology in business.
3. Required Textbooks and Reading Material
1. Fundamentals of Python (1st Edition) by Kenneth A. Lambert, Lambert/ Juneja, ISBN: ISBN-13: 978-81-315-2903-4 / 9788131529034, CENGAGE
2. Zed A. Shaw, “Learn Python 3 the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code”, Addison-Wesley Professional, 2017; ISBN: 0134693906, 9780134693903
3. Python Programming for the Absolute Beginner, 3rd Edition Michael Dawson; ISBN: 9781435455009

4. Tentative Session Plan

Session	Topic (No. of Sessions)	Coverage	Pedagogy
2	introduction to Python	installation and working with Python, understanding Python variables, Python basic operators, understanding Python blocks	Class Assignment (Reading Material to be provided)
2	Python data types	declaring and using numeric data types: int, float, complex, using string data type and string operations, defining list and list slicing, use of tuple data type	Lecture & lab. (lab assignments)
1	Python program conditional flow control	conditional blocks using if, else and elif	Lecture & lab. (lab assignments)
2	Python program iterations flow control	simple for loops in Python, for loop using ranges, string, list and dictionaries, use of while loops in Python, loop manipulation using pass, continue, break and else, programming using Python conditional and loops block	Lecture & lab. (lab assignments)
3	Python functions, modules and packages	organizing Python codes using functions, organizing Python projects into modules, importing own module as well as external modules, understanding packages, powerful lamda function in Python, programming using functions, modules and external packages	Lecture & lab. (lab assignments)
3	list and dictionary manipulations	building blocks of Python programs, understanding string in build methods, list manipulation using in build methods, dictionary manipulation, programming using string, list and dictionary in build functions	Lecture & lab. (lab assignments)
2	Python file operation	understanding read functions, read(), readline() and readlines(), understanding write functions, write() and writelines(), manipulating file pointer using seek, programming using file operations, reading config files in Python, writing log files in Python	Lecture & lab. (lab assignments)
2	Python regular expression	powerful pattern matching and searching, power of pattern, searching using regex in Python, real time parsing of networking or system data using regex, password, email, url validation using regular expression, pattern finding programs using regular expression	Lecture & lab. (lab assignments)
1	Python exception handling	avoiding code break using exception handling, safeguarding file operation using exception handling, handling and helping developer with error code, programming using exception handling	Lecture & lab. (lab assignments)
2	introduction to R	installation and starting with R. basic arithmetic & logical operators in R. handling matrixes, writing plotting functions	Lecture & lab. Reading Material to be provided

5. Evaluation

No.	Evaluation Component	Duration	Weightage	Data & Time	Nature of Component
1	Quiz	10 min	10%		Closed Book
4	Mid Sem	60 min	20%		Closed Book
3	End Sem	2 Hrs	40%
4	Lab Assignments & Performance		30%		Continuous

6. Academic Integrity
· Students are requested to prepare the cases earmarked before coming to the class
· Students will have hands-on lab sessions as and when lab is available
· Students are expected to be punctual and attentive in class
· Mobile phones cannot be used in the classroom
· Attendance policy of the school will be strictly enforced
· Students should strictly adhere to the deadlines for project/assignment submissions. Any kind of unfair means or coping from others will be treated as serious offence and penalized.
· Retest or re-exam will not be entertained in case of a student missing the test/exam
· The faculty may modify part of the course outline/evaluation composition at his discretion during the course
Created By: Alora Kar on 06/26/2019 at 10:28 AM
Category: MBA(Exe.)BA-2019-20 T-II Doctype: Document