Preamble
The main objective of this course is to familiarize the student with Python programming concepts, syntax, semantics, and the runtime environment, as well as with general coding techniques and object-oriented programming.</p
| Course Name | Computer programming |
| Course Code | 24MMD204 |
| Program | B. Sc. Honors (with Research) in Molecular Medicine |
| Semester | 3 |
| Credits | 2 |
| Campus | Kochi |
The main objective of this course is to familiarize the student with Python programming concepts, syntax, semantics, and the runtime environment, as well as with general coding techniques and object-oriented programming.</p
Basic concepts in Python: Python runtime environment, Python variables, Python basic Operators, Understanding python blocks. Python Data Types, Declaring and using Numeric data types and functions. Conditional statements and loop statements in Python
Python Complex data types: Strings and string functions, List and Tuple manipulation, Dictionary and Set operations.
Functions and modules in Python: defining functions, scope, types of arguments, the anonymous function(lambda), map, filter, reduce and zip functions. Introduction to Python modules and creating own modules.
Exception handling in Python. Python File Operations: Reading files, Writing files in python. Python directories.
Object oriented programming in Python: Defining classes and instantiating objects. Python Constructors and destructors. Inheritance and polymorphism in Python.
Pthon-mysql connectivity, Establishing Connection, CURD operations.
Fundamentals for data science: Introduction to Jupyter notebook, Programming using Numpy, Pandas and matplotlib libraries.
Course Outcomes
CO1 Understand Python variables, operators and data types
CO2 Get an idea about Python control structures and loops
CO3 Understand Python complex datatypes
CO4 Understand Python functions
CO5 Get an idea about NumPy and Pandas
Program outcome (PO)
PO1: Bioscience Knowledge
PO2: Problem Analysis
PO3: Design/Development of Solutions
PO4: Conduct Investigations of complex problems
PO5: Modern tools usage
PO6: Bioscientist and Society
PO7: Environment and Sustainability
PO8: Ethics
PO9: Individual &Team work
PO10: Communication
PO11: Project management & Finance
PO12: Lifelong learning
| P O
C O |
P
O 1 |
P
O 2 |
P
O 3 |
P
O 4 |
P
O 5 |
P
O 6 |
P
O 7 |
P
O 8 |
P
O 9 |
P
O 1 0 |
P
O 1 1 |
P
O 1 2 |
P
S 0 1 |
P
S O 2 |
P
S O 3 |
| CO1 | 1 | 3 | 2 | – | – | – | – | – | – | – | – | – | – | – | – |
| CO2 | 2 | 3 | 3 | – | – | – | – | – | – | – | – | – | – | – | – |
| CO3 | 2 | 3 | 3 | – | – | – | – | – | – | – | – | – | – | – | – |
| CO4 | 2 | 3 | 3 | – | – | – | – | – | – | – | – | – | – | – | – |
| CO5 | 2 | 3 | 3 | – | 1 | – | – | – | – | – | – | – | – | – | – |
Program Specific Outcome (PSO)
PSO 1 – Chemical and physical basis of biology
PSO 2 – Computational science in biology and medicine
PSO 3 – Biochemical and physiological complexity in biology and medicine
PSO 4 – Molecular technology in biology and medicine
PSO 5 – Cell based approaches in diagnosis and therapy
PSO 6 – Microorganisms in medicine
PSO 7 – Nanoscale entities and its significance in medicine
PSO 8 – Tissue architecture engineering in medicine
PSO 9 – Compounds as drugs and its efficacy
PSO 10 – Bioinformatics and artificial intelligence in medicine
PSO 11 – Technology in personalizing medicine
PSO 12 – Protein structural complexity in medicine
PSO 13 – Projecting science and medicine to public
| PSO1 | PSO2 | PSO3 | PSO4 | PSO5 | PSO6 | PSO7 | PSO8 | PSO9 | PSO10 | PSO11 | PSO12 | PSO13 | |
| CO 1 | – | 2 | – | – | – | – | – | – | – | 3 | – | – | 2 |
| CO 2 | – | 2 | – | – | – | – | – | – | – | 3 | – | – | 2 |
| CO 3 | – | 2 | – | – | – | – | – | – | – | 3 | – | – | 2 |
| CO 4 | – | 2 | – | – | – | – | – | – | – | 3 | – | – | 2 |
| CO 5 | – | 2 | – | – | – | – | – | – | – | 3 | – | – | 2 |
| Internal Assessment – 40% | ||
| Periodical 1 | Exam | 15% |
| Periodical 2 | Exam | 15% |
| Continuous Assessment | Assignment/Test/Quiz | 10% |
| 40% | ||
| End Semester Examination- 60% | ||
| Theory Exam | 30% | |
| Lab Exam | 30% | |
| 60% | ||
| Total | 100% |
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