About the Course Python For Machine Learning - CST 283 - KTU Minor



CST283 :PYTHON FOR MACHINE LEARNING
CATEGORY:MINOR
L T P :3 1 0
CREDIT: 4
YEAR OF INTRODUCTION:2019 

Preamble: This is a programming course for awarding B. Tech. Minor in Computer Science and  Engineering with specialization in Machine Learning. The objective of the course is to provide learners an insight into Python programming, and develop programming skills to manage the development of software systems. It covers programming environment, important instructions,data representations, intermediate level features, Object Oriented Programming and file data processing of Python. This course lays the foundation to develop web applications, Machine Learning, and Artificial Intelligence-based applications and tools, Data Science and Data Visualization applications.

Prerequisite: Nil

Mark Distribution
Total Marks     CIE Marks     ESE Marks     ESE Duration
150                     50                 100                     3

Continuous Internal Evaluation Pattern:
Attendance : 10 marks
Continuous Assessment Test : 25 marks
Continuous Assessment Assignment : 15 marks 

Internal Examination Pattern

Each of the two internal examinations has to be conducted out of 50 marks. The first series test shall be preferably conducted after completing the first half of the syllabus and the second series test shall be preferably conducted after completing the remaining part of the syllabus. There will be two parts: Part A and Part B. Part A contains 5 questions (preferably, 2 questions each from the completed modules and 1 question from the partly completed module), having 3 marks for each question adding up to 15 marks for part A. Students should answer all questions from Part A. Part B contains 7 questions (preferably, 3 questions each from the completed modules and 1 question from the partly completed module), each with 7 marks. Out of the 7 questions, a student should answer any 5.


End Semester Examination Pattern:

There will be two parts; Part A and Part B. Part A contains 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which a student should answer any one. Each question can have a maximum of 2 sub-divisions and carries 14 marks.

Course Outcomes: After the completion of the course the student will be able to

CO1:Write, test and debug Python programs (Cognitive Knowledge level: Apply)
CO2: Illustrate uses of conditional (if, if-else, if-elif-else and switch-case) and iterative
(while and for) statements in Python programs (Cognitive Knowledge level: Apply)
CO3: Develop programs by utilizing the modules Lists, Tuples, Sets and Dictionaries in Python (Cognitive Knowledge level: Apply)
CO4: Implement Object Oriented programs with exception handling (Cognitive Knowledge level: Apply)
CO5: Write programs in Python to process data stored in files by utilizing the modules Numpy, Matplotlib, and Pandas (Cognitive Knowledge level: Apply)

Sample CO Level Assessment Questions
Course Outcome1(CO1): What is type conversion? How is it done in Python?
Course Outcome 2(CO2): Write a Python program which takes a positive integer n as input and finds the sum of cubes all positive even numbers less than or equal to the number.
Course Outcome 3(CO3): Given is a list of of words, wordlist, and a string, name. Write a Python function which takes wordlist and name as input and returns a tuple. The first element of the output tuple is the number of words in the wordlist which have name as a substring in it. The second element of the tuple is a list showing the index at which the name occurs in each of the words of the wordlist and a 0 if it doesn’t occur.
Course Outcome 4(CO4): Write a Python program to implement the addition, subtraction, and multiplication of complex numbers using classes. Use constructors to create objects. The input to the program consist of real and imaginary parts of the complex numbers.
Course Outcome 5(CO5): Given a file “auto.csv” of automobile data with the fields index, company, body-style, wheel-base, length, engine-type, num-of-cylinders, horsepower, average-mileage, and price, write python code to
1) Clean and Update the CSV file
2) Print total cars of all companies
3) Find the average mileage of all companies
4) Find the highest priced car of all companies.

Comments

Post a Comment

Popular posts from this blog

Python For Machine Learning - CST 283 - KTU Minor Notes- Dr Binu V P

Dr Binu V P -About Me About the Course Syllabus Previous Year Question Paper and Answer Key CST 283 Python For Machine Learning Dec 2020 Previous Year Question Paper and Answer Key CST 283 Python For Machine Learning Dec 2021 Previous Year Question Paper CST 283 Python For Machine Learning Dec 2022  Previous Year Question Paper CST 283 Python For Machine LearningFeb 2024 Module-I Programming Environment and Python Basics 1.Introduction to Python 2.Running Python Program- IDLE,Interactive Shell, Jupyter notebook 3.Identifiers, variables and keywords 4.Basic Python data types- numbers and strings, type conversion 5.Operators 6.Operator precedence and expression evaluation 7.Input and output- input() and print() 8.Built-in functions, modules and packages 9.The software development process 10.Simple programs to begin with, comments and statements 11.Basic Programs to try 12.Programs using built-in functions and modules 13.Sample Programs ( contact) Module-II Building Python Progra...
Read more

KTU Python for machine learning Sample Question Paper and Answer Key Dec 2020

  APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY THIRD SEMESTER B.TECH DEGREE EXAMINATION, DECEMBER 2020 Course Code: CST283 Course Name: Python for Machine Learning Max. Marks: 100   Duration: 3 Hours   PART A     Answer all questions. Each question carries 3 marks Marks   1 Explain the input statement with an example. How the type conversion is done 3   2 Illustrate the concept of modules and explain with example how they are used in Python programs 3   3 Write a Python program to print all prime numbers less than 100. 3   4 Demonstrate Lambda function with an example 3   5 Use list to read n names an...
Read more

46.Classes and Objects in Python- Accessors and mutators

Python is an object-oriented programming language, which means that it provides features that support object-oriented programming. The basic components of object oriented programming are  classes and objects. A Class is a blue print to create an object. It provides the definition of basic attributes(properties) and functions of objects. Object is a running instance of the class having the identity(name), properties( values) and behaviors(functions). The object oriented program thus consist of object definitions (classes) and most of the computations and functions are mentioned as operations on the object.Each object definition corresponds to some object or concept in the real world, and the functions that operate on these object correspond to the ways real-world objects interact. We have learned objects of string, list, tuple etc…and used the properties and functionalities of these objects which are built into the Python. Now we are going to create our own(user defined) objects. Th...
Read more