313306: Data Structure Using Python Syllabus for Artificial Intelligence 3rd Sem K Scheme MSBTE PDF

Data Structure Using Python detailed Syllabus for Artificial Intelligence (AI), K scheme PDF has been taken from the MSBTE official website and presented for the diploma students. For Subject Code, Subject Name, Lectures, Tutorial, Practical/Drawing, Credits, Theory (Max & Min) Marks, Practical (Max & Min) Marks, Total Marks, and other information, do visit full semester subjects post given below.

For all other MSBTE Artificial Intelligence 3rd Sem K Scheme Syllabus PDF, do visit MSBTE Artificial Intelligence 3rd Sem K Scheme Syllabus PDF Subjects. The detailed Syllabus for data structure using python is as follows.

Rationale

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.

Course Outcomes:

Students will be able to achieve & demonstrate the following COs on completion of course based learning

1. Develop Python program using basic syntactical constructs.
2. Perform operations on sequence structures in Python.
3. Implement Modules, Packages in Python for given problem.
4. Design classes for given problem.
5. Implement Linear Data Structure in Python.
6. Develop Python program to implement tree data structure.

Unit I

Introduction and Control Flow statements in Python 1.1 Features of Python – interactive, object oriented, interpreted, platform independent. 1.2 Python building blocks – identifiers, keywords, indentation, variables, comments. 1.3 Python data types: numbers, string, tuples, lists, dictionary. 1.4 Basic operators: arithmetic, comparison/ relational, assignment, logical, bitwise, membership, identity operators , Python operator precedence. 1.5 Control flow: conditional statements (if, if else, nested if),looping in python (while loop, for loop, nested loops) loop manipulation using continue, pass, break, else. Presentations Chalk-Board Hands-on

Unit II

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
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Unit III

Python Modules and Packages 3.1 Modules: writing modules, importing modules, importing objects from modules, Python built- in modules (e.g. numeric and mathematical module, functional programming module). 3.2 Python packages: introduction, writing Python packages. 3.3 Using standard Numpy: methods in Numpy, creating arrays and initializing, reading arrays from files,special initializing functions, slicing and indexing, reshaping arrays, combining arrays, NumPy maths. Chalk-Board Presentations Hands-on

Unit IV

Object Oriented Programming in Python 4.1 Introduction to object oriented programming, creating classes and objects, constructor and destructor in Python. 4.2 Data abstraction and data encapsulation. 4.3 Concept of polymorphism- method overloading and overriding. 4.4 Inheritance and types of inheritance. Chalk-Board Presentations Hands-on

Unit V

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Unit VI

Non-Linear Data Structure. 6.1 Trees – tree Terminology, binary trees: implementation, tree traversals, binary search trees 6.2 Applications of trees – spanning tree, BST , tree traversal – inorder, preorder and postorder concepts. Presentations Hands-on

Suggested Micro Project

Micro project

• The micro project has to be industry based, internet based ,workshop based, laboratory based or field based as suggested by teacher.
1. Develop an application to create tic-tac-toe game.
2. Create a code generator. This can that take text as input, replaces each letter with another letter, and outputs the “encoded” message.
3. Build an interactive quiz. Build a personality or recommendation quiz that asks users some questions, stores their answers, and then performs some kind of calculation to give the user a personalized result based on their answers.
4. Build an alarm clock using snooze function.

Other

• Implement various applications of stacks.

Compute the arithmetic mean along the specified axis using NumPy.

• Present a seminar on different IDE used in Python.

Note :

• Above is just a suggestive list of microprojects and assignments; faculty must prepare their own bank of microprojects, assignments, and activities in a similar way.
• The faculty must allocate judicial mix of tasks, considering the weaknesses and / strengths of the student in acquiring the desired skills.
• If a microproject is assigned, it is expected to be completed as a group activity.
• SLA marks shall be awarded as per the continuous assessment record.
• For courses with no SLA component the list of suggestive microprojects / assignments/ activities are optional, faculty may encourage students to perform these tasks for enhanced learning experiences.
• If the course does not have associated SLA component, above suggestive listings is applicable to Tutorials and maybe considered for FA-PR evaluations.

Laboratory Equipment

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.

Suggested Learning Materials

1. Rao, K. Nageswara Shaikh Akbar Python Programing Scitech Publications (India) Pvt. Ltd. ISBN: 9789385983450
2. Michael T. Goodrich, Roberto Tamassia Data Structures and Algorithms in Python Wiley publication New Delhi 2016 ISBN: 978-81- 265-5423-2
3. Beazley, David Python Essential Reference 4th Edition, Addison-Wesley Professional, ISBN: 9780672329784
4. Dr.Basant Agarwal Hands-On Data Structures and algorithms with Python 3rd Edition, Packt publisher, ISBN : 9781801073448

Learning Websites & Portals

1. https://onlinecourses.nptel.ac.in/noc22_cs26/preview Online Learning Initiatives by IIT faculties.
2. https://www.geeksforgeeks.org/graph-data-structure-and-algor ithms/ Data structures in Python
3. https://www.freecodecamp.org/news/object-oriented-programmin g-in-python/ Object Oriented Programming Concepts
4. https://realpython.com/python3-object-oriented-programming/ Basics Object Oriented Programming Concepts.

Note : Teachers are requested to check the creative common license status/financial implications of the suggested online educational resources before use by the students

For detail Syllabus of all other subjects of Artificial Intelligence, K scheme do visit Artificial Intelligence 3rd Sem Syllabus for K scheme.

For all Artificial Intelligence results, visit MSBTE Artificial Intelligence all semester results direct links.