MACHINE LEARNING FOR DATA SCIENCE Lab

 SEMESTER :  IV                                         HOURS/WEEK   : 4

CODE :  P20CA4P7                                        CREDITS    : 3

 

Core Practical VII :  MACHINE LEARNING FOR DATA SCIENCE LAB

 

           List of Practical:

1. Vector operations in R

2. Managing data in R

•          Descriptive Statistics
  
•          Managing the Data
•             Movies.csv 
•            Genres.csv 

3. Forecasting using Regression techniques

4. Classification using Naives Bayes

5. Classification using Decision trees

6. Finding patterns using Association Rules

7. Clustering with K-Means

MACHINE LEARNING FOR DATA SCIENCE

SEMESTER:  IV                                           HOURS/WEEK: 4

CODE:  P20CA411                                              CREDITS    : 3

 

Core XI: MACHINE LEARNING FOR DATA SCIENCE

Syllabus: ML for DS - Theory

MCQs: ML MCQs

Sample Code: Unit 1

UNIT 1: Journey from Statistics to Machine Learning

UNIT 3:  kNN

                        kNN Code

                    Filtering mobile phone spam with the naive Bayes algorithm

Unit 4:  Regression, Neural Networks & Support Vector Machines and Finding Patterns

        Code for Predicting medical expenses using linear regression

        Code for Estimating quality of wine

        Code for Modeling the strength of concrete with ANNs

        

Unit 5:  Evaluating Model Performance

 

Elective V: BIG DATA & CLOUD COMPUTING

 SEMESTER :  III                                                              HOURS/WEEK   : 4

CODE :  P20CA3:4                                                                   CREDITS    : 3

Elective V: BIG DATA & CLOUD COMPUTING

 

• Syllabus: Syllabus

MCQs: MCQs - Big Data

• Unit 1: Introduction to Big Data

• Unit 2: 

• Unit 3: Introduction To MAP REDUCE Programming

• Unit 4

• Unit 5

PROGRAMMING IN PYTHON

 SEMESTER :  III                                                              HOURS/WEEK   : 4

CODE :  P22CA309                                                                   CREDITS    : 3

 

Core IX: PROGRAMMING IN PYTHON

            Syllabus: Syllabus

•  Unit 1: Introduction to Python, Data types and Statements
• PPT
  
• Code: Control Statement, String

•  Unit 2: Sequence Code:  List, Tuple & Dictionaries

•  Unit 3: Functions, Classes & Objects

•  Unit 3: OOPs and Databases

•  Unit 4: NUMPY, PANDAS and MATPLOTLIB

•  Unit 5: DJANJO

Artificial Intelligence

  ARTIFICIAL INTELLIGENCE

 Elective II: P20CA2:3

P24CA308 Core VIII: SMART DEVICES PROGRAMMING

 SEMESTER :  III                                                           HOURS/WEEK   : 4

CODE :  P24CA308                                                         CREDITS    : 3

 

Core VIII: SMART DEVICES PROGRAMMING

 

Dr. A. Florence Deepa

Associate Professor, Department of Computer Applications,

Bishop Heber College, Trichy

Syllabus: Syllabus

• UNIT 1: Android Programming - Introduction
• PPT
  

• UNIT 2: Layouts
• PPT
  

• UNIT 3: JAVA Basics and Android
• PPT
• UNIT IV - Animations and Interpolations

• UNIT V – SQLite Database and Flutter 

• 60 - Data Persistence and Sharing
• 48 - Localization

49	Firebase Database
60	Data Persistence
58	Spinner Widget
35	Drawing Graphics
30
12	Handling Screen Touches
48	Localization

• UNIT IV - Animations and Interpolations 

REG #	TOPIC TITLE
27	Fragment Lifecycle
29	Supporting different versions of android
32	Animations in Android
13	Designing cool animations in XML
42	Instantiating animations and controlling them with Java code
52	More animation features
56	Introducing SeekBar
38	Animation demo app
16	Getting started drawing with Bitmap, Canvas, and ImageView
19	Using the Canvas class
23	Canvas demo app
28	The Android coordinate system
22	Creating & Manipulating bitmaps
59	The Matrix class
20	Bitmap manipulation demo app
4	Creating the Live Drawing project
33	Implementing the game loop with a thread
45	Particle Systems
6	Spawning particle systems in the LiveDrawingView class
53	Handling touches
36	The Android Studio Profiler tool
54	The SoundPool class
47	Sound demo app introducing the Spinner widget

• UNIT V – SQLite Database and Flutter 

REG #	TOPIC TITLE
55	Introducing the model-view-controller pattern
37	Device detection mini-app
18	Configuration qualifiers
2	Fragments Life Cycle
8	Managing Fragments with FragmentManager
21	Building an image gallery
9	Coding the PagerAdapter class
10	Coding the MainActivity class
31	Introducing NavigationView
46	Examining the Simple Database app - Create Insert
11	Examining the Simple Database app - Update Delete
3	Exploring the autogenerated code and assets
50	Using the Fragment classes and their layouts
40	Make SMS and Phone call services.

51	Android SQLite API - Introduction
34	SQLiteOpenHelper and SQLiteDatabase
39	Building and executing queries
43	Database cursors
24	Coding the database class
14	Coding the Fragment classes to use the DataManager class
17	Running the Age Database app
41	Flutter – Introduction
57	Flutter – Installation
5	Flutter – Creating Simple Application in Android Studio.
15	Firebase Database - Introduction
7	Firebase Database - Installation
44	Perform CRUD operations with Firebase Database -  Update Delete & Display
25	Perform CRUD operations with Firebase Database - Create Insert & Display
1	Create an application with login and homepage.

Elective V: BLOCK CHAIN AND CRYPTO-CURRENCIES

 SEMESTER :  III                                        HOURS/WEEK   : 4

CODE :  P20CA3:5                                     CREDITS    : 3

Elective V: BLOCKCHAIN AND CRYPTO-CURRENCIES

Multiple Choice Questions

 

Blockchain MCQs 

Study Materials 

•  UNIT I: 
•  Part 1 

• Part 2 

• UNIT II:  Unit 2

• UNIT III: Unit 3

• UNIT IV: 
• ICO 
• Unit 4  

• UNIT V:
• Part 1 
• Part 2