Modules

Program Modules

The WISE program will have set of five lecture and three project Modules which will be spread across the academic cycle of five semesters and three summer breaks. Each lecture and project modules will be of 30 and 50 hours duration respectively.

1. First Steps:

1.1 Introduction
1.2 Datatypes
1.3 First Program
1.4 Writing Python Code

2. Decision Making

2.1 Conditional Statements
2.2 Simple If
2.3 If…else
2.4 Nested if
2.5 compound conditions
2.6 if…elif…else

3. Functions and Strings

3.1 Functions:

3.1.1 Defining a Function
3.1.2 Calling a Function
3.1.3 Returning Multiple Values

3.2 Strings:

3.2.1 String Operations
3.2.2 Accessing characters in String
3.2.3 Slicing the String
3.2.4 String Methods

4. Lists and Dictionaries

4.1 Lists:

4.1.1 Accessing an element
4.1.2 Slicing and striding
4.1.3 List Methods

4.2 Dictionaries:

4.2.1 Creating Dictionaries
4.2.2 Adding items
4.2.3 Accessing Values
4.2.4 Modifying Dictionaries
4.2.5 Deleting Items

5. File Handling:

5.1 File I/O:

5.1.1 Crate or Open the file
5.1.2 Methods of File Objects
5.1.3 Reading Data from File
5.1.4 Writing to File

1. Getting Started

1.1 Sum Of Digits
1.2 Next Multiple of 100
1.3 Three Digit Palindrome
1.4 Cube Of Number

2. Generating Sequences

2.1 Natural Numbers
2.2 Fibonacci Series
2.3 Russian Multiplication
2.4 Collatz Sequence

3. Comparing and Organising

3.1 Maximum of 3 Numbers
3.2 Three Boolean
3.3 Alarm Clock
3.4 Round Sum

4. Patterns and Strings

4.1 Star Pyramid 01
4.2 Star Pyramid 02
4.3 Four Per Line

5. Modularizing Programs

5.1 Odd Palindromes
5.2 Armstrong Numbers
5.3 Twin Primes
5.4 Type Of Number

6. Manipulating Strings

6.1 Date Format
6.2 Lucky Number
6.3 Mask Email ID

1. Creating Static Web Pages

1.1 Designing Layout
1.2 Registration Form

2. Creating Interactive Web Pages

2.1 Color Paragraphs
2.2 Form Validations
2.3 Image Slider
2.4 Add Row To Table
2.5 Sort Table Data
2.6 Tic Tac Toe

3. Getting Started With Bootstrap

3.1 Design a Responsive Web Page
3.2 Design Hello World Web Page

4. Rich User Interface

4.1 Design a Responsive Web Page

5. Widgets

5.1 Design a Responsive Web Page

6. Developing Servlets

6.1 Introduction to Servlets
6.2 Developing Web Apps using Servlets
6.3 Session Management
6.4 Servlet Context and Config
6.5 Servlet Filters
6.6 Debugging Exercise

7. Developing JSPs

7.1 Introduction to JSP
7.2 Developing JSP Pages
7.3 Custom Tags
7.4 JSTL

8. Working With JDBC and MVC

8.1 Introduction To MVC Architecture
8.2 Integrating Web Applications With Databases

1. Data Binding

1.1 Sign Up Process
1.2 Sign Up Process with Data Submission Confirmation
1.3 Sign Up Process with Data Saved in Database
1.4 Sign In Process

2. Form Validation

2.1 Sign Up Form Input Validation
2.2 Sign In Form Input Validation

3. Filters

3.1 Filter Data Dynamically based on Criteria
3.2 Filter Data Dynamically based on User Input

4. Routing

4.1 Single Page Application with Multiple Views
4.2 Single Page Application with Multiple Local Views

5. Components

5.1 Components
5.2 Modularizing Application

1. Welcome to machine Learning

1.1 Welcome to Machine Learning
1.2 Prerequisites
1.3 Types of Machine Learning
1.4 Why Machine Learning is Future
1.5 Applications of Machine learning

2. Data Preprocessing

2.1 Importing Libraries
2.2 Import Datasets
2.3 Missing Data
2.4 Categorical Data
2.5 Training set and Test set
2.6 Feature Scaling
2.7 Data Preprocessing Template

3. Simple Linear Regression

3.1 Regression
3.2 Simple Linear Regression
3.3 Multiple Linear Regression
3.4 Polynomial Regression
3.5 Decission Tree Regression
3.6 Random forest Regression

4. Polynomial Linear Regression

5. Decision Tree Regression

6. Logistic Regression

6.1 Logistic Regression
6.2 K-Nearest Neighbors (K-nn)
6.3 Naive Bayes
6.4 Decission Tree Classification
6.5 Random forest Classification

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