Sample Input: The user is prompted to enter details for four training sessions: 1. Enter details of Session 1: Session ID: TECH101 Session Title: Intro to cloud Computing Total Duration (hours): 3.5 Current participant: 25 。 Available seats: 10 2. Enter details of Session 2: 。 Session ID: TECH102 Session Title: Advanced Python Programming Total Duration (hours): 4.0 Current participant: 25 Available seats: 5 3. Enter details of Session 3: Session ID: TECH103 Session Title: Data Science Fundamentals о Total Duration (hours): 5 Current participant: 28 Available seats: 2 4. Enter details of Session 4: Session ID: TECH104 Session Title: Machine Learning Basics Total Duration (hours): 2.5 Current participant: 12 о Available seats: 18 Sample Output: Message Training Session Report Total number of sessions: 4 Total number of participants: 85 Average number of participants per session: 21.25 Details of all sessions: Session Code: TECH101 | Title: Introduction to Cloud Computing | Duration: 3.5 hours | Participants: 20 | Available Spots: 10 Session Code: TECH 102 | Title: Advanced Python Programming | Duration: 4.0 hours | Participants: 25 | Available Spots: 5 Session Code: TECH 103 | Title: Data Science Fundamentals | Duration: 5.0 hours | Participants: 28 | Available Spots: 2 Session Code: TECH104 | Title: Machine Learning Basics | Duration: 2.5 hours | Participants: 12 | Available Spots: 18 OK

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Please answer the scenario of the JAVA OOP Programming Assignment 1 below:

Scenario: 
You have been hired by TechCo to create and manage their employee training portal. Your first 
task is to develop a program that will create and track different training sessions in the portal. 
Each training session has the following properties: 
• A session ID (e.g., "TECH101", "TECH205") 
• A session title (e.g., "Machine learning", "Advanced Java Programming") 
• A total duration in hours (e.g., 5.0, 8.0) 
• Current number of participants (e.g., 25) 
Each session must have at least a session ID and a total duration and must met the following 
requirements: 
• The maximum participant for each session is 30. 
• The total duration of a session must not exceed 10 hours. 
• The current number of participants should never exceed the maximum number of 
participants. 
Design an object-oriented solution to create a data definition class(DDC) and an 
implementation class for the session object.  
In the DDC, a session class must include: 
• Constructors to initialize session details. 
• Accessors and Mutators with proper validation. 
• A method to calculate remaining seats (maximum participant - current participant). 
• A toString method 
With a completed data definition class, your implementation class must instantiate four 
training sessions, gathering session details from the user inputs. Once all sessions are created, 
the program should generate a well-formatted report, displaying: 
o Total number of sessions. 
o Total number of enrolled employees. 
o Average participant per session. 
o Details of each session

 

Other Requirements: 
• Your solution must use object-oriented techniques (No points earned for a procedural 
solution). You must keep Data definition class and Implementation class separate. 
• Your solution must be designed as a modular solution using methods other than main, with 
each method performing one task. The main method should contain only a very minimal 
amount of code, calling methods instead. 
• Your solution must not use any regular expressions for validation or String Builder Class. 
• Your solution must not use any arrays or arrayList.  
• Your solution must include appropriate constants, constructors, accessors, mutators, and special 
purpose methods (including a toString() method), as necessary in support of the problem. 
• Your solution may not use any functions or language constructs not covered during IT 106 or this 
semester’s IT 206 without prior authorization from your instructor, even if you know other 
functions or language constructs. We want everyone to be on the same "playing field", 
regardless of previous programming exposure, and get practice with algorithmic design to solve 
problems (the intent of the session). Using something existing not discussed in class does not 
give you as much practice as solving the problem yourself. Doing this may lead to a substantial 
grade penalty, a grade of zero, or an Honor Code inquiry. When in doubt, ask! 

Hints: 
• You do NOT need to use arrays to solve this problem. Keep in mind once you have finished 
entering the information for one group, it is not necessary to keep the information. 
• Think about any special purpose methods that might be needed in the data definition class. 
Special purpose methods are important when using values in instance variables to perform a 
specific process. 

Requirements: 
1) List and describe the purpose of each class that will be needed to solve this problem 
a. You must separately identify (list) and describe the purpose of each class. One or two 
sentences per class should be sufficient. 
2) Data Definition Class(es) - Create a detailed UML Class Diagram, listing and explaining all class 
variables, accessors, mutators, special purpose methods, and constructors associated to each 
data definition class. 
3) Write a well-documented, efficient Java program that implements the solution design you 
identified in 1 to 3 above. Include appropriate documentation as identified in the 
documentation expectations document.

Sample Input:
The user is prompted to enter details for four training sessions:
1. Enter details of Session 1:
Session ID: TECH101
Session Title: Intro to cloud Computing
Total Duration (hours): 3.5
Current participant: 25
。
Available seats: 10
2. Enter details of Session 2:
。
Session ID: TECH102
Session Title: Advanced Python Programming
Total Duration (hours): 4.0
Current participant: 25
Available seats: 5
3. Enter details of Session 3:
Session ID: TECH103
Session Title: Data Science Fundamentals
о Total Duration (hours): 5
Current participant: 28
Available seats: 2
4. Enter details of Session 4:
Session ID: TECH104
Session Title: Machine Learning Basics
Total Duration (hours): 2.5
Current participant: 12
о Available seats: 18
Transcribed Image Text:Sample Input: The user is prompted to enter details for four training sessions: 1. Enter details of Session 1: Session ID: TECH101 Session Title: Intro to cloud Computing Total Duration (hours): 3.5 Current participant: 25 。 Available seats: 10 2. Enter details of Session 2: 。 Session ID: TECH102 Session Title: Advanced Python Programming Total Duration (hours): 4.0 Current participant: 25 Available seats: 5 3. Enter details of Session 3: Session ID: TECH103 Session Title: Data Science Fundamentals о Total Duration (hours): 5 Current participant: 28 Available seats: 2 4. Enter details of Session 4: Session ID: TECH104 Session Title: Machine Learning Basics Total Duration (hours): 2.5 Current participant: 12 о Available seats: 18
Sample Output:
Message
Training Session Report
Total number of sessions: 4
Total number of participants: 85
Average number of participants per session: 21.25
Details of all sessions:
Session Code: TECH101 | Title: Introduction to Cloud Computing | Duration: 3.5 hours | Participants: 20 | Available Spots: 10
Session Code: TECH 102 | Title: Advanced Python Programming | Duration: 4.0 hours | Participants: 25 | Available Spots: 5
Session Code: TECH 103 | Title: Data Science Fundamentals | Duration: 5.0 hours | Participants: 28 | Available Spots: 2
Session Code: TECH104 | Title: Machine Learning Basics | Duration: 2.5 hours | Participants: 12 | Available Spots: 18
OK
Transcribed Image Text:Sample Output: Message Training Session Report Total number of sessions: 4 Total number of participants: 85 Average number of participants per session: 21.25 Details of all sessions: Session Code: TECH101 | Title: Introduction to Cloud Computing | Duration: 3.5 hours | Participants: 20 | Available Spots: 10 Session Code: TECH 102 | Title: Advanced Python Programming | Duration: 4.0 hours | Participants: 25 | Available Spots: 5 Session Code: TECH 103 | Title: Data Science Fundamentals | Duration: 5.0 hours | Participants: 28 | Available Spots: 2 Session Code: TECH104 | Title: Machine Learning Basics | Duration: 2.5 hours | Participants: 12 | Available Spots: 18 OK
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