CODE IN PYTHON.

note: --> Please explain the code and your approach

--> Analyse the big-O complexity by measuring the complexity step by step and clearly show how you did it

--> explain the complexity of the code critically

--> don't use built-in python functions from libraries

(All of the things mentioned above are the part of this question)

I need the solutions as soon as possible :(

Overview In this assignment, you are tasked to implement a smart applicants search program that can be used by the potential recruiters to find suitable applicants from the field of Computing & IT. The program will facilitate recruiters to filter, sort and save profiles by considering various factors such as area of specialization, country of the highest qualification, years of experience, expected salary, and qualification level. Assume that you have a dataset of the profiles extracted from a job search site. A sample of the profiles data is given below: profiles = [['Rose Winds', 'Cloud Computing', 'USA', 6.5, 5000, 5, 'F'], ['Merry Brown', 'Cloud Computing', 'UK', 5, 7000, 5, 'F'], ['Lina Mesro', 'Cyber Security', 'Malaysia', 7, 6500, 4, 'F'], ['Abdul Fazil', 'Big Data', 'Australia', 11, 8000, 4, 'M'], ['Chris Janes', 'Big Data', 'Ireland', 7, 2500, 4, 'M'], ["Sireen May', 'Artificial Intelligence', 'Australia', 0, 4000, 4, 'F'), ['Jine Tims', 'Robotics', 'Australia', 0, 3500, 3, 'M'], ['Niki Rohdes', 'Artificial Intelligence', 'China', 9, 8500, 5, 'F']] In the dataset above, 'Rose Winds' is the applicant name, 'Cloud Computing' is the area of specialization, 'USA' is the country of the highest qualification, 6.5 is the years of experience, 5000 is the expected monthly salary, 5 is the level of qualification, and 'F' is the gender, i.e. Female. 'M' refers to the male gender. Levels of qualification: 5 = PhD, 4 = Master, 3 = Bachelor degree (Highest to Lowest) Note: your functions and algorithms must be generic and not dependent on the specific data. For example, your program must be able to perform all the tasks when provided new data. Task 4: Cost Estimation (25 marks) Assume that an employer wants to recruit two applicants who are specialized in Cloud Computing. However, the employer has budget constraints. Therefore, they are searching for two applicants with the lowest expected salary. You are required to create and implement an algorithm as a python program which can traverse all the profiles and displays the two most inexpensive applicant profiles who are specialized in Cloud Computing along with the total annual cost that will be allocated on them. Your program should be based on a general algorithm; in other words, it must work with new inputs, i.e. new applicant profiles. For example: Using the profiles dataset as stated on Page 2, your program will produce the following results because currently, those are only two applicants with Cloud Computing specialization. However, if a new profile is added with low expected salary, the result must change accordingly. Matching Profiles = [['Rose Winds', 'Cloud Computing', 'USA', 6.5, 5000, 5, 'F'], ['Merry Brown', 'Cloud Computing', 'UK', 5, 7000, 5, 'F']] Total Annual Cost = 144,000 Marks allocation: 1. Correctness, completeness, quality of the code, effectiveness and results of the search, calculation of the annual cost, accepting new inputs. (10 marks) 2. Discuss and justify your implementation technique/approach. (2 marks) 3. Analyse the Big-O complexity of your algorithm by measuring the complexity step-by- step in your program code. (10 marks) 4. Critically discuss the complexity of your algorithm, especially focusing on the growth rate with respect to the input size and efficiency of your algorithm. (3 marks) Note: Use of built-in functions from python libraries to implement this algorithm is not permitted, and it will not contribute to marks. The theoretical discussion should be included in your python module as docstring or comments