Full document for AI powered resume Analyzer

Career Guidance App for Students AI powered

1. CARRER GUIDANCE APP FOR STUDENTS -AI ASSISTED

2. OBJECTIVE To empower users in their career by offering personalized insights and recommendations. To provide guidance to users based on their individual skills, experiences, and career goals. By analyzing user profiles and job market trends, the application matches users with relevant job opportunities and offers suggestions for skill development and career advancement. To take control of their career journeys by providing them with personalized insights and offering comprehensive resources for continuous learning and development. Through these efforts, we strive to help users achieve success and fulfilment in their professional endeavours.

3. SCOPE The scope of the career guidance app encompasses a comprehensive suite of features and functionalities designed to support individuals at every stage of their career journey. From user registration and resume analysis to personalized job matching and skill development recommendations, the app aims to provide a seamless and intuitive platform for users to navigate their career paths effectively. The career guidance app is designed to offer a wide range of services to meet the diverse needs of users across various industries and career stages. In addition to facilitating user registration and resume analysis, the app provides personalized job matching based on individual skills, experiences, and preferences.

4. ABSTRACT The rapid evolution of technology and the changing dynamics of the job market demand innovative solutions for career planning and guidance. The app employs artificial intelligence (AI) algorithms to empower students with personalized career insights, skill development strategies, and practical tools to enhance their employability. The app helps users by analyzing job market trends and employer preferences through AI-driven insights, it provides suggestions for optimizing resumes and with the advancement in AI/ML technologies, we can leverage data-driven systems to provide personalized job recommendations based on user preferences. Offering personalized learning paths, the app recommends courses, and certifications aligned with students' career goals.

5. EXISTING VS PROPOSED METHOD EXISTING SYSTEM As per the job issue faced nowadays, many job recommending platform grown up with help of new technologies, Where students and job seeking persons upload their resume to get the area of working to be sorted. The existing platforms is only giving the recommendation of jobs which is barely matching the resumes and the skill set what the people post. This is much satisfied in case of just knowing the opening and job offers in the sector or in the companies. PROPOSED SYSTEM According to the improving phase of skills in all the job sectors, people used to know only about the existing skills which are barely know by many of their competitors. So as of now growing jobless situation people need to know the extra qualification that can secure them a sure spot in the job consideration by the companies. Where as involving the AI technology which will show the job offers as well as the further more opportunities with extra phase of learning.

6. LITERATURE SURVEY S.NO TITLE AUTHOR METHODOLOGY ADVANTAGE DISADVANTAGE 1. Machine Learning and Explainable AI in Educational Data Mining for Career Counseling Pratiyush Guleria and Manu Sood Year-2020 Artificial Intelligence and Data Analysis ML Framework for automatic assessment Artificial Neural Networks 1.Recommends suitable course curriculums based on student capabilities 2.Acts as an advisor for parents and students in course selection 3. Enhances accuracy and efficiency in career counseling. Complexity in extending models using unsupervised and data mining frameworks.

7. S.NO TITLE AUTHOR METHODOLOGY ADVANTAGE DISADVANTAGE 2. AI-Powered Academic Guidance and Counseling System Based on Student Profile and Interests" Hajar Majjate,Adil Jeghal , Et al. Year-2023 1.Data Mining 2.Machine learning algorithms like Decision Trees, Random Forests, and Support Vector Machines. 1. High predictive accuracy based on past student data. 2. Empowerment of students by providing insights into academic opportunities at different universities. Risk of algorithmic bias affecting recommendations and predictions.

8. S.NO TITLE AUTHOR METHODOLOGY ADVANTAGE DISADVANTAGE 3. Artificial Intelligence in Career Counseling: A Test Case Study with ResumeAI . Muhammad Rahman Et al. Year-2023 1.Utilization of OpenAI API text-davinci-003 for chatbot development 2. Incorporation of prompt-based guidance for users 3. Comparison of AI recommendations with human counselors' suggestions . 1.Increased accessibility with 24/7 availability. 2. Personalized feedback tailored to individual needs. 3. Efficient resume editing process. Ethical concerns regarding data privacy and bias.

9. S.NO TITLE AUTHOR METHODOLOGY ADVANTAGE DISADVANTAGE 4. AI-Based Career Guidance System for Efficient Career Path Selection Firdosh Sayyed , Ronak Sanghani , Abhishek Vora , Nikita Lemos Year-2020 Artificial Neural Network(ANN) 1.Efficient guidance through AI analysis of student parameters 2.Accessible on various devices for convenience 3.Personalized recommendations based on individual traits Reliance on technology may limit accessibility

10. S.NO TITLE AUTHOR METHODOLOGY ADVANTAGE DISADVANTAGE 5. Opportunities and Risks of AI in Career Development Practice Marianne Wilson, Et al. Year – 2020 1.AI mapping skills from job adverts to categories . 2.Development of AI tools like CiCi chatbot for personalized career information Cost savings 2. Elimination of human error 3. Reduction of unconscious bias in recruitment processes Potential for algorithmic bias 2. Lack of transparency in decision-making

11. Hardware & Software Requirements Hardware : PC/Laptop Specifications (Minimum Requirements ): Processor : Intel i5 Architecture : x64 bit RAM : 4 Gigabyte Storage : 128 Gigabyte SSD

12. Software Requirements Operating System: Windows 10 Coding Language: Python Front-End: StreamLit , Python Back-End: MySql Database: XAMPP, PHP IDE: VS Code, Anaconda

13. Functional Flow of Proposed System The Registration facilitates user authentication and account creation and the Upload Resume allows users to submit resumes, which are then parsed for relevant information. The Pattern Matching module compares resume content with job descriptions using algorithms like cosine similarity and finally in Recommendation module provides personalized suggestions, recommending either courses for skill development or job opportunities based on user profiles

14. MODULES Module is the process of defining how the information system should be built (i.e., physical system design),ensuring that the information system meet quality standard (i.e., quality assurance). The following are the modules identified for our system. REGISTRATION USER DETAILS PATTERN MATCHING RECOMMENDATION

15. REGISTRATION The first module of the Career Guidance web application is the Registration Module, which facilitates the process of user account creation. This module allows individuals to sign up for the platform by providing basic information such as a username and password. This module allows users to register for an account on the web application. It typically includes a form where users can input their basic information such as username and password. Upon successful registration, user data is stored and the user is granted access to the other features of the application. No specific algorithm is used in this module. It mainly involves database operations for user registration, such as checking if the username already exists and adding the new user if it doesn't.

16. USER DETAILS The User Details module is responsible for managing and updating user profile information. It provides functionality for users to upload their Resume and Job description. The `docx2txt` library is used to extract text content from uploaded resume files. The ‘docx2txt’ library in the Career Guidance app employs specialized algorithms to accurately extract text content from Microsoft Word resume files. These algorithms interpret the document's structure and formatting, analyzing elements like paragraphs and headings while discarding irrelevant details. Additionally, the library handles various document elements such as tables and images, ensuring only relevant text is extracted and ability to process resume uploads seamlessly and provide users with valuable insights and recommendations based on extracted textual information.

17. PATTERN MATCHING Pattern Matching for career guidance involves identifying relevant attributes from student profiles such as academic achievements, skills, and extracurricular activities. These features can be quantified and organized to capture essential information, facilitating effective analysis and personalized career recommendations using machine learning algorithms. Cosine similarity algorithm is an collaborative filtering algorithm used to calculate the similarity between the text content of the uploaded resume and job descriptions. This algorithm measures the cosine of the angle between two vectors of text data, providing a similarity score .

18. RECOMMENDATION In the Recommendation phase of career guidance, a AIML model can be trained to categorize student profiles into distinct career paths based on their extracted features. The model's output would provide personalized recommendations or suggestions, and guiding the students towards suitable career options aligned with their academic achievements, skills, and interests. In the Career Guidance app, collaborative filtering algorithm can be employed to provide personalized recommendations for job opportunities or skill development courses based on user preferences and past interactions. Collaborative filtering analyzes user behavior and preferences, as well as similarities with other users, to make relevant recommendations.

19. Registration and Login

20. Login and Upload Documents

21. Similarity Score and Job or Course Recommendation

22. Course Recommendation

23. Conclusion and Future Enhancement Giving students and job seeking people the recommendation according to their resume with few more job opportunities that may correlate with their skill set. Showing them few more skill which can be developed that may help them to back confirmation in the job rush . W e can create a powerful system that provides accurate and tailored job recommendations. W ith the increasing demand for personalized experiences, job recommendation systems are becoming essential tools in the job search process. By understanding the project structure and implementation details, we can harness the potential of AI technologies to empower job seekers and connect them with their dream opportunities . Utilization of advanced machine learning algorithms for enhanced personalization. Expansion of job matching criteria to include factors like location and company culture.

24. References Dahanke Ajay, Et.al. (2022). ‘An Intelligent Career Guidance System Using Machine Learning’, journal on IRJMETS, Vol. 04, Issue. 03, pp. 2582-5208. Firdosh sayyed , Et.al. (2020). ‘AI-Based Career Guidance System for Efficient Career Path Selection’, journal of Engineering and Technology, Vol. 07, Issue. 05. Hajar Majjate & Adil Jeghal . (2023). ‘AI-Powered Academic - Guidance and Counseling System Based on Student Profile and Interests, journal on MDPI, Vol. 07, Issue. 06. Manali surve , Vaishnavi Lalge & Pranali . (2023). ‘Android Application for Student Career Choices, journal on IRJMETS, Vol. 05, Issue. 02. Marianne Wilson, Et.al. (2020). ‘Opportunities and Risks of AI in Career Development Practice’, journal on jnicec , Issue. 48.

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