project ppt.pptx pptpptpptpptpptpptpptpptppt
- 1. STUDENT CAREER GUIDANCE FOR RECOMMENDATION OF RELEVANT COURSE SELECTION
- 2. CONTENTS Abstract Introduction Literature survey Existing System and Disadvantages Proposed System and Advantages System Requirements System Design Testing Further Enhancement Conclusion
- 3. ABSTRACT There is a trend amongst students to generally opt for career paths based on either the choices of their colleagues or the highest salary paying roles. They fail to know their strengths and choose their career randomly which leads to frustration and demoralization. Thus, there is a need for a system that helps students decide a job role that is best suited for him/her which is based on his/her skillset and other evaluation metrics which is now possible due to advancements in the field of deep learning. This project proposes an automated system using Artificial Neural Network which considers personality traits of the individual along with personal interests and academics to predict which computer science job role would be best suited for them.
- 4. INTRODUCTION Artificial Neural Networks is a data processing system consisting of a large number of simple, highly interconnected processing elements . For career recommendation various parameters are considered which becomes quite difficult to predict using traditional regression models. Any student after graduation needs to decide which job role is best suited for him according to his profile. This is important for a long-term career plan. Similarly, for a recruiter it is very crucial to recruit a candidate after assessing him/her in all different aspects. A career recommender system will help undergraduate students and recruiters in finding the right job based on their personality, academics, interests, etc.
- 5. we propose a career recommendation system using neural networks due to the high number of parameters for classification. These parameters include student performance in various subjects present in the undergraduate curriculum of computer science as well as student interests, interpersonal skills, talents, etc.. This project aims to implement the concept using an Artificial Neural Network (ANN) model. The model is trained and tested on 15,000 and 3,000 dataset entries respectively. The model performs multiclass classification and is able to predict one of the 6 domains (i.e. Database Administrator, Project Manager, Software Developer, Business Intelligence Analyst, Security Administrator, Technical Support). INTRODUCTION
- 6. LITERATURE SURVEY Introduction to artificial neural networks: Author: R. E. Uhrig A neural network is a data processing system consisting of a large of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain . Predicting Students Performance in Educational Data Mining: Authors: Guo, Bo & Zhang, Rui & Xu, Guang & Shi Student’s future career and goal can be choosen by using data analysis of python. Prediction modelling in career management: Authors:H. Mallafi and D. H. Widyantoro It is easy to choose their Carrer Goal in a Simple way By predicting past data.
- 7. EXISTING SYSTEM As students are going through their academics and pursuing their interested courses, it is very important for them to assess their capabilities and identify their interests so that they will get to know in which career area their interests and capabilities are going to put them in. This will help them in improving their performance and motivating their interests so that they will be directed towards their targeted career and get settled in that. Also recruiters while recruiting the candidates after assessing them in all different aspects, these kind of career recommender systems help them in deciding in which job role the candidate should be kept in based on his/her performance and other evaluations. This project mainly concentrates on the career area prediction of computer science domain candidates.
- 8. DISADVANTAGES OF EXISTING SYSTEM A person may get a job but they may not get the job according to their interests. The person just can predict the type of role they may get with the knowledge they are having but they cannot get a job suggestion that they are interested in.
- 9. PROPOSED SYSTEM In the proposed system we added the fields like prediction data and job search in which prediction data take the data related to the person and predict the type of job we get according to their skills ,knowledge and skills (i.e... Academic percentage in Operating Systems, Percentage in Algorithms, Percentage in Programming Concepts, Percentage in Software Engineering, Working Hours per Day, can work long time before system, Self-learning capability? Etc..) The person can search the job of their interest from the existing job roles based on the role they are interested, available in the job search field we provided.
- 10. ADVANTAGES OF PROPOSED SYSTEM Can Choose The Destination Easily. We Can proceed With out any proper Guidance. Discards Confusion. Support and Motivation. Determining the Strengths and weakness. Set objective for greater results.
- 11. SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS: System : Intel core i3(minimum). Hard Disk : 1 TB. Monitor : 14’ Color Monitor. Mouse : Optical Mouse. Ram : 8 GB.
- 12. SYSTEM REQUIREMENTS SOFTWARE REQUIREMENTS: Operating system : Windows 10 Ultimate. Coding Language : Python. Front-End : Python console, Jupyter notebook, HTML. Data-Base : SQLite
- 13. SYSTEM ARCHITECTURE Prediction data Prediction skills Job search User data Preproces s Model Predictio n results Job portal Output result Online portals
- 14. DATA FLOW DIAGRAM User Skills Prediction skills Prediction data Career data Skill set input Job search Online jobs portals Preproces s Data Visualizatio n Data cleaning Data Scaling Model deployme nt Model Fitting Saved model Predictions result User input
- 16. CLASS DIAGRAM Users +String: Username +String: Password +accessing() +enter details() Database1 +String: username +String: password +put() +get() System +load dataset() +preprocess() +split() +trainalgorithm() +Predict()
- 17. SEQUENCE DIAGRAM User System 1.User will give the data in Prediction data 2:It will give the suitable results 3:User will give the data in prediction skills 4.It will give one skilled base job 5:User will go for job search 6:User will get the suggestions Uses random forest algorithm Uses random forest algorithm
- 18. ACTIVITY DIAGRAM Home page Prediction data Prediction skills Job search Will give the suitable jobs to him Skilled based job Gives an idea
- 19. MODULES Modules used in the Career Recommendation are Data Analysis Data Preprocessing Machine Learning Algorithm for Prediction
- 20. Data Analysis: How the data will be according to the condition. Data Preprocessing: It means replacing the Null data with the mean , median and mode values. Machine learning algorithms for prediction: For predicting the output we used the classification algorithms.
- 21. Test Cases S.no Test Case Excepted Result Result Remarks (IF Fails) 1. Prediction Data In prediction Data after giving the information of User then it should give the Suitable information Pass If it not giving the appropriate information then it will fail. 2. Prediction Skills In prediction skills if the User has given any one skill, then it should give most suitable skill job. Pass If it is not giving the skill job then it fails. 3. Code chef link (in Job Search) If the User has selected code chef link, then it should go to that link Pass If it is not going to it then it fails.
- 22. S.no. Test case Expected Results Result Remarks (IF Fails) 4. Hackerrank Link (In Job Search) If the User has selected Hackerank link, then it should go to that Link. Pass If it is not going to it then it fails. 5. Geeks for Geeks Link (In job Search) If the user has selected Geeks for Geeks Link, then it should go to that Link. Pass If it is not going ti it then it fails. Test Cases
- 23. FURTHER ENHANCEMENT Sub-Domains - The model can be further scaled to recognize the specialization within that particular domain. For instance, if the suggested role is in the domain of Security, there can be various sub domains within it like System Security Administrator, network Engineer, Network Administrator, Information Security Analyst, etc.
- 24. CONCLUSION This project proposes an efficient ANN model for predicting a well-suited job- role for the Computer Engineering student. The developed model is apt for the analysis of many objective factors for a person with qualified knowledge, and skills. This recommender system can be used by any IT based recruiter to hire a candidate appropriate for the job. Additionally, an individual as a Computer Engineering fresher can find out the domain that they are qualified for based on their profile and the ones who are unaware of their career. The proposed model used 15 parameters to predict one of the six job-roles with an accuracy of 94.9%. Hence, ANN model gives more accurate results to traditional machine learning models.
- 25. REFERENCES 1. R. E. Uhrig, "Introduction to artificial neural networks," Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics, Orlando, FL, USA, 1995, pp. 33-37 vol.1. 2. S. Elayidom, S. M. Idikkula, J. Alexander and A. Ojha, "Applying Data Mining Techniques for Placement Chance Prediction," 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, Trivandrum, Kerala, 2009, pp. 669-671. 3. H. Mallafi and D. H. Widyantoro, "Prediction modelling in career management," 2016 International Conference on Computational Intelligence and Cybernetics, Makassar, 2016, pp. 17-21
- 26. Any Queries