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Get runnable AI Career Analysis and Job Matching Final Year Project Source Code with database files, project setup instructions, live demo options and installation support. This project resource helps students understand the implementation, modules, workflow and technical architecture of a complete MACHINE-LEARNING project.
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01 Source Code Only
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AI-Based Career Profile Analysis, Skill Gap Prediction and Job Matching is a full-stack Django web application designed to help students and job seekers analyze their professional profiles, identify missing skills, discover suitable career roles, and find relevant jobs through Artificial Intelligence and Machine Learning.
Users can build detailed career profiles, add skills, education, projects, and certifications, upload PDF resumes, automatically detect skills from resumes, run OpenAI-powered profile analysis, generate skill gap reports for target job roles, receive career suggestions, search jobs, view BERT/OpenAI/combined job match scores, apply for jobs, save jobs, and review previous analysis results.
The system uses a hybrid AI/ML pipeline combining BERT dual-encoder embeddings, OpenAI embeddings, cosine similarity, skill overlap, BM25 sparse retrieval, FAISS dense retrieval, NLP normalization, resume skill extraction, and optional contrastive learning. This allows the platform to compare a user's profile against career roles and job requirements using multiple matching techniques rather than simple keyword matching.
The application also includes a dedicated Career AI Admin Panel where staff can manage users, companies, job categories, skills, career roles, jobs, applications, AI pipeline logs, reports, OpenAI settings, ML weights, retrieval settings, and system configuration.
This project is suitable for B.Tech, M.Tech, BCA, MCA, BE, ME, BSc, MSc, Data Science, AI, and Machine Learning students who need a practical final year project, major project, or minor project based on Artificial Intelligence, career recommendation, skill gap prediction, resume analysis, job recommendation, BERT, OpenAI API, NLP, information retrieval, and Django development.
| Password | Role | Notes | |
|---|---|---|---|
[email protected] |
admin123 |
Staff / Superuser | Admin panel |
[email protected] |
demo123 |
User | Main AI career demo |
[email protected] |
demo123 |
User | Data/Analytics profile |
[email protected] |
demo123 |
User | Frontend/React profile |
[email protected] |
demo123 |
Disabled User | Login block testing |
The demo data also contains companies, jobs, skills, career roles, applications, saved jobs and AI history records.
/manage/ areaThe custom admin panel covers users, applications, companies, job categories, skills, career roles, jobs, AI logs, reports, OpenAI settings, ML/retrieval configuration and password management.
The documented user panel includes Dashboard, Profile, Resume, Jobs, Applications, AI Analysis, Profile Analysis, Skill Gap, Career Suggestions, History and Embeddings Refresh modules.
The project combines several AI, NLP, Machine Learning, and Information Retrieval techniques.
The production AI/ML pipeline includes NLP normalization, BERT dual encoder, optional contrastive training, BERT/OpenAI embeddings, cosine similarity, hybrid matching, skill-gap scoring, resume skill resolution, OpenAI JSON analysis, paraphrase augmentation, BM25 and FAISS retrieval.
User Profile + Resume
↓
Profile Skills Extraction
↓
NLP Normalization
↓
BERT Profile Embedding
↓
OpenAI Embedding (when configured)
↓
Job Skills + Job Description
↓
BERT / OpenAI Similarity
↓
Skill Overlap Calculation
↓
Cosine Similarity
↓
BM25 + FAISS Retrieval
↓
Hybrid Weighted Match Score
↓
Ranked Job Recommendations
OpenAI-specific features degrade gracefully if OPENAI_API_KEY is not configured, allowing BERT-based matching to continue while OpenAI-specific scores may be unavailable.
User Career Profile
↓
Existing Skills
↓
Select Target Career Role
↓
Load Weighted Skills Required for Role
↓
Compare Existing vs Required Skills
↓
Calculate Match %
↓
Identify Missing Skills
↓
Generate Skill Gap Report
The project uses pdfplumber for resume PDF text extraction and custom NLP/skill resolution for skill synchronization.
| Layer | Technology |
|---|---|
| Backend | Python 3.10+, Django 5.x |
| Database | SQLite by default |
| Authentication | Custom email-based user model, Django sessions |
| Frontend | Django Templates |
| CSS Framework | Bootstrap 5 |
| Icons | Bootstrap Icons |
| JavaScript | Vanilla JavaScript |
| Resume PDF | pdfplumber |
| Images | Pillow |
| NLP | NLTK |
| Transformer | BERT |
| ML Framework | PyTorch |
| Transformer Library | Hugging Face Transformers |
| Dense Retrieval | FAISS CPU |
| Sparse Retrieval | rank-bm25 |
| AI / LLM | OpenAI API |
| Embeddings | BERT + OpenAI |
| Similarity | Cosine similarity |
| Configuration | python-dotenv |
| Numerical Processing | NumPy |
| Search / Retrieval | BM25 + FAISS fusion |
The technology stack includes Django, Bootstrap, pdfplumber, NLTK, PyTorch, Hugging Face Transformers, FAISS, BM25, OpenAI, NumPy and supporting libraries.
cd "c:\Project\Python Source Code\AI-Based Career Profile Analysis, Skill Gap Prediction and Job Matching"
python -m venv venv
.\venv\Scripts\Activate.ps1
pip install -r requirements.txt
.env
copy .env.example .env
python manage.py migrate
python manage.py seed_demo
python manage.py runserver
| Password | Role | Notes | |
|---|---|---|---|
[email protected] |
admin123 |
Staff / Superuser | Admin panel |
[email protected] |
demo123 |
User | Main AI career demo |
[email protected] |
demo123 |
User | Data/Analytics profile |
[email protected] |
demo123 |
User | Frontend/React profile |
[email protected] |
demo123 |
Disabled User | Login block testing |
The demo data also contains companies, jobs, skills, career roles, applications, saved jobs and AI history records.