Master AI to Create Solutions
That Think, Learn & Predict
Learn how to design, train, and deploy machine learning models through mentor-guided, real-world projects.
Why This Track?
Artificial Intelligence is reshaping every industry. This track gives you the practical skills to build predictive models, NLP apps, and smart systems.
Who This Track Is For
- College students (any stream)
- Beginners in AI & ML
- Coding enthusiasts with interest in algorithms
- Career switchers aiming for AI/ML roles
- Professionals seeking AI upskilling
Tools You Will Master
The essential stack for modern AI Engineers
How You Will Learn
Live Mentor Sessions
Project-led guidance
Real Datasets
Work with authentic data
Weekly Milestones
Track progress regularly
Recorded Lessons
For concept revision
Step-by-step
Guided project building
Doubt Support
Clear your queries
Curriculum by Program
Choose your learning pace and explore the week-by-week structure.
AI & Machine Learning - Standard (8 Weeks)
Comprehensive 8-week project-based learning curriculum covering all fundamentals and advanced concepts.
- Learning Materials & Concepts
- Project Activity: SOLO PROJECT 1 START
- Learning Materials & Concepts
- Project Activity: SOLO PROJECT 1 DELIVERY
- Learning Materials & Concepts
- Project Activity: SOLO PROJECT 2 START
- Learning Materials & Concepts
- Project Activity: SOLO PROJECT 2 DELIVERY
- Learning Materials & Concepts
- Project Activity: PAIR PROJECT START
- Learning Materials & Concepts
- Project Activity: PAIR PROJECT DELIVERY
- Learning Materials & Concepts
- Project Activity: GROUP CAPSTONE START
- Learning Materials & Concepts
- Project Activity: GROUP CAPSTONE DELIVERY
Project Roadmap (6 Projects)
From solo builds to team capstones — real-world projects that prove your skills
Voice & Audio Emotion Recognition
Converting audio to Mel-spectrograms, training a CNN/ResNet, real-time microphone inference in browser. Handing noisy data and varied accents.
💼 Mid-Level ML. Working with unstructured data (audio) and deep learning.
Customer Lifetime Value (CLV) & Churn Predictor
Cohort analysis, RFM modeling, survival analysis, and XGBoost/LightGBM prediction. Deployed as a Streamlit app where marketing teams can upload CSVs and get risk dashboards.
💼 Junior ML Engineer. End-to-end tabular data handling.
Enterprise RAG (Retrieval-Augmented Generation) System
Enterprise RAG (Retrieval-Augmented Generation) System
💼 Senior ML. LLMs, Vector DBs, and advanced search.
AI-Powered Legal Contract Analyzer
NER for clause extraction, risk highlighting using LLMs, anomaly detection in contract terms compared to company standards.
💼 Capstone Project
Algorithmic Trading & Signal Generator
Reinforcement learning for portfolio balancing, sentiment analysis on financial news feeds, historical backtesting engine.
💼 Capstone Project
Multi-Modal Personal Shopper
Visual search (upload image to find similar items), conversational AI for style advice, integrating vision and NLP transformers.
💼 Capstone Project
Mentor Support & Verification
Our mentors don't just teach — they verify your skills. Every project you build is reviewed, ensuring you meet industry standards before you get certified.
- Assign & explain projects
- Review project submissions
- Verify project completion
- Provide feedback
- Approve assessment eligibility
- Issue recommendation letters
Projects Are Not Self-Assessed
"You cannot certify yourself. A working professional mentor must start, review, and approve your work."
Project-Based Assessment Test (PAT) Format
Assessment is based on how you build, improve, and explain projects — not on a single final exam.
Overall Structure (100 Marks)
1. Project Completion & Quality
Evaluated across best 3 projects. Mentor checks problem understanding, implementation, tools, and code quality.
2. Milestone Reviews
3. Business Value
4. Tool Proficiency
5. Final Defense
Pass Criteria
- Minimum 60/100 Score
- All 5 Projects Completed
- Mentor Verification Done
- No Plagiarism Found
Plagiarism Check
- Code similarity check
- Git commit history audit
- Oral questioning
- Random live modification
Certification
You only receive the SkillCred Project-Based Certificate & Recommendation Letter if all criteria are met.
Your Portfolio Output
Your portfolio will show model project details, dataset used, algorithm & tool applied, accuracy metrics, mentor verification, and assessment scores.
HR-Ready Profile
Recruiters can filter candidates based on these specific skills.
Career Outcomes
HR Corner (Preview)Recruiter View
Frequently Asked Questions
Do I need prior Python experience?
No — Python basics are included in the track.
Are projects real-world?
Yes, each project replicates real industry problems.
Is deployment included?
Yes, models are deployed via Streamlit / Flask for live testing.
Will I be job-ready?
Absolutely — the track covers building, evaluating, and deploying AI systems.