Why AI & Machine Learning?
AI/ML engineers are among the most in-demand roles in tech. But most bootcamps teach theory without production context. SkillCred's AI & ML stream is different — you'll build real ML pipelines, train models on custom datasets, fine-tune transformers, and deploy everything with MLOps best practices.
What You'll Build
Solo Project 1 — Predictive Analytics Dashboard (Weeks 1–2)
Build an end-to-end ML pipeline: dataset selection, EDA, feature engineering, training 3+ algorithms, hyperparameter tuning with Optuna, SHAP explainability, and a Streamlit dashboard. Each student picks a different dataset and problem domain.
Solo Project 2 — Image Classification System (Weeks 3–4)
Build a CNN-based image classifier with custom dataset, transfer learning (ResNet/EfficientNet), data augmentation, training visualization, confusion matrix analysis, and a Gradio web interface.
Pair Project — NLP Text Intelligence Engine (Weeks 5–6)
Fine-tune a HuggingFace transformer for multi-class text classification with custom training pipeline, evaluation suite, and FastAPI endpoint. One partner handles data pipeline + model training, the other builds API + frontend.
Group Capstone Options (Weeks 7–8)
Choose from: Smart Attendance System (face recognition), Crop Disease Detector, Resume Screening Engine, Fake News Detector, or Medical Image Analyzer. All include MLflow tracking, Docker deployment, and production monitoring.
8-Week Curriculum Overview
| Week | Phase | Key Topics |
|---|---|---|
| 1 | Python for ML & Math | NumPy, Pandas, Matplotlib, statistics, calculus intuition |
| 2 | Classical ML | Regression, Trees, SVM, KNN, K-Means, Scikit-learn pipelines |
| 3 | Feature Engineering | SMOTE, GridSearch, Optuna, XGBoost, SHAP/LIME |
| 4 | Deep Learning | Neural networks, TensorFlow/PyTorch, CNNs, transfer learning |
| 5 | NLP & Transformers | Tokenization, Word2Vec, RNNs/LSTMs, HuggingFace fine-tuning |
| 6 | Advanced Deep Learning | Object detection (YOLO), GANs, RL concepts, GPU optimization |
| 7 | MLOps & Production | MLflow/W&B, FastAPI serving, Docker, monitoring, drift detection |
| 8 | Capstone Sprint & Demo | Pipeline assembly, quantization, edge deployment, live demo |
Career Outcomes
Graduates are prepared for ML Engineer, Data Scientist, AI Developer, NLP Engineer, and MLOps Engineer roles.