Cyber Security & Ethical Hacking Foundations
Learn defensive security fundamentals, ethical hacking concepts and common web/network risks in a responsible lab environment.
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Machine Learning Engineer
Design, train, evaluate and serve practical machine-learning models.
Admissions Open
₹29,999 Indicative fee — update before production launch
Duration16 Weeks
FormatOnline / Classroom
LevelIntermediate
ScheduleWeekday / Weekend batches
Course overview
Go beyond introductory data science into reusable machine-learning pipelines. Learn feature engineering, model selection, evaluation, imbalance handling, tree-based models, experiment discipline and API-based model serving.
What you will be able to do
✓Build reproducible ML pipelines
✓Choose suitable evaluation metrics
✓Train and tune classical ML models
✓Handle real-world data issues
✓Serve models through APIs
Curriculum
ML Foundations3 Weeks
Problem types
Train/validation/test
Metrics and baselines
Feature Engineering3 Weeks
Encoding and scaling
Missing values
Leakage and pipelines
Supervised Learning4 Weeks
Linear models
Trees and ensembles
Gradient boosting
Model Evaluation & Tuning3 Weeks
Cross-validation
Hyperparameter tuning
Imbalanced data
Serving ML Models3 Weeks
Model packaging
FastAPI inference API
Monitoring concepts
Projects you can build
Fraud Risk Classifier
End-to-end binary classification pipeline with evaluation and API serving.
Lead Scoring Model
Predictive scoring workflow with explainable business metrics.
Frequently asked questions
Do I need prior experience?
The entry requirement depends on the course level. Beginner courses start from fundamentals; intermediate tracks expect basic programming or domain knowledge.
Will I build projects?
Yes. Every course includes practical labs and one or more projects designed to help you demonstrate the skills you learn.
Is a certificate included?
Yes. A completion certificate can be issued after meeting attendance, assessment and project requirements.
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