Certified Machine Learning Engineer
Build, tune and deploy production machine learning systems.
Program overview
A focused Machine Learning engineering certification — build, evaluate, tune and deploy models on real datasets, with emphasis on production thinking rather than notebook experiments. This Professional Certification runs for 5 Months as offline instructor-led classroom training at our Indore campus, combining daily lab practice, weekly assessments and mentor-reviewed projects.
- Students pursuing or having completed 12th / Diploma / Graduation (any stream)
- Working professionals looking to switch or upskill into technology roles
- Basic computer literacy — no prior coding experience required for foundation modules
- A laptop is recommended; institute lab systems are available for practice
- Apply Machine Learning Engineer skills to real business problems
- Build and present a mentor-reviewed capstone project
- Clear technical assessments and interview rounds with confidence
- Graduate with a portfolio, resume and GitHub profile employers can review
- Python for ML
- Feature engineering
- Supervised & unsupervised models
- Hyperparameter tuning
- Pipelines
- Model deployment
- MLOps basics
- Python
- Scikit-learn
- Pandas
- XGBoost
- MLflow
- FastAPI
- Docker
- Loan default prediction service
- Customer segmentation engine
- Demand forecasting model
- Deployed recommendation API
- Weekly module assessments in the classroom
- Hands-on lab evaluations with instructor feedback
- Final certification assessment
- Mock interview rounds before program completion
8-Module Curriculum
Expand any module to see exactly what is covered in the classroom and lab.
Module 1ML Foundations
- ML problem types
- Bias-variance tradeoff
- Data splitting
- Baseline models
Module 2Feature Engineering
- Encoding & scaling
- Handling imbalance
- Feature selection
- Leakage prevention
Module 3Regression & Classification
- Linear & logistic models
- Tree-based models
- Boosting (XGBoost/LightGBM)
- Metric selection
Module 4Unsupervised Learning
- Clustering
- Dimensionality reduction
- Anomaly detection
- Segmentation use cases
Module 5Model Tuning
- Cross-validation
- Grid & random search
- Regularisation
- Ensembling
Module 6Pipelines & Reproducibility
- Scikit-learn pipelines
- Experiment tracking with MLflow
- Versioning data & models
- Documentation
Module 7Deployment
- FastAPI inference service
- Docker packaging
- Batch vs real-time
- Monitoring drift
Module 8Capstone
- End-to-end ML product
- Business impact framing
- Presentation
- Mock ML interviews
What you walk away with
Internship eligibility is offered to top-performing learners on completion of the certification and capstone project, with an internship certificate awarded after successful completion.
- Professional Certification Certificate
- Project Completion Certificate
Roles this program prepares you for
Choose your batch
Frequently asked questions
Are Career Programs offline like your courses?
Yes. Every Career Program is delivered as offline, instructor-led classroom training at our Indore campus, with supervised lab practice.
What is the difference between a Diploma and a Certification?
Diplomas are longer (6–9 months) and cover an entire career track end to end with internship eligibility. Certifications (3–6 months) are focused on a single job role.
Do I need prior coding experience?
No. Every program starts from foundations. Prior experience helps but is not required for admission.
Is an internship included?
Diploma and Job Ready programs include internship placement for eligible learners. Certification learners become internship-eligible after clearing the capstone.
Will I get placement assistance?
Yes — resume building, LinkedIn optimisation, mock interviews, career mentorship and referral support are part of Diploma and Job Ready programs.
What are the fees and payment options?
Fees vary by program length. Call the campus or submit the admission form and our team will share the current fee structure and installment options.
Apply for Certified Machine Learning Engineer
Submit the admission form and our team will call you back to schedule a campus visit and counselling session.