Learn How Machine Learning Models Are Built and Evaluated
Move from Python and data foundations into practical machine learning. Learn how to prepare data, choose algorithms, train models, evaluate results and communicate model performance.
Supervised Learning
Understand regression and classification workflows.
Unsupervised Learning
Learn clustering and pattern-discovery foundations.
Model Evaluation
Use appropriate metrics and validation thinking.
Project Practice
Apply concepts to guided datasets and capstone work.
Who This Course Is For
- Python learners with basic data handling knowledge.
- Data Science learners moving into modelling.
- Students targeting AI/ML career paths.
- Professionals who want practical ML foundations.
What You Will Be Able to Do
- Prepare data for modelling.
- Train basic regression and classification models.
- Apply clustering techniques.
- Evaluate model performance using suitable metrics.
- Document experiments and project results clearly.
Course Curriculum
ML Foundations
- Problem types
- Features and targets
- Train/test split
- Bias and variance concepts
- Preprocessing
- Baseline models
Supervised Learning
- Linear regression
- Logistic regression
- Decision trees
- Ensemble concepts
- Classification workflow
- Evaluation metrics
Unsupervised Learning
- Clustering concepts
- K-means
- Dimensionality reduction foundations
- Pattern discovery
- Use-case selection
Practical Workflow
- Feature preparation
- Model comparison
- Validation thinking
- Error analysis
- Experiment tracking concepts
- Project presentation
Projects & Practical Work
Project difficulty is adjusted to the learner's level and batch progress. The goal is to turn concepts into demonstrable work rather than only complete theory modules.
- Regression project
- Classification project
- Clustering project
- Machine learning capstone
Career Preparation
Mango Engineers' learning process can include project review, portfolio/GitHub readiness, resume guidance, mock interview practice and placement assistance. Placement assistance is support, not a job guarantee.
- Machine Learning pathway
- Data Science pathway
- Junior ML/Analytics Associate
- AI learning pathway
Frequently Asked Questions
Basic Python and data handling are recommended. Statistics foundations also help.
Yes. The course is designed around guided model-building and evaluation projects.
This page focuses on machine learning foundations. Advanced deep learning can be taken as a later AI pathway.
No. Mango Engineers can support career preparation, but cannot guarantee employment.
