Artificial Intelligence & Machine Learning
A practical AI track focused on data workflows, model thinking, evaluation and real industry applications.
Designed as a guided journey: concepts, practice, project work and enquiry support.
Learning architecture
What you will learn.
Each program is structured to move from fundamentals to application, then into practical implementation and project presentation.
Advanced Curriculum
- Python for AI workflows
- Data cleaning, preprocessing and visualization
- Machine learning foundations: regression, classification and clustering
- Model training, testing and evaluation
- AI use cases, prompt workflows and responsible usage
Practical Sessions
- Prepare datasets for machine learning
- Train and evaluate prediction/classification models
- Build a simple AI assistant workflow
- Interpret results and improve model output
Project Outcomes
- Prediction model
- Classification model
- AI assistant prototype
- Data-driven recommendation workflow
After completing this, you will be able to
- Know what AI can and cannot do
- Build practical AI workflows using data
- Understand model accuracy, evaluation and application areas
Need guidance?
Know the details before you join.
For session booking, duration, mode, fees, internship details, certification and project guidance, contact SCIENWAVE directly.