Machine Learning & Deep Learning (Practical)
Build real ML models from scratch. Project-based, deployment-focused — not just theory.
This course is built for you if…
Engineering graduates
Your math and programming background is the ideal foundation. This course builds on it systematically — from ML fundamentals through deep learning to deployment.
Data Analytics graduates
You know Python and SQL. This course takes you from analysis to prediction — building models that automate the insights you currently produce manually.
Research-oriented learners
Kaggle competitions, HuggingFace model cards, and GitHub repositories that demonstrate real ML capability — the profile that opens doors to research roles.
Working software developers
ML is increasingly integrated into software products. Learn to build and deploy models as part of a backend system — a skill that commands premium salaries.
What you’ll learn week by week
ML Fundamentals & Scikit-learn
ML FoundationsSupervised learning · Linear/logistic regression · Decision trees, random forests · KNN · Model evaluation metrics · Cross-validation
Unsupervised learning · K-means clustering · PCA · Feature engineering · Pipeline construction · Hyperparameter tuning
Deep Learning with TensorFlow & Keras
Deep LearningNeural network fundamentals · Backpropagation · TensorFlow + Keras setup · Dense networks · Regularisation · Batch normalisation
CNNs for computer vision · Image augmentation · Transfer learning · Pre-trained models (ResNet, MobileNet) · Fine-tuning
Natural Language Processing
NLPNLP fundamentals · Text preprocessing · Sentiment analysis · Transformers intro · HuggingFace library · Fine-tuning BERT · Building NLP pipelines
PyTorch & Advanced Deep Learning
PyTorchPyTorch fundamentals · Custom datasets + dataloaders · Training loops · RNNs and time-series intro · Model comparison: TF vs PyTorch
MLOps & Deployment
DeploymentModel deployment with FastAPI · Streamlit dashboards · Docker basics · HuggingFace Spaces hosting · API endpoint for ML model
Capstone project · Portfolio submission · Kaggle public notebook · GitHub README · HuggingFace model card · Career path presentation
Everything you’ll master
Real deliverables. Real work.
Kaggle classification project
Customer churn prediction model with full EDA, feature engineering, and model evaluation.
Customer segmentation model
K-means clustering on real customer data — business-ready insights and visualisation.
Transfer learning image model
Computer vision model using transfer learning — >90% accuracy on a real classification problem.
NLP sentiment model
Fine-tuned BERT model for sentiment analysis — deployed live on HuggingFace Spaces.
Full deployment capstone
Complete ML project: data → model → FastAPI endpoint → Streamlit dashboard. Publicly accessible.
Real work experience guaranteed
Offline classes in Kothamangalam
Nellikuzhi, Kothamangalam, Ernakulam, Kerala 686691
Easily reachable from
- Muvattupuzha15 min
- Perumbavoor30 min
- Aluva40 min
- Ernakulam / Kochi45 min
Weekend and evening batches available for working professionals across Ernakulam district. Online live-stream batches open to students outside Kerala.
Apply Now →Invest in your future at your pace
Pay in instalments
| When | Amount | Note |
|---|---|---|
| Day 1 | ₹10,750 | Pay on enrollment |
| Week 4 | ₹7,000 | After 4 weeks |
| Week 8 | ₹7,000 | After 8 weeks |
| Week 12 | ₹7,000 | After 12 weeks |
| When | Amount | Note |
|---|---|---|
| Day 1 | ₹9,250 | Pay on enrollment |
| Week 4 | ₹6,333 | After 4 weeks |
| Week 8 | ₹6,333 | After 8 weeks |
| Week 12 | ₹6,334 | After 12 weeks |
What’s included
- 28 live sessions
- Recordings
- 4-week external internship
- Certificate
- LOR
- LinkedIn recommendation
- Kaggle + GitHub + HuggingFace setup
- ML resume template
- Technical mock interview
- Portfolio review
- Alumni Telegram + Discord
- Google Colab Pro access guidance
Ready to start? Seats are limited per batch.
Apply Now — Secure Your Seat →