What you'll learn
- Wrangle and visualise data with NumPy, Pandas and Matplotlib
- Understand the linear algebra, statistics and probability behind ML
- Build regression, classification, tree and ensemble models with scikit-learn
- Engineer features and evaluate models correctly
- Build neural networks with PyTorch: CNNs, RNNs and transformers
- Track experiments with MLflow
- Serve models via APIs with Docker
- Monitor models for drift in production
Curriculum
7 modules · 23 topics · hands-on labs in every module
Python for Data3 topics
- NumPy, Pandas and data cleaning
- Visualisation with Matplotlib / Seaborn
- Exploratory data analysis
Maths for ML3 topics
- Linear algebra essentials
- Probability and statistics
- Gradient descent intuition
Classical Machine Learning4 topics
- Linear & logistic regression
- Decision trees, random forests, gradient boosting
- Clustering and dimensionality reduction
- Project: churn prediction model
Model Evaluation & Feature Engineering3 topics
- Train/validation/test splits, cross-validation
- Metrics: precision, recall, ROC-AUC, RMSE
- Feature engineering and pipelines
Deep Learning with PyTorch4 topics
- Neural networks from scratch
- CNNs for vision
- Sequence models and transformers
- Project: image classifier
MLOps4 topics
- Experiment tracking with MLflow
- Model serving with FastAPI and Docker
- Deploying on AWS SageMaker
- Monitoring and data drift
Capstone2 topics
- Capstone: ML feature for a live Incred product
- Model review with senior engineers
Requirements
- Basic Python
- Class 12 level maths (we'll refresh the rest)
About this program
LLMs get the headlines, but most production AI is still classical ML. This program teaches you the full lifecycle, from raw data to a monitored model in production.
After this program you can join the 6-month internship and take part in the ownership model: build an Incred vertical and earn a share, sell your product locally, or pitch your own idea for funding.
Your mentor
Amit Singh
CTO, Incred Applications Pvt Ltd · IIT Delhi alumnus
Leads the global engineering team of incred.golf across Germany, London, Croatia, India and Denver. Ex-lead at LangChain; previously with NVIDIA and IBM.