AI & DataIntermediate
AI & Machine Learning
Data science, ML models and Generative AI
Learn how modern AI systems are built — from data wrangling and classical machine learning to deep learning and Generative AI with large language models. Every module ends in a practical model you train, evaluate and deploy.
12 weeks · 8 hrs/week 15 lessons in 4 modules Online with AI tutor Classroom in Pune
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Register to view feesI already have an accountWhat you'll learn
- Clean, explore and visualise data with pandas and matplotlib
- Train and evaluate regression, classification and clustering models
- Build neural networks with PyTorch / TensorFlow
- Create LLM applications with prompt engineering and RAG
Curriculum
4 modules · 15 lessons
1Data Foundations
4 lessons · The maths and tools behind every ML project.
Data Foundations
4 lessons · The maths and tools behind every ML project.
- NumPy and vectorised computingWork with arrays efficiently.Preview45m
- pandas for data wranglingLoad, clean, join and reshape datasets.45m
- Exploratory data analysis and visualisationFind patterns with charts and statistics.45m
- Statistics and probability essentialsDistributions, sampling and hypothesis testing.45m
2Classical Machine Learning
4 lessons · Supervised and unsupervised learning with scikit-learn.
Classical Machine Learning
4 lessons · Supervised and unsupervised learning with scikit-learn.
- Linear and logistic regressionYour first predictive models.45m
- Decision trees, random forests and boostingPowerful models for tabular data.45m
- Model evaluation and cross-validationMetrics, overfitting and honest evaluation.45m
- Clustering and dimensionality reductionK-means, PCA and customer segmentation.45m
3Deep Learning
3 lessons · Neural networks for images, text and sequences.
Deep Learning
3 lessons · Neural networks for images, text and sequences.
- Neural network fundamentalsPerceptrons, activation functions and backpropagation.45m
- Computer vision with CNNsImage classification and transfer learning.45m
- NLP with transformersTokenisation, embeddings and attention.45m
4Generative AI & MLOps
4 lessons · LLM applications and putting models in production.
Generative AI & MLOps
4 lessons · LLM applications and putting models in production.
- Prompt engineering and LLM APIsGet reliable outputs from large language models.45m
- Retrieval-augmented generation (RAG)Ground LLMs in your own documents with vector search.45m
- Serving models with FastAPI and DockerExpose a model as a production API.45m
- Capstone: end-to-end AI productShip a data-to-deployment AI project.45m