What You’ll Learn

Our Data Science Academy is designed to take you from beginner to industry-ready. Here's a detailed breakdown of what you’ll master — from data fundamentals to production-grade AI systems.

Foundations of Data Science 🧠

  • Python Programming for Data Science (NumPy, Pandas, Scikit-Learn)

  • SQL for Analytics and Reporting

  • Statistics, Probability, and Hypothesis Testing

  • Exploratory Data Analysis & Visualization (Matplotlib, Seaborn)

  • Data Cleaning, Feature Engineering

  • Version Control with Git & GitHub

Machine Learning Techniques 🤖

  • Supervised Learning (Regression, Classification)

  • Unsupervised Learning (Clustering, Dimensionality Reduction)

  • Tree-Based Models: Random Forest, XGBoost, LightGBM

  • Model Evaluation: Confusion Matrix, ROC-AUC, Precision-Recall

  • Cross-Validation & Hyperparameter Tuning

  • Model Explainability: SHAP, LIME

Deep Learning & Model Optimization 🔬

  • Introduction to Neural Networks

  • CNNs for Image Data, RNNs/LSTMs for Sequential Data

  • Transfer Learning & Fine-Tuning

  • Knowledge Distillation for Lightweight Models

  • Quantization & Pruning for Deployment Optimization

Generative AI & LLM Applications 💡

  • Fundamentals of Generative AI & Large Language Models

  • Prompt Engineering & Few-Shot Learning

  • Retrieval-Augmented Generation (RAG) Architecture

  • Building Smart Agents & Assistants with LLM APIs

  • Safety, Fairness, and Ethical Use of GenAI

MLOps & Model Lifecycle Management 🛠️

  • ML Lifecycle: Experiment Tracking, Version Control (MLflow)

  • Model Packaging: Docker, ONNX, TorchScript

  • CI/CD for Machine Learning

  • Model Deployment Strategies (Batch, Real-Time, A/B Testing)

  • Monitoring, Drift Detection, and Feedback Loops

  • Feature Stores & Metadata Management

Cloud Platforms & Production Deployment ☁️

  • Introduction to AWS (S3, SageMaker, Lambda, CloudWatch)

  • Deploying APIs with FastAPI, Flask

  • Azure & GCP: Comparative Cloud Concepts (Optional)

  • Serverless Inference & Edge Deployments

  • Scaling Models in Production

Career Readiness & Capstone Projects 🎓

  • Introduction to AWS (S3, SageMaker, Lambda, CloudWatch)

  • Deploying APIs with FastAPI, Flask

  • Azure & GCP: Comparative Cloud Concepts (Optional)

  • Serverless Inference & Edge Deployments

  • Scaling Models in Production