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Intermediate
Data Science Mastery
From raw data to deployed machine learning models.
Master the complete data science pipeline — from exploratory analysis to production ML systems. You'll work with real datasets from Kaggle, build 5 end-to-end projects, and learn to communicate insights to non-technical stakeholders.
PythonNumPyPandasMatplotlibScikit-learnTensorFlowKerasSQLTableauMLflowFastAPIDocker
What you'll achieve
✓Build and deploy production ML models
✓Analyze datasets with 10M+ rows
✓Create executive-level data reports
✓Land data scientist/analyst roles
✓Pass data science interviews at top firms
Full curriculum
Week 1–3
Python & Statistics
Python refresherNumPy & PandasStatistical analysisProbability basicsData cleaning
Week 4–6
Data Visualization
Matplotlib & SeabornPlotly dashboardsTableau basicsStorytelling with dataEDA techniques
Week 7–10
Machine Learning
Regression & ClassificationEnsemble methodsFeature engineeringCross-validationHyperparameter tuning
Week 11–13
Deep Learning
Neural networksCNNs & RNNsTransfer learningNLP basicsComputer vision projects
Week 14–16
MLOps & Capstone
MLflow trackingModel serving with FastAPIDocker deploymentMonitoringEnd-to-end capstone
Your mentor
K
Dr. Kavitha Rajan
Principal Data Scientist @ Amazon
Industry expert with 10+ years of experience. Committed to practical, project-first teaching that prepares students for real-world roles.
Ready to start learning?
Talk to an advisor and get all your questions answered before you commit.
Book a Free Session →