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Bestselling Course
Master Data Science & Machine Learning
Learn to analyze data, build predictive models, and launch your career as a Data Scientist with our comprehensive 60-session curriculum.
60 Sessions
Certification
Exemplary Feedbacks
Avg. Salary
$120k+
Projects
15+
Prerequisites
Basic Python programming
Statistics fundamentals
Linear Algebra basics
What You'll Learn
Build end-to-end machine learning pipelines
Perform advanced statistical analysis & hypothesis testing
Create compelling data visualizations & dashboards
Deploy ML models to production environments
Work with big data frameworks like Spark
Master feature engineering & model optimization
Learning Roadmap
Python for Data Science
Session no. 1-8
Statistics & Probability
Session no. 9-16
Data Visualization
Session no. 17-22
ML Fundamentals
Session no. 23-32
Advanced ML & Deep Learning
Session no. 33-42
MLOps & Deployment
Session no. 43-50
Capstone Project
Session no. 51-60
Detailed Syllabus
Module 1: Python for Data Science
8 sessionsNumPy & Pandas masteryData manipulation & cleaningExploratory Data AnalysisJupyter Notebooks & workflows
Module 2: Statistics & Probability
8 sessionsDescriptive & inferential statisticsProbability distributionsHypothesis testing & A/B testingBayesian thinking
Module 3: Data Visualization
6 sessionsMatplotlib & SeabornPlotly interactive chartsDashboard creationStorytelling with data
Module 4: Machine Learning Fundamentals
10 sessionsLinear & logistic regressionDecision trees & random forestsSVM & KNNModel evaluation & cross-validation
Module 5: Advanced ML & Deep Learning
10 sessionsEnsemble methods (XGBoost, LightGBM)Neural networks with TensorFlowCNNs & RNNsNLP fundamentals
Module 6: MLOps & Deployment
8 sessionsModel serialization & APIsDocker for MLCI/CD for ML pipelinesAWS/GCP deployment
Module 7: Capstone Project
10 sessionsReal-world problem definitionEnd-to-end ML pipelineModel optimization & testingPresentation & code review