Data Science
Become a full-stack Data Scientist. Master the end-to-end pipeline: from data engineering and statistical modeling to machine learning and production deployment.
What You Will Learn
A comprehensive curriculum covering the entire data science lifecycle.
Statistical Analysis
In-depth statistics, probability, hypothesis testing and data-driven storytelling.
Machine Learning
Building, tuning, and evaluating predictive models for real-world business problems.
Big Data & SQL
Handling large datasets using SQL, Spark, and cloud-based data environments.
Production ML
Deploying models as APIs using FastAPI, Docker, and monitoring model performance.
Course Curriculum
Four intensive modules to master the science of data.
Module 01: Data Engineering
SQL, data pipelines, ETL processes, and handling unstructured data.
Module 02: Advanced EDA
Exploratory Data Analysis, Feature Engineering, and Advanced Visualization.
Module 03: Machine Learning
Supervised, Unsupervised, Ensemble methods, and Model Optimization.
Module 04: ML in Production
API development, Model Serving, MLOps, and CI/CD for Data Science.
The Science Stack
Course Details
Duration: 12 Weeks
Intensive program with 200+ hours of learning and practice.
Pre-reqs: Programming
Basic Python/R and high-school math recommended.
Capstone Project
End-to-end Data Science project: From data scrape to ML deployment.
Certification
Full Professional Data Science Certification + Job Prep.
Learning Roadmap
Your step-by-step path to becoming a Data Scientist.
Data Engineering
Master SQL, ETL processes, and handling large-scale data architecture.
Statistical Modeling
Advanced EDA, Machine Learning algorithms, and model optimization techniques.
MLOps & Production
Deploy models as scalable APIs and manage the full ML lifecycle in production.
Data Science FAQ
Basic understanding of statistics, algebra, and calculus is helpful, but we cover the essentials.
It starts from basics but moves quickly into advanced concepts. Some programming familiarity is recommended.
Yes, we offer portfolio reviews, resume building, and mock interviews as part of the job prep module.