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Data Science & Analytics
Transform data into insights. Master statistical analysis, machine learning, and data visualization to make data-driven decisions and build predictive models.
7 Modules
Data Projects
Python & SQL
Course Curriculum
Master Python fundamentals, NumPy, Pandas, and data manipulation essentials.
- • Python Fundamentals
- • NumPy for Numerical Computing
- • Pandas for Data Manipulation
- • Data Cleaning and Preprocessing
Learn descriptive statistics, probability distributions, hypothesis testing, and A/B testing.
- • Descriptive Statistics
- • Probability Distributions
- • Hypothesis Testing
- • A/B Testing
Create compelling visualizations with Matplotlib, Seaborn, Plotly, and Streamlit dashboards.
- • Matplotlib Fundamentals
- • Seaborn Statistical Plots
- • Plotly Interactive Charts
- • Streamlit Dashboards
Build ML models with regression, classification, clustering, and scikit-learn.
- • Linear & Logistic Regression
- • Decision Trees & Random Forests
- • K-Means Clustering
- • Model Evaluation Metrics
Master gradient boosting, feature engineering, and advanced ML techniques.
- • Gradient Boosting (XGBoost, LightGBM)
- • Feature Engineering
- • Dimensionality Reduction (PCA)
- • Hyperparameter Tuning
Query and analyze data with SQL, joins, window functions, and database design.
- • SQL Fundamentals
- • JOINs and Aggregations
- • Window Functions
- • Database Design