Master pandas, NumPy, matplotlib, and statistical analysis to extract meaningful insights from complex datasets and make data-driven decisions.
Start your data science journey with this comprehensive course covering essential tools and techniques. Learn to work with real datasets, perform statistical analysis, and create compelling visualizations that tell data stories.
Python basics, data types, control structures, functions, and data science libraries overview
Arrays, mathematical operations, broadcasting, linear algebra, and random numbers
DataFrames, Series, indexing, grouping, merging, and time series analysis
Handling missing data, outliers, data transformation, and feature engineering
Matplotlib fundamentals, seaborn for statistical plots, and interactive visualizations
Descriptive statistics, probability distributions, correlation, and regression analysis
A/B testing, t-tests, chi-square tests, and interpreting statistical significance
End-to-end data analysis project with real-world dataset and presentation
Senior Data Scientist at LinkedIn
PhD in Statistics from Berkeley, 8+ years in data science, led analytics teams at Uber and LinkedIn, expert in statistical modeling and A/B testing.
Analyze retail sales data to identify trends, seasonal patterns, and key performance indicators.
Pandas + MatplotlibUse statistical analysis to segment customers based on behavior and demographics.
Statistical AnalysisBuild an interactive dashboard to monitor and analyze A/B test results.
Hypothesis Testing"Dr. Smith made data science so accessible! As someone with no programming background, I never thought I could do this. Now I'm a data analyst at Spotify!"
"The hands-on projects were perfect for learning. The portfolio I built from this course helped me transition from marketing to data science at Amazon."