Data Science Bootcamp with Python – From Data Wrangling to Prediction

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Data Science Bootcamp with Python – From Data Wrangling to Prediction

Modules and Content

1. Python for Data Analysis

Pandas, NumPy, data cleaning
Working with CSV, Excel, and APIs

2. Data Visualization with Matplotlib & Seaborn

Creating insightful charts, dashboards
Plot styling, storytelling with visuals

3. Statistical Foundations & Exploratory Data Analysis (EDA)

Hypothesis testing, correlation, regression
Outlier detection, feature engineering

4. Machine Learning with Scikit-Learn

Supervised/unsupervised learning
Model training, validation, and evaluation

5. Capstone Project: Predictive Model (Sales, Health, or Finance)

Real-world dataset + report + deployment

Reference

“Piping Handbook” by Mohinder L. Nayyar ,
“Process Piping: The Complete Guide to ASME B31.3” by Charles Becht IV,
“Pipe Stress Engineering” by Liang-Chuan Peng and Tsen-Loong Peng
“Piping Design Handbook” by John J. McKetta Jr.
“The Planning Guide to Piping Design” by Richard Beale and David R. Sherwood