| File Name: | Python Programming & Data Science |
| Content Source: | https://www.udemy.com/course/python-data-science-machine-learning-engineering-ai/ |
| Genre / Category: | Programming |
| File Size : | 1.8 GB |
| Publisher: | Expert Planners |
| Updated and Published: | March 17, 2026 |
Welcome to the Complete Python for Data Science & Engineering Bootcamp—the only course you need to bridge the gap between technical engineering and Artificial Intelligence. With 16 years of professional experience in civil engineering and project scheduling, I have designed this curriculum to be the most practical, engineering-focused Python program on Udemy. Whether you have zero programming experience or you are a seasoned engineer looking to automate your workflow, this course will take you from beginner to professional.
Why is this the right course for you?
This isn’t just another generic coding bootcamp. This is a specialized path designed to turn you into a Data-Driven Engineer. Here’s why this course stands out:
- Engineering-First Approach: We don’t just build games; we solve real problems. You’ll master Computational Mechanics, the Stiffness Method, and Truss Analysis using Python.
- Complete Data Science Stack: You will become fluent in the industry-standard libraries used at companies like Tesla, Boeing, and Google: NumPy, Pandas, Matplotlib, and Scikit-learn.
- Master Modern AI: From Linear Regression to Deep Learning (Neural Networks) and XGBoost, you will learn to build predictive models that can be applied to slope stability, construction scheduling, and more.
- Project-Based Learning: Every section includes a Quiz and a Practical Coding Exercise to ensure you aren’t just watching, but actually doing.
The Step-by-Step Curriculum
We take you through a massive range of tools and technologies, organized into 6 professional modules:
- Python Essentials: Variables, Logic, Loops, and Functions.
- Computational Mechanics: Finite Element Analysis (FEA), 2D Truss Analysis, and Matrix Theory.
- Data Analytics: High-performance manipulation with Pandas and NumPy.
- Scientific Visualization: Professional figures and plotting with Matplotlib.
- Machine Learning (ML): Supervised and Unsupervised learning, Logistic Regression, and SVMs.
- Advanced AI & Ensembles: Artificial Neural Networks (ANN), Decision Trees, Random Forests, and XGBoost.
DOWNLOAD LINK: Python Programming & Data Science
Python_Programming_Data_Science.part1.rar – 1000.0 MB
Python_Programming_Data_Science.part2.rar – 875.6 MB
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