Python for Engineers, Scientists and Analysts
Python for Engineers, Scientists and Analysts
Introduction to Data Analysis, Engineering and Science Statistics, Modelling, Simulation and Visualisation
Product Brand: Udemy
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Udemy Coupon Code for Python for Engineers, Scientists and Analysts Course. Introduction to Data Analysis, Engineering and Science Statistics, Modelling, Simulation and Visualisation
Created by Harry Munro | 1.5 hours on-demand video | 17 downloadable resources
Python for Engineers, Scientists and Analysts Course Overview
Unlock the power of Python to address real-world challenges in engineering, science, and data analysis. This course is designed to provide you with the essential skills needed to apply Python in practical, industry-relevant contexts – whether you’re seeking to automate your work, aiming to enhance your data analysis capabilities, or simply interested in using Python to simplify complex tasks.
Developed for learners of all levels, this course provides clear, structured guidance on the core concepts of Python. Through hands-on exercises and real-world examples, you will learn how to import, clean, and manipulate data, perform key statistical analyses, build mathematical models and simulations, and create professional visualisations. The lessons are concise and focused, ensuring you can acquire the knowledge and skills you need efficiently.
While covering fundamental Python programming and data analysis techniques, this course is intentionally designed to avoid more advanced topics such as machine learning, object-oriented programming, and complex Boolean operations – allowing you to focus on practical skills that can be applied immediately.
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What you’ll learn
- Learn how to install and run Python on your computer
- Write and execute basic Python scripts.
- Import data from CSV files and other formats.
- Utilise libraries such as Pandas for data manipulation and exploration.
- Apply statistical methods to analyse data (e.g., mean, median, standard deviation).
- Calculate and interpret descriptive statistics using Python libraries.
- Apply advanced statistical measures such as percentiles and interquartile range to gain deeper insights into data variability.
- Create new data using mathematical and statistical models.
- Simulate real-world scenarios using models in Python.
- Generate plots and visualisations using libraries like Matplotlib and Seaborn.
- Create informative charts, graphs, and plots to summarise data.
- Write functions for repetitive tasks in data analysis.
- Understand the concept of modular programming and apply it to real-world problems.
- Solve engineering, scientific, and analytical problems using Python.
- Integrate data analysis and visualisation techniques to extract insights from data.
- Present data analysis results through clear, professional visualisations.
- Use Python to automate processes and produce immediate, actionable insights.
Who this course is for:
- Engineers, Scientists, and Analysts
- Students and Academics
- Industry Professionals Looking to Upskill
- Beginners Interested in Python for Data Science
