The 10-Day Python Bootcamp for Engineers and Scientists 2025 from Udemy

Python Skills for Professionals – Guaranteed in Just 10 Days or Your Money Back

if engineer_or_scientist and wants_to_learn_python:

print("Welcome. You are in the right place, please read on. ")

else:

print("This probably isn't for you but please feel free to check it out anyway.")

What’s Included:

Bite-Sized, Actionable Lessons: No fluff, no wasted time - just concise, practical Python training tailored for busy professionals.
Real-World Application: From visualising data to simulating an investment portfolio, every exercise is designed to mimic real-world challenges in engineering, science, and finance.
Industry-Tested Techniques: Learn from proven tools and workflows with Pandas, NumPy, and Seaborn – essentials for modern data analysis and modelling.
Comprehensive Resources: Downloadable code snippets, quizzes, and a final project to simulate and analyse an investment portfolio’s performance.
Lifetime Access and Updates: Enjoy free lifetime access to all lessons and updates, including restructured modules and harder exercises based on feedback.

3 Reasons Why this Course is a No-Brainer:

Made by an engineer, for engineers: I'm a chartered mechanical engineer and I've coded in Python for over a decade. Skip endless YouTube tutorials and blog posts. Get straight to practical skills that are actually relevant for industry application.
Gain Immediate Results: Test your knowledge with coding exercises, assignments and quizzes throughout the course.
Be Ready for the Future: Python is essential for modern fields like AI and data science. You can magnify your existing skillset by leveraging the power of Python.

Course updates:

5th December 2024: Some general bug fixes.
24th November 2024: Added a big final coding exercise where you will simulate the returns of an investment portfolio and analyse the performance. Also made some of the coding exercises a little harder in response to feedback.
28th October 2024: Big update - complete restructure to the course, breaking down lessons into much smaller bite-sized chunks to make it far easier to reference different sections.

"This is exactly what I was looking for to help jumpstart my Python skills." - Rhys Feeney, Product Manager at Ocula Technologies

“Perfect Course for Busy Professionals Who Want Real-World Python Skills. The bite-sized lessons are perfect for someone like me who’s juggling work and learning. The course goes straight to the point, cutting out unnecessary fluff, and dives right into practical, industry-relevant examples.” - Grace, Actuary

“This course is fantastic. Just the right level of detail and pacing to help get up to speed with Python and then apply the knowledge to real-world scenarios. I’d especially recommend this course for mechanical, chemical, or civil engineers and scientists who have resisted trying Python but are now ready to dive in.” - Chris, Engineer

Enrol today, enjoy lifetime access (including access to all future course updates) and level up your Python skills in 10 days or your money back.

What's inside

Learning objectives

Learn practical python programming for data science, engineering, modelling and simulation tasks
Analyze and manipulate data using pandas and numpy
Visualise data with matplotlib and seaborn
Develop predictive models and simulate real-world scenarios
Automate data processes to produce immediate, actionable insights
Understand and apply statistical methods to analyse and interpret data
Create professional visualisations to present your findings
Write efficient python scripts and functions for data analysis

Solve engineering, scientific, and analytical problems using python
Build practical projects to showcase your skills
Prepare for a career in data science, analytics or engineering
Apply your skills to real-life business cases and projects
Understand the concept of modular programming and apply it to real-world problems
Work with real datasets to solve complex analytical challenges
Show more
Show less

Learn practical python programming for data science, engineering, modelling and simulation tasks
Analyze and manipulate data using pandas and numpy
Visualise data with matplotlib and seaborn
Develop predictive models and simulate real-world scenarios
Automate data processes to produce immediate, actionable insights
Understand and apply statistical methods to analyse and interpret data
Create professional visualisations to present your findings
Write efficient python scripts and functions for data analysis
Solve engineering, scientific, and analytical problems using python
Build practical projects to showcase your skills
Prepare for a career in data science, analytics or engineering
Apply your skills to real-life business cases and projects
Understand the concept of modular programming and apply it to real-world problems
Work with real datasets to solve complex analytical challenges
Show more
Show less

Syllabus

Learn about the upcoming course!

Introduction to the Section

Course Outcomes

Real World Applications

This quiz tests your understanding of the BIDMAS rule, which dictates the order of operations in mathematical expressions. In Python, just as in mathematics, it's important to follow this order to ensure accurate calculations. This quiz will help you reinforce your knowledge of the correct sequence for solving expressions.

This quiz tests your knowledge of different data types in Python and how to choose the right type for various tasks. As an engineer, scientist, or analyst, selecting the correct data type is crucial for accurately storing and manipulating information in your programs. This quiz will guide you through key scenarios to ensure you can confidently use the appropriate data type for each task.

This quiz assesses your understanding of key statistical concepts, such as mean, median, mode, standard deviation, and variance, as well as how to calculate them using Pandas in Python. You will also test your knowledge of how outliers affect data and how to interpret statistical results in data analysis. By the end of this quiz, you'll reinforce your ability to perform statistical calculations on real-world datasets, a crucial skill for engineers, scientists, and analysts.

This quiz will test your understanding of the primary functions and purposes of the NumPy library in Python. NumPy is essential for handling large arrays and performing numerical computations efficiently. By the end of this quiz, you'll reinforce key concepts of how NumPy is used in data manipulation and analysis.

Quiz Description: This quiz tests your knowledge of Pandas, a crucial Python library for data manipulation and analysis. You’ll be quizzed on the structure and functionality of DataFrames, how to explore data, and key methods used in Pandas. By the end of this quiz, you’ll have a stronger understanding of how to work with Pandas to manage and analyse large datasets.

This quiz tests your knowledge on working with time-related data in Pandas. You'll explore how to convert columns to datetime formats, extract useful date-specific information like months and hours, and aggregate data using the groupby() function. Mastering these skills is essential for data analysis tasks where time-based trends and patterns are critical. By the end of this quiz, you will better understand how to manipulate and analyse time-related data in Python, extracting valuable insights from datasets.

This quiz focuses on key concepts in data visualisation using Seaborn, with an emphasis on how to effectively display distributions and categorical data. You will be tested on the best plotting techniques for comparing distributions across categories, as well as the functionality of Seaborn's versatile catplot() function. By completing this quiz, you will solidify your understanding of how to visualise and interpret data using the most appropriate plots in Seaborn.

This quiz is designed to test your knowledge of Python functions and their role in writing reusable, efficient code. You'll also explore how to apply custom functions to data using Pandas. By the end of this quiz, you will solidify your understanding of how functions work in Python, how to define them, and how they are applied in real-world data analysis tasks. These are essential skills for anyone working with Python for data analysis, engineering, or software development.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses Pandas, NumPy, and Seaborn, which are essential tools for modern data analysis and modeling in engineering and scientific fields

Includes a final coding exercise simulating the returns of an investment portfolio and analyzing its performance, which is relevant to finance and engineering

Teaches skills that are applicable to real-life business cases and projects, allowing learners to immediately apply their knowledge

Course content is updated as recently as December 2024, suggesting that the course is actively maintained and reflects current practices

Requires learners to install Thonny, which may not be the preferred IDE for all engineers and scientists who may already be familiar with other IDEs

Focuses on Python 3, which is essential as Python 2 is deprecated and no longer supported, ensuring learners are using a relevant and up-to-date language

Reviews summary

Practical python for engineers and scientists

According to learners, this bootcamp offers a highly practical and efficient way to learn Python for engineering and scientific applications. Students particularly praise the bite-sized lessons, which are ideal for busy professionals balancing work and study. The course covers essential libraries like Pandas and NumPy with a strong focus on real-world examples and data, making the skills immediately applicable. Recent updates to the course structure and exercises have been well-received, showing the instructor is responsive to feedback. However, the fast pace means it may be challenging for absolute beginners or those unable to dedicate significant time.

Concise lessons well-suited for busy professionals' schedules.

"The bite-sized lessons fit into my schedule, and the practical examples..."

"The bite-sized lessons are perfect for someone like me who’s juggling work and learning."

"Big update - complete restructure to the course, breaking down lessons into much smaller bite-sized chunks..."

Recent updates enhanced structure and added valuable content.

"...including restructured modules and harder exercises based on feedback."

"Excellent course! The restructured lessons are very easy to navigate."

"The updated exercises after the feedback were definitely better and more challenging."

"I appreciated the recent updates making the course more challenging and the final project is a good addition."

Provides solid introduction to essential Python libraries.

"Good crash course for getting up to speed with Python for data analysis. Covers the essential libraries."

"Solid bootcamp covering essential tools like Pandas and NumPy."

"Learn from proven tools and workflows with Pandas, NumPy, and Seaborn – essentials for modern data analysis and modelling."

Applies Python skills to practical, relevant problems.

"As a mechanical engineer, ... the practical examples using Pandas and NumPy were immediately applicable to my work."

"The course goes straight to the point... dives right into practical, industry-relevant examples."

"Loved the practical focus. Learned a lot about data visualization with Seaborn and Matplotlib that I can use right away."

"every exercise is designed to mimic real-world challenges in engineering, science, and finance."

Intense pace; requires dedication and may challenge beginners.

"Ten days is intense, but achievable if you dedicate the time. Some parts felt a little rushed..."

"The pace is very fast, definitely not for absolute beginners unless you can commit significant hours per day."

"Too fast paced for me. Assumes too much prior knowledge... Struggled to keep up after the basic Python syntax."

"Decent introduction... Useful if you need a quick overview."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The 10-Day Python Bootcamp for Engineers and Scientists 2025 with these activities:

Review Order of Operations (BIDMAS/PEMDAS)

Show steps

Reinforce your understanding of the order of operations to avoid errors in Python calculations, especially when modeling physical systems.

Browse courses on Order of Operations

Show steps

Review the rules of BIDMAS/PEMDAS.
Practice solving mathematical expressions manually.
Write Python code to solve the same expressions and compare results.

Review 'Python Crash Course'

Show steps

Solidify your understanding of Python fundamentals with a comprehensive guide.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

Show steps

Read the chapters covering basic Python syntax and data structures.
Work through the example projects to practice your skills.
Use the book as a reference when you encounter difficulties in the course.

Pandas Data Manipulation Exercises

Show steps

Sharpen your Pandas skills by completing a series of data manipulation exercises, focusing on filtering, grouping, and aggregation.

Show steps

Find online resources with Pandas exercises.
Work through the exercises, focusing on common data manipulation tasks.
Compare your solutions with the provided answers or community solutions.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Help Others in Online Forums

Show steps

Reinforce your understanding by helping other students in online forums, answering questions and providing guidance.

Show steps

Find online forums related to Python and data science.
Browse the forums for questions you can answer.
Provide clear and helpful explanations to assist other learners.

Review 'Fluent Python'

Show steps

Deepen your understanding of Python's advanced features and best practices.

View Fluent Python: Clear, Concise, and Effective... on Amazon

Show steps

Read the chapters covering advanced data structures and functions.
Experiment with the code examples to understand the concepts.
Apply the techniques to improve your existing Python projects.

Create a Data Visualization Portfolio

Show steps

Showcase your data visualization skills by creating a portfolio of charts and plots using Matplotlib and Seaborn.

Show steps

Select several datasets relevant to engineering or science.
Create visualizations to explore and present the data.
Write a brief description of each visualization and its insights.
Compile your visualizations into a portfolio.

Automate Data Analysis for a Real-World Dataset

Show steps

Apply your Python skills to automate the analysis of a real-world dataset, such as sensor data or financial data.

Show steps

Choose a dataset relevant to your field of interest.
Write Python scripts to clean, analyze, and visualize the data.
Document your code and findings in a report.

Career center

Learners who complete The 10-Day Python Bootcamp for Engineers and Scientists 2025 will develop knowledge and skills that may be useful to these careers:

Data Scientist

A data scientist uses programming languages to analyze data and extract meaningful insights. This course, with its focus on practical Python training tailored for busy professionals, helps build a foundation for this career. The course's real-world applications, such as visualizing data and simulating an investment portfolio, directly align with the tasks a data scientist performs daily. Proficiency in Pandas, NumPy, and Seaborn, covered in the course, are essential for data analysis and modelling. The course also offers downloadable code snippets, quizzes, and a final project to simulate and analyze an investment portfolio’s performance to build practical skills. A data scientist benefits greatly from the applied knowledge gained in this course.

See salaries and explore the career path for Data Scientist

Data Analyst

The role of a data analyst involves collecting, processing, and performing statistical analyses of large datasets. The '10-Day Python Bootcamp' provides practical Python skills tailored for data analysis, specifically through the use of Pandas, NumPy, and Seaborn. The course's emphasis on real-world applications, such as visualizing data and analyzing investment portfolios, directly prepares you for the tasks a data analyst undertakes. The statistical methods taught in the course are useful to interpret data and identify trends. By learning to write efficient Python scripts, a data analyst can automate data processes to produce immediate, actionable insights. This course simulates real-world challenges in engineering, science, and finance.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine learning engineers develop algorithms that allow computers to learn from data. This course helps build a foundation through training in Python, Pandas, NumPy, and Seaborn, which are essential for modern machine learning. The focus on real-world applications, like simulating an investment portfolio, helps develop skills applicable to machine learning models. The course teaches you to develop predictive models and simulate real-world scenarios, a crucial skill for machine learning engineers. The ability to write efficient Python scripts, acquired through this bootcamp, will allow you to automate data processes.

See salaries and explore the career path for Machine Learning Engineer

Financial Analyst

Financial analysts use data to provide insights and recommendations for investment decisions. Considering a career in financial analysis? This course incorporates real-world applications, such as simulating and analyzing investment portfolios, which aligns perfectly with the tasks a financial analyst performs. The use of Pandas and NumPy will allow you to manipulate and analyze financial data effectively. You will learn to understand and apply statistical methods to interpret data, create professional visualizations using Matplotlib and Seaborn to present findings, and ultimately, write efficient Python scripts for data analysis, all of which are directly applicable to financial analysis. The comprehensive resources, including downloadable code snippets and quizzes, provide additional benefit.

See salaries and explore the career path for Financial Analyst

Research Scientist

Research scientists design and conduct experiments, analyze data, and report findings. This course helps those considering this career to analyze and manipulate data using Pandas and NumPy, both of which are essential for scientific research. You will learn to develop predictive models and simulate real-world scenarios. The course will also train you to write efficient Python scripts and functions for data analysis, allowing you to automate data processes to produce immediate, actionable insights. The course is designed to solve engineering, scientific, and analytical problems using Python.

See salaries and explore the career path for Research Scientist

Quantitative Analyst

Quantitative analysts, often working in finance, develop and implement mathematical models for pricing and risk management. The '10-Day Python Bootcamp' provides a hands-on approach to learning the fundamentals of Python and data analysis, specifically tailored towards practical applications. The course covers Pandas and NumPy. The course's final project, which simulates the returns of an investment portfolio and analyzes its performance, is highly relevant. Developing predictive models and automating data processes are key aspects of Python training that are useful for quantitative analysts.

See salaries and explore the career path for Quantitative Analyst

Business Intelligence Analyst

Business intelligence analysts analyze data to identify trends and insights that can improve business decision-making. The '10-Day Python Bootcamp' helps build a foundation in practical Python programming for data science. The course’s emphasis on analyzing and manipulating data using Pandas and NumPy, as well as visualizing data with Matplotlib and Seaborn, are directly relevant to this role. The ability to automate data processes and produce actionable insights is crucial for a business intelligence analyst, and this course covers precisely those aspects.

See salaries and explore the career path for Business Intelligence Analyst

Statistical Modeler

Statistical modelers create and implement statistical models to solve business problems. This course may be useful, as it helps to analyze and manipulate data using Pandas and NumPy. The course is valuable because of its focus on applying statistical methods to analyze and interpret data. The opportunity to develop predictive models and simulate real-world scenarios can directly improve the results of a statistical modeler. You will also learn how to write efficient Python scripts for data analysis.

See salaries and explore the career path for Statistical Modeler

Data Engineer

Data engineers are responsible for building and maintaining the infrastructure that allows data to be accessed and analyzed. This course may be useful as it teaches efficient Python scripts and functions for data analysis. You will learn to automate data processes to produce immediate, actionable insights. You will develop skills to solve engineering, scientific, and analytical problems using Python. By understanding the concept of modular programming and applying it to real-world problems, a career as a data engineer will be strengthened.

See salaries and explore the career path for Data Engineer

Investment Manager

Investment managers make investment decisions on behalf of clients or organizations. This course may be useful, as it teaches skills that could supplement existing knowledge. By simulating the returns of an investment portfolio and analyzing its performance, an investment manager may be able to improve their decision-making abilities. The power of Python allows the investment manager to automate data processes to produce immediate, actionable insights. The course will teach you to understand and apply statistical methods to analyze and interpret data.

See salaries and explore the career path for Investment Manager

Risk Manager

Risk managers identify and mitigate potential risks to an organization. This course may be useful, as it teaches Python skills that can be relevant. By simulating the returns of an investment portfolio and analyzing the performance, a risk manager may be able to recognize warning signals. Learning to develop predictive models and simulate real-world scenarios can help improve risk management abilities. The Python programming language is powerful in that it allows you to automate data processes to produce immediate, actionable insights.

See salaries and explore the career path for Risk Manager

Economist

Economists study the production and distribution of resources, goods, and services. This course may be useful, as knowledge of Python skills can be relevant. The bootcamp includes working with real datasets to solve complex analytical challenges. The opportunity to develop predictive models and simulate real-world scenarios can help the discovery of useful information. The Python programming language allows you to automate data processes to produce immediate, actionable insights.

See salaries and explore the career path for Economist

Statistician

Statisticians collect, analyze, and interpret numerical data to identify trends and relationships. This course may be useful in the study of statistics, as the bootcamp introduces the Python language. The course includes applying statistical methods to analyze and interpret data. You will learn to write efficient Python scripts and functions for data analysis. The bootcamp allows you to work with real datasets to solve complex analytical challenges.

See salaries and explore the career path for Statistician

Market Research Analyst

Market research analysts study consumer behavior and market trends to advise companies on their products and services. This course may be useful to learn Python skills. The bootcamp teaches skills to analyze and manipulate data using Pandas and NumPy. The course is valuable because it includes an opportunity to visualize data with Matplotlib and Seaborn. The Python programming language allows users to automate data processes to produce immediate, actionable insights.

See salaries and explore the career path for Market Research Analyst

Actuary

Actuaries analyze risk and uncertainty to help businesses and clients develop policies that minimize risk. This course may be useful, as it teaches Python skills. Included in the course's syllabus is a simulation of synthetic portfolio investment returns. The actuary role fits with the bootcamp's opportunity to apply skills to real-life business cases and projects. The bootcamp includes knowledge of how to work with real datasets to solve complex analytical challenges.

See salaries and explore the career path for Actuary

The 10-Day Python Bootcamp for Engineers and Scientists 2025

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Practical python for engineers and scientists

Activities

Career center

Reading list

Share

Similar courses