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Python For Science & Engineering - The Bootcamp
Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 17.80 GB | Duration: 13h 7m
Master applied Python for Science and Engineering - Essential Skills and Hands-On Projects!
What you'll learn
Master Python from Fundamentals to Advanced Concepts.
Solve Engineering Problems through Analysis and Modelling.
Manipulate, Analyse, and Visualize data efficiently.
Excel in Critical Libraries for Scientifical Computation.
Unlock the Power of Symbolic Mathematics with SymPy.
Develop Professional Data Visualization Skills with Matplotlib.
Utilize Python for Efficient Numerical Analysis.
Requirements
No programming Experience needed. Everything will be shared along the way.
Open to learners from all backgrounds and Disciplines.
No paid software required, just a computer having access to internet (and a little dedication! )
Description
It is finally time you unlock your full professional potential with Python! •In this comprehensive bootcamp, The Python for Science and Engineering you'll embark on a structured and concise learning journey designed to equip you with practical Python skills tailored specifically for science and engineering applications.Who is this course thought by? •Guided by an instructor who has 5+ years experience in Python and Engineering that understands the challenges of being a student, the course covers fundamental and advanced Python concepts, presented in a clear, logical and intuitive manner. What will this course teach you? •You'll learn to navigate through powerful and crucial libraries in the scientifical realm:Handle Multi-dimensional Arrays and perform Numerical Computation with NumPy.Develop Professional Data Visualization Skills with Matplotlib.Unlock the Power of Symbolic Mathematics with SymPy.But also learn how to master Python when applied in Engineering, by learning how to:Master the fundamentals of python programming while adopting good writing habits.Define and Model, Solve and Simulate a Differential Equation that governs a physical phenomena.The course is crafted to avoid unnecessary complexity, offering focused content that is both current and relevant. With an optimal course length, you'll efficiently gain the skills needed to boost your resume and excel in your academic or professional pursuits.Enroll today to unlock your full potential and prepare yourself for success in the STEM field! •
Overview
Section 1: Welcome to the Python for Engineers Course!
Lecture 1 Course Introduction - An Overview!
Lecture 2 Installing Python and Visual Studio Code
Lecture 3 Installing Jupyter Notebook
Section 2: Fundamentals of Python Programming
Lecture 4 Variables - Numerical Variables (Int, Float, Complex)
Lecture 5 Variables - Textual Variables (Strings)
Lecture 6 Variables - Booleans
Lecture 7 Variables - Additional Features
Lecture 8 User I/O - User Output
Lecture 9 User I/O - Formated Output
Lecture 10 User I/O - User Input
Lecture 11 Operators & Expressions - Arithmetical Operations
Lecture 12 Operators & Expressions - Comparaison Operations
Lecture 13 Operators & Expressions - Logical Operations
Lecture 14 Operators & Expressions - Assignment Operations
Lecture 15 Conditional Statements (If, Elif, Else)
Lecture 16 Loop Statements - For Loop
Lecture 17 Loop Statements - While Loop
Lecture 18 Control Flow Statement (break, continue, pass)
Section 3: Functions & Modular Programming
Lecture 19 Functions - Overview
Lecture 20 Functions - Proper Documentation
Lecture 21 Modular programming - A practical example with a Planets!
Lecture 22 Modular Programming - Built-In Functions
Lecture 23 Create Mathematical functions in Python
Lecture 24 Additionnal Features on Functions
Section 4: Data Structures
Lecture 25 Lists - Overview
Lecture 26 Lists - A practical example with the BMI !
Lecture 27 Lists - Multi-Dimensional Lists (1D, 2D and n-D)
Lecture 28 Tuples - Overview
Lecture 29 Strings - Overview
Lecture 30 Dictionaries - Overview
Lecture 31 Dictionaries - A practical example with Sensors!
Lecture 32 Sets - Overview
Lecture 33 List Comprehension in Python
Section 5: Object Oriented Programming
Lecture 34 Classes & Objects - Overview
Lecture 35 Classes & Objects - A practical example with Car Accelerations!
Lecture 36 Classes & Objects - Class Inheritance
Section 6: Errors and Exceptions
Lecture 37 Errors and Exceptions in Python
Section 7: File Handling and I/O Operations
Lecture 38 File Operations - Overview & File Writing
Lecture 39 File Operations - File Reading
Lecture 40 File Operations - File Appending
Lecture 41 File Operations - Additional Informations & the 'with' keyword
Lecture 42 Storing & Retrieving Data - From a Text file (.txt)
Lecture 43 Storing & Retrieving Data - From a JSON file (.json)
Lecture 44 Storing & Retrieving Data - From a Pickle file (.pickle)
Lecture 45 Handling CSV files (.csv) in Python
Section 8: Handling Multi-Dimensional Arrays with NumPy
Lecture 46 Getting Started with NumPy!
Lecture 47 Creating your first NumPy-Arrays
Lecture 48 Indexing and Slicing NumPy-Arrays
Lecture 49 Operating NumPy-Arrays
Lecture 50 Managing NumPy-Arrays
Section 9: Data Visualization & Plotting with Matplotlib
Lecture 51 Getting Started with Matplotlib!
Lecture 52 Make Professional Looking Plots & Graphs
Lecture 53 Draw Multiple Plots & Layouts
Lecture 54 Plotting 3D Mathematical Functions
Section 10: Symbolic Mathematics & Expressions with SymPy
Lecture 55 Write your First Symbolic Expression with SymPy!
Lecture 56 Creating Symbolic Variables
Lecture 57 Solving Symbolic Equations
Lecture 58 Advanced Symbolic Expressions
Lecture 59 Creating & Handling Symbolic Matrices
Section 11: Solving Differential Equations (DE) with Python
Lecture 60 A Theoretical Overview on DE
Lecture 61 Solving Differential Equations with Sympy!
Lecture 62 Solving Differential Equations numerically using `solve_ivp`!
Beginners who have never programmed before and seek an engaging adventure.,Regular Programmers transitioning to Python.,Intermediate Python Programmers seeking to elevate their skills by applying them in the scientific field.,Career-Driven Engineers aiming to enhance their opportunities.,PhD students and researchers aiming to apply Python in their research field, bringing illumination to the unknown.
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