Master Math by Coding in Python
What you'll learn
- Most important: Confidence in learning math!
- Algebra (1, 2)
- Linear algebra
- Python programming
- Python libraries including sympy, numpy, matplotlib, scipy
- Formatting beautiful equations in LaTeX
- Data visualization
- Integrating Python, Markdown, and LaTeX
- Just the course, a computer, and a positive attitude!
- No Python experience necessary - I take you through everything!
- Jupyter IPython notebook - free to use! Either local installation or use online
You need to learn mathematics
Math is at the heart of all advances in modern computing, including data science, AI (artificial intelligence), deep learning, generative AI, machine learning, statistics, video games, and on and on...
If you want to study or work in these fields, or if you're just curious to learn more about these technical topics, you need to have a grasp of mathematics.
You can learn a lot of math with a bit of coding!
Many people don't know that Python is a really powerful tool for learning math. Sure, you can use Python as a simple calculator, but did you know that Python can help you learn more advanced topics in algebra, calculus, and matrix analysis? That's exactly what you'll learn in this course. Python isn't just a coding language; it's a gateway to mastering math.
This course is a perfect supplement to your school/university math course, or for your post-school return to mathematics.
Let me guess what you are thinking:
"But I don’t know Python!" That’s okay! This course is aimed at complete beginners; I take you through every step of the code. You don't need to know anything about Python, although it's useful if you already have some programming experience.
"But I’m not good at math!" You will be amazed at how much better you can learn math by using Python as a tool to help with your courses or your independent study. And that's exactly the point of this course: Python programming as a tool to learn mathematics. This course is designed to be the perfect addition to any other math course or textbook that you are going through. It's also a great way to get started on your adventures into data science, deep learning, and AI.
What do you get in this course?
Over 37 hours of instruction that includes Python coding, visualization, loops, variables, and functions.
Important Python libraries for data science and mathematics, including numpy, sympy, scipy, and matplotlib.
LOTS of practical exercises! Each video has at least one hands-on coding/math exercise (and you'll get to watch me solve those exercises). And each section ends with "bug hunts" where you get to find and fix my math-coding errors!
That warm, fuzzy feeling of confidence that you can combine the skills from this course to improve your understanding of mathematics.
A big-picture overview of beginner and advanced mathematics, from solving for "x" to computing integrals to finding eigenvalues. If you are only just beginning your adventures in maths, then this course will show you what you have to look forward to!
This course is right for you if you are:
In middle/high school, university, or are returning to math as an independent learner.
A data professional who wants to brush up on math and Python skills.
A complete beginner to Python.
A student of data science, machine learning, or AI who needs to improve their mathematics knowledge to understand algorithms.
Looking to transition from another field into AI-related fields like deep learning.
Already proficient with math "in theory" and want to learn how to translate math formulas and concepts into computer code.
Bored and looking for a fun intellectual challenge.
With over 33 hours of teaching, plus student exercises, challenges and an active course Q&A forum (get a response to any question within 48 hours!), this course gives you everything you need to succeed in your maths course or independent adventures in learning math.
All the code that appears in the videos is also included for download. You can code along as you watch the videos, or download the code and use it directly.
This course covers the following topics:
Introduction to Sympy
Introduction to LaTeX (to print beautiful equations!)
Graphing conic sections
Who is your teacher?
I am Mike X Cohen, a former neuroscience professor (I left that job to focus full-time on teaching online). I'm a bestselling and highly rated instructor on Udemy. I've taught over 250,000 students the foundations of scientific programming, data analysis, data science, and applied mathematics, and I've written several textbooks on programming and data analyses.
I worked really hard to make this course a great learning experience for you. Check out what some of my students have said about my other courses:
** ‘Best teacher ever. I am a psychologist and I didn’t have mathematical training as an undergrad, but the books and lectures of Dr. Cohen have been life saving’
** ‘What I REALLY like about Mike's style is that not only clear and direct, but he mixes in appropriate amounts of foreshadowing … to make it easier for me to connect the dots.’
** ‘Mike X Cohen's courses are by far the best ones I've done in Udemy.’
What you should do right now:
Watch the free preview videos.
Check out the reviews of this course.
Joining this course is risk-free: If you change your mind after enrolling, Udemy offers a 30 day money back guarantee.
Who this course is for:
- Maths students looking to use computers as a learning tool
- Developers keen to improve their math skills
- Independent learners returning to maths
- Programmers who want to use their coding skills to explore mathematics
Best-selling Udemy instructor Rob Percival wants to revolutionize the way people learn to code by making it simple, logical, fun and, above all, accessible. But as just one man, Rob couldn’t create all the courses his students - more than half a million of them - wanted.
That’s why Rob created Codestars. Together, the instructors that make up the Codestars team create courses on all the topics that students want to learn in the way that students want to learn them: courses that are well-structured, super interactive, and easy to understand. Codestars wants to make it as easy as possible for learners of all ages and levels to build functional websites and apps.
I am a full-time educator and writer, and former professor of neuroscience. I "retired" from that position so I could focus my time and energy creating high-quality educational material just for you.
I have 20 years of experience teaching programming, data analysis, signal processing, statistics, linear algebra, and experiment design. I've taught undergraduate students, PhD candidates, postdoctoral researchers, and full professors. I have taught in "traditional" university courses, special week-long intensive courses, and Nobel prize-winning research labs. I have >100 hours of online lectures on neuroscience data analysis that you can find on my website and youtube channel. And I've written several technical books about these topics with a few more on the way.
I'm not trying to show off -- I'm trying to convince you that you've come to the right place to maximize your learning from an instructor who has spent two decades refining and perfecting his teaching style.
Over 200,000 students have watched over 15,000,000 minutes of my courses. Come find out why!
I have several free courses that you can enroll in. Try them out! You got nothing to lose ;)
By popular request, here are suggested course progressions for various educational goals:
MATLAB programming: MATLAB onramp; Master MATLAB; Image Processing
Python programming: Master Python programming by solving scientific projects; Master Math by Coding in Python
Applied linear algebra: Complete Linear Algebra; Dimension Reduction
Signal processing: Understand the Fourier Transform; Generate and visualize data; Signal Processing; Neural signal processing