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Path of Data Analysis
The ultimate pack with all our Data Analysis courses with R and Python to turn you into a well-paid Data Scientist. Includes upcoming courses and updates and improvements to current ones
Nieves
Intermediate Foundations of Mathematics for Machine Learning: master the logic behind the algorithm
This course dives into the mathematical pillars that support machine learning, ideal for those who already know the basics and want to move toward a more technical and applied understanding. You'll learn linear algebra, multivariable calculus, inferential statistics, advanced probability, information theory, and optimization, all with practical examples in Python, TensorFlow, and PyTorch. The approach is progressive, with visualizations, guided exercises, and real-world applications in data science and artificial intelligence.
Jorge
The perfect bridge between basics and advanced
After covering the fundamentals, this course helped me take the next step without blowing my mind. It's super rewarding to see how everything starts to make more sense and how you feel more capable of understanding complex problems. A necessary step that I really enjoyed.
Samuel
recommended
This is the course I needed to understand everything I was seeing, now formulas don't scare me, I feel much more confident
Javi
A step further
I liked it because it doesn't stay in the basics, but it doesn't become overwhelming either. It helps you connect the dots and understand where all that information comes from that we use today for machines to learn. I left feeling like I have much more solid tools for my current challenges
Santiago
Key concepts explained in a really straightforward way.
Giovanni
The perfect bridge to specialization
With the basics under my belt, this intermediate level was exactly what I needed to level up
Nicolás
Very complete and practical
María
It helped me understand the basics of everything
I always thought math was complicated, but this course makes it look super accessible. Now I understand the models much better
Rocío
I loved this continuation of the math fundamentals course
Sara
10/10, excellent
Jackeline
The Math Behind the Models
This course helped me understand what's really going on inside an algorithm. I learned about linear algebra, calculus, and applied probability without feeling overwhelmed
Angel
Fundamentos Intermedios de Matemáticas para Machine Learning
This course is designed for those who want to strengthen their mathematical foundation before diving into complex Machine Learning models. Through a structured approach, we cover the mathematical pillars that underpin machine learning algorithms: linear algebra, multivariable calculus, probability and statistics.
Rosa
I liked that concepts like entropy, activation functions, and gradients are explained with clarity and context.
Silvana
The middle ground I needed
Intermediate Mathematics for Machine Learning was perfect for connecting what I already knew with what I needed to move forward. The course is clear, not overwhelming, and with examples that really help you understand.
Maria del Mar
Mathematics made easy
Juan Gabriel is a wizard with these topics. Whether it's quantum nuclear physics, he'll explain it so a 5-year-old can understand it. Highly recommended course, no doubt about it
Gabriela
My next level in ML
After mastering the fundamentals, this course took me to the next level. I dived deep into more advanced mathematical concepts and how they apply to Machine Learning. It was a challenge, but it was worth it.
Carlos
Diving Deeper into Theory and Practice
After completing the fundamentals, this course helped me take the next step. Learning probability, statistics, and information theory in a practical way with Python has been incredibly useful. It's given me a better understanding of Machine Learning models and how the algorithms really work behind the scenes.
Yvonne
You need to handle the math
so you can get a better understanding of the ML and AI courses, I love this series for that reason
Caty
Excellent course
Great for continuing to strengthen Intermediate Foundations of Mathematics in Machine Learning, and let's go for more. I'll keep applying it
Carlos
Fundamentals of Mathematics for ML Part 2
This course is wonderful. Well explained and very well documented. Congratulations and I highly recommend it
danison
Mathematics for ML: The key I was missing
This course gave me the mathematical foundations I needed for Machine Learning. With practical exercises in NumPy, TensorFlow and PyTorch, I now understand probability and statistics much better. Highly recommended!
Joiser
Explains its application in complex models clearly
delves into key topics like advanced algebra, optimization and matrix theory