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Machine Learning & Data Science Foundations Masterclass

The Theoretical and Practical Foundations of Machine Learning. Master Matrices, Linear Algebra, and Tensors in Python
4.5
4.5/5
(1,574 reviews)
80,217 students
Created by Jon Krohn

8.8

CourseMarks Score®

9.9

Freshness

8.1

Feedback

7.9

Content

Platform: Udemy
Price: $11.99
Video: 6h 15m
Language: English
Next start: On Demand

Top Machine Learning courses:

Detailed Analysis

CourseMarks Score®

8.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.9 / 10
This course was last updated on 3/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.1 / 10
We analyzed factors such as the rating (4.5/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

7.9 / 10
Video Score: 8.5 / 10
The course includes 6h 15m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 15 minutes of 454 Machine Learning courses on Udemy.
Detail Score: 9.6 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

To be a good data scientist, you need to know how to use data science and machine learning libraries and algorithms, such as Scikit-learn, TensorFlow and PyTorch, to solve whatever problem you have at hand.
To be an excellent data scientist, you need to know how those libraries and algorithms work under the hood.
This is where our “Machine Learning & Data Science Foundations Masterclass” comes in. Led by deep learning guru Dr. Jon Krohn, the Machine Learning Foundations series provides a firm grasp of the underlying mathematics, such as linear algebra, tensors, and eigenvectors, that operate behind the most important Python libraries, machine learning models, and data science algorithms.
The first step in your journey into becoming an excellent data scientist is broken down as follows:
•Section 1: Linear Algebra Data Structures
•Section 2: Tensor Operations
•Section 3: Matrix Properties
•Section 4: Eigenvectors and Eigenvalues
While the above sections constitute a standalone course all on their own, we’re not stopping there! We have finished filming additional, intermediate-level linear algebra content (Section 5 on Matrix Operations for Machine Learning) as well as all of the calculus content (Sections 6 through 10). It will all be edited and uploaded in early 2021. We will release all remaining sections of the comprehensive Machine Learning Foundations series into the course as quickly as we can. Ultimately, the course will cover not only linear algebra and calculus, but also probability, statistics, algorithms, data structures, and optimization. Enrollment now includes free, unlimited access to all of this future course content — over 25 hours in total.
Throughout each of the sections, you’ll find plenty of hands-on assignments, Python code demos, and practical exercises to get your math game up to speed!
Are you ready to become an outstanding data scientist? See you in the classroom.

Requirements

• All code demos will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples.Familiarity with secondary school-level mathematics will make the class easier to follow along with. If you are comfortable dealing with quantitative information — such as understanding charts and rearranging simple equations — then you should be well-prepared to follow along with all of the mathematics.

You will learn

✓ Understand the fundamentals of linear algebra, a ubiquitous approach for solving for unknowns within high-dimensional spaces.
✓ Manipulate tensors using the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch
✓ Possess an in-depth understanding of matrices, including their properties, key classes, and critical ML operations
✓ Develop a geometric intuition of what’s going on beneath the hood of ML and deep learning algorithms.
✓ Be able to more intimately grasp the details of cutting-edge machine learning papers

This course is for

• You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms, and would now like to understand the fundamentals underlying the abstractions, enabling you to expand your capabilities
• You’re a software developer who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems
• You’re a data scientist who would like to reinforce your understanding of the subjects at the core of your professional discipline
• You’re a data analyst or A.I. enthusiast who would like to become a data scientist or data/ML engineer, and so you’re keen to deeply understand the field you’re entering from the ground up (very wise of you!)

How much does the Machine Learning & Data Science Foundations Masterclass course cost? Is it worth it?

The course costs $11.99. And currently there is a 87% discount on the original price of the course, which was $94.99. So you save $83 if you enroll the course now.
The average price is $17.2 of 454 Machine Learning courses. So this course is 30% cheaper than the average Machine Learning course on Udemy.

Does the Machine Learning & Data Science Foundations Masterclass course have a money back guarantee or refund policy?

YES, Machine Learning & Data Science Foundations Masterclass has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Machine Learning & Data Science Foundations Masterclass course, but there is a $83 discount from the original price ($94.99). So the current price is just $11.99.

Who is the instructor? Is Jon Krohn a SCAM or a TRUSTED instructor?

Jon Krohn has created 1 courses that got 1,574 reviews which are generally positive. Jon Krohn has taught 80 students and received a 4.5 average review out of 1,574 reviews. Depending on the information available, Jon Krohn is a TRUSTED instructor.

More info about the instructor, Jon Krohn

Chief Data Scientist and #1 Bestselling Author
Jon Krohn is Chief Data Scientist at the machine learning company untapt. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University and New York University, as well as online via O’Reilly and the SuperDataScience podcast. He holds a PhD from Oxford and has been publishing on machine learning in leading academic journals since 2010; his papers have been cited over a thousand times.

8.8

CourseMarks Score®

9.9

Freshness

8.1

Feedback

7.9

Content

Platform: Udemy
Price: $11.99
Video: 6h 15m
Language: English
Next start: On Demand

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