Course Highlights

Eduonix Learning Solutions via Udemy
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★★★★☆ 4.2 (1,243 Ratings)

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Artificial Intelligence has been progressing at a rapid pace over the last decade. Since there had been promising developments that have encouraging applications in our daily life, the probable bright future is not far enough. The innovations in the medical industry, automotive industry, Education industry, and Agriculture based on AI have produced an urge in developers to generate AI and ML programs. These Algorithms require sufficient knowledge of mathematics as it has proved to be the cornerstone in building a strong foundational base of programming.

This course is designed in coordination with the experts in their respective fields to develop an optimal structure of the course which has a breakdown that could adhere to the easy-to-follow approach. Three core mathematical theories including Linear Algebra, Multivariate Calculus, and Probability Theory are incorporated into this course. In the first section of linear algebra topics such as Scalars, vectors, matrices, Eigenvalues, etc. are included. In the second section, the subsections such as Differentiation, Integration, convex optimization, etc. are added. The last section of probability theory includes Elements of probability, distributions, variance, expectation, etc. Embark on a journey to master linear algebra with the best online courses available, designed to provide a solid foundation in mathematical principles.

This course is a perfect match for candidates that wish to learn powerful mathematical tools that are deemed necessary for AI and Machine learning.

TTC Course Analysis | Effectiveness Score | Pros & Cons | Learner’s Reviews | Learner’s Recommendations

TTC Course Analysis:

Following are the results of comprehensive analysis of “Mathematical Foundation For Machine Learning and AI” online course by our team of experts.

TTC Rating
233 Reviews

3.0

TakeThisCourse Sentiment Analysis Results:

In order to facilitate our learners with real user experience, we performed sentiment analysis and text mining techniques that generates following results:

TTC analyzed a total of 233 reviews for this online course.
The analysis indicates that around 60% reviews were positive while around 40% of reviews had negative sentiment.
Eduonix Learning Solutions online course received a total score of 3.0 out of 5, based on user opinions related to 4 effectiveness factors including content, engagement, quality practice and career benefit.

Course Review Mathematical Foundation For Machine Learning and AI Barchart

TTC Course Effectiveness:

Online Course Effectiveness Score (Learn More)
Content	Engagement	Practice	Career Benefit
3.8 / 5.0 ★★★★☆ 96 Reviews	3.9 / 5.0 ★★★★☆ 117 Reviews	4.1 / 5.0 ★★★★☆ 29 Reviews	3.9 / 5.0 ★★★★☆ 14 Reviews

Based on learner reviews we believe;

This course provides an overview of the mathematical models used in the coding of AI or ML programs. This provides a great insight into the most important aspects of mathematics considered obligatory.
The instructor has great command over the subject and was able to answer the problems that could possibly arise in the minds of the candidates prior to being raised by them.
The design of the course is such that it covers brief explanations of the topics rather than diving into the deep concepts considering the time constraints.
There is room for improvement in the course as practice problems were lacking. The candidates believe that their learning potential could be exploited more had there been more practice material.

Course Review Mathematical Foundation For Machine Learning and AI - SA Visualization

Pros & Cons:

Pros:

Brief description and explanation of the course topics.
Expert and engaging instructor.
Precise course content.
Targeted audience.
Real-world examples.
Professional presentation.

Cons:

Lack of practice material.
No in-depth explanations of the topics.

What Learners Are Saying About this Course:

This section contains feedback that has been given by online learners about this course. Note that we have divided these reviews based on our main points mentioned below;

Content:

The course content of the course contains an overview and brief descriptions of the topics. It provides a particular path as to how one should proceed in order to get detailed knowledge. (Nihar D, ★★★★☆)
This course can prove to be the cornerstone for any advanced-level ML course. It provides fairly good in-depth illustrations of mathematic models used in AI. The content is well designed keeping in consideration the audience which is a beginner level one. (Joe R, ★★★★★)
This course provides valuable content that helps the participants in strengthening their foundational concepts. This course provides complete basic information which can aid the students in acquiring a deep knowledge of ML and AI in the future. (Jainesh J H, ★★★★☆)
I was looking for the exact course that could cover the basics of all the topics that carry high significance. The course content covers all the possible important topics with great relevance. Apart from this, the topic related to camera-based forensics left me in awe. It was beyond my expectations. I really admire your efforts Eduonix. (Angelina G, ★★★★★)

Engagement:

The course is covered in a great manner. This course is moved along at a perfect pace. The engaging nature of this course is an attraction for the participants. The course material offers a brief summary of various aspects of mathematics involved in ML. (Shawn I, ★★★★★)
Some lectures were quite entertaining as the instructor was able to keep the audience engaged. The examples presented during the lectures were well explained. (Piotr S, ★★★★☆)
The instructor was able to keep my attention all the time as he did not hurry on to the topics. The probability section was the highlight of the whole course. (Development S, ★★★★★)
The instructor was very proactive in terms of interacting with the candidates which made this course very engaging. He efficiently addressed the queries that I was about to put up. (Rishi, ★★★★★)

Quality Practice:

I really admire the effort made by the team of the course. The quizzes were competitive enough to challenge your skills and learning. (Steven M, ★★★★★)
I assumed that the course would contain practice problems and worksheets. The lectures were theoretical along with examples also, but they lacked the quality practice which is required for an efficient understanding of the subject. (Vineet V, ★☆☆☆☆)

Learner’s Career Benefits:

I planned to enroll in an ML course which is a requirement for me to proceed in my career. But, prior to that, I took this course and I do not regret taking the course. This course some powerful knowledge that helped me build cemented foundational knowledge. (Andrea M, ★★★★★)
This course is a must and should be considered as a pre-requisite in pursuing a career in Artificial intelligence or Machine learning. This course helps polish your mathematical skills which are necessary for a successful career in AI or ML. (Arohi B, ★★★★★)

If you’re interested in advancing your career, consider the AWS Machine Learning Certification as a valuable credential to showcase your expertise.

Learner’s Suggestions/Recommendations:

The content is very brief at times. So the content could be enriched with more useful information and knowledge.
The section that incorporated probability should be focused on a bit more. More useful exercises in this section could have been added.
The course instructor should include more examples to provide a better understanding of the subject.
The sound quality needs to be improved to keep the participants stay focused.
Laplace and exponential distributions should be explained in depth with help of strong examples.

Is this Course worth taking?

Conclusively, this course is worth taking especially for candidates willing to star their career in AI or ML. Those professionals that are new in the fields of artificial intelligence and machine learning can also put their considerations into taking this course. Empower yourself to explore the exciting realms of AI and ML with freely available resources carefully selected to facilitate your learning journey and foster your passion for innovation. The course content does not contain deep knowledge of the topics such as probability, distributions, Eigenvectors, etc. It provides a summarized concept of the course topics. Considering the importance of these mathematical techniques in AI, you should not pursue your career in AI or ML without strengthening the fundamental concepts. This course should be considered a compulsory pre-requisite to another course in AI or ML. The course instructor is an expert in the field and possesses rich knowledge of the subject.

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Course Review: Mathematical Foundation For Machine Learning and AI