Mathematics is a broad subject, but there are specific subfields that are heavily employed in data science: calculus and linear algebra – and this is what the 365 Data Science program covers. However, in order to thrive in data science, you must have all the numerical tools so you can eventually understand the most complicated of machine learning algorithms.
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In this section, we will discuss the basics of linear algebra – scalars, vectors, matrices, and tensors. We will dive into the terminology and the different operations that one can perform, like transposing, addition, subtraction, multiplication, etc. We look into types of matrices like identity matrix and inverse matrix. We finish off this part with Eigen values and Eigen Vectors.
This course is part of Module 1 of the 365 Data Science Program. The complete training consists of four modules, each building up on your knowledge from the previous one. Whereas the other three modules are designed to improve upon your technical skillset, Module 1 is designed to help you create a strong foundation for your data science career. You will understand the core principles of probability, statistics, and mathematics; you will also learn how to visualize your data.See All Modules
Real-life project and data. Solve them on your own computer as you would in the office.
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The course is in-depth and is delivered at a steady pace with eye catching visuals. The instructors go through all the basics really well. They try not to over-simplify the material, you get a good sense аof how deep Data Science is in the course. Great job!!!
This course is amazing! After watching the video carefully and doing all the exercises, I am even capable of having discussions with Machine learning major Master’s students! High standard course with reasonable pricing.
Very clear and in-depth explanation of data science and how all the inter-related concepts apply in real life business environment. Absolutely great for beginners! Best data science course I have come across so far!
I would highly recommend the course to any beginner who wants to venture into the world of Data Science. The concepts are very well explained and there is an emphasis on practical application which really helps create a better understanding of the concepts.