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Yes, of course, you need to know the Mathematics and particularly Linear Algebra, Theory of probability and a good amount on differential & integral calculus

But what matters here is on each individual - if you want to practice data science all through your career you have to learn that depth of Mathematics.

Maths is the base for data. You should know it. You can excel in data science by having strong understanding of statistical concepts. I think you should elaborate on your question ‘lot of mathematics’. What do you mean by it? Is it to do with your scores on maths exams in school, is it do with gaps in understanding some specific topics,

It is good to have a solid foundation of mathematics covering Statistics , probability , Linear Algebra and Calculus. The role of a data scientist is to work on the underlying data and come up with analysis to help managers take decisions. Also, data science is a prelude / pre -requisite for building Machine Learning models. Today, we have a number of tools and technologies that make the entire life cycle of data science and Machine Learning fairly simple and straight forward. Any one with basic understanding of high school maths can also work on building a career in data science provided he / she commits to build skills over time.

So don’t worry if you don’t consider yourself an expert in maths, you can still aspire to become a data scientist. But be ready to work on building on your foundational knowledge and develop an appreciation / intuition of the underlying algorithms and models.

Most of the data analysis work revolves around the following : 1.Identification and treatment of missing data 2. Standardization of data structure 3. Data visualization to identify any patterns (like correlation across the data features) 4. Working with the IT team to address issues in the data. A lot of time is spent on ensuring the preparation of accurate , quality assured, and reconciled data and these activities take up significant amount of effort (and patience too).

Try out google colab and work on basic exploratory data analysis. You will get a lot of materials and help online. There are good tutorials on you tube too.

If you have a learning mindset, the right attitude and are willing to set aside 2 hours a day for 3 months, I am sure you will be ready to take up a job as a data scientist in an entry level role.

Not really. If you have a grasp of probability and statistics and have a basic knowledge of coding in any language , you should be able to do this course and career successfully

Yes, of course, you need to know the Mathematics and particularly Linear Algebra, Theory of probability and a good amount on differential & integral calculus

But what matters here is on each individual - if you want to practice data science all through your career you have to learn that depth of Mathematics.

Maths is the base for data. You should know it. You can excel in data science by having strong understanding of statistical concepts. I think you should elaborate on your question ‘lot of mathematics’. What do you mean by it? Is it to do with your scores on maths exams in school, is it do with gaps in understanding some specific topics,

It is good to have a solid foundation of mathematics covering Statistics , probability , Linear Algebra and Calculus. The role of a data scientist is to work on the underlying data and come up with analysis to help managers take decisions. Also, data science is a prelude / pre -requisite for building Machine Learning models. Today, we have a number of tools and technologies that make the entire life cycle of data science and Machine Learning fairly simple and straight forward. Any one with basic understanding of high school maths can also work on building a career in data science provided he / she commits to build skills over time.

So don’t worry if you don’t consider yourself an expert in maths, you can still aspire to become a data scientist. But be ready to work on building on your foundational knowledge and develop an appreciation / intuition of the underlying algorithms and models.

Most of the data analysis work revolves around the following : 1.Identification and treatment of missing data 2. Standardization of data structure 3. Data visualization to identify any patterns (like correlation across the data features) 4. Working with the IT team to address issues in the data. A lot of time is spent on ensuring the preparation of accurate , quality assured, and reconciled data and these activities take up significant amount of effort (and patience too).

Try out google colab and work on basic exploratory data analysis. You will get a lot of materials and help online. There are good tutorials on you tube too.

If you have a learning mindset, the right attitude and are willing to set aside 2 hours a day for 3 months, I am sure you will be ready to take up a job as a data scientist in an entry level role.

Not really. If you have a grasp of probability and statistics and have a basic knowledge of coding in any language , you should be able to do this course and career successfully