What qualifications you should have to go to a data science course?

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What qualifications you should have to go to a data science course?


Data Science is one of the fastest-growing industries that is taking the world by storm. Many professionals in the IT industry are actively changing the course of their careers to become a Data Scientist. However, becoming a Data Scientist is not that easy though. Yes, you do need a knack of playing with numbers and applying theories and proofs to a number of real-life situations. However, that is not enough and one needs to possess a number of other skills as well to become a successful data scientist. This article has tried to list out all the pre-requisites that one needs before becoming a Data Scientist.

Prerequisites for a Data Scientist

The fundamental knowledge plays an important role in the professions of a Data Scientist. Even before joining a data science course, one needs to have a lot of fundamental knowledge of the following areas:

  1. Reporting
  2. Business Intelligence
  3. Data Analytics
  4. Extract Transform Load (ETL) and concerned tools
  5. Database Basics
  6. Relational Algebra
  7. Binary Tree
  8. Hash Functions
  9. Linear Algebra Functions
  10. Matrices
  11. Good knowledge of programming languages used for Machine Learning and Data Science, i.e., R or Python
  12. Basic Knowledge of Machine Learning and common knowledge pertaining to it such as why is ML used and what are the restrictions of ML. You should also be aware of the various divisions of Machine Learning algorithms, i.e., Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Though all of this will be taught in detail in any Data Science Course, one should be well-acquainted with all the Supervised and Unsupervised Algorithms such as Clustering, K Nearest Neighbor, Random Forest, Decision Tree, Logistic Regression and Linear Regression.
  13. One must also be clear about their knowledge of Statistics and the various theorems that are commonly used in Data Science. Some of the principles and theorems are Skewness, Cumulative Distribution Tables, Random Variables, Bayes Theorem, Probability Theory, Percentiles and Outliers, Exploratory Data Analysis, and Descriptive Statistics, such as Mean, Mode, Gradient, etc.
  14. Deep Learning has also been creating ripples in Data Science. Basic knowledge of the same will also be helpful.

It is pretty clear from the above that a particular degree or certificate is not required to get enrolled in a Data Science Course. You just need to be interested in the course and basic knowledge about all the subjects mentioned above. It is basically the interest and the wish to learn something new that counts. 

Data Science is a great field and it is growing every month, every year. Establishing oneself in this field might turn out to be a great decision. Hence, you should go ahead and take this leap of faith and live a fulfilling life later.

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We hope that this article was good enough to give you some basic details about Data Science Courses. If you find the contents of this article good enough, you should enroll yourself in a Data Science as soon as possible and share this article with your friends who have similar interests.

Reference Link- https://www.excelr.com/blog/data-science/regression/understanding-logistic-regression-using-r

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