Can I Learn Data Science in 3 Months?

What do you Need?

To start learning data science, you must have the following capabilities to get a positive result in 3 months:

• You must have some technical knowledge like a degree in Stat. Math etc.
• You also need to know about coding schemes and programming languages
• You need to have work experience in the environment of data science
• It would help if you had an idea that who databases store databases
• The course of data science:

If you want to learn data science, you should know the syllabus of data science. Five divisions of data science are discussed below:

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• Linear Algebra &Statistics:

  This aspect of data science is crucial. Recall your lessons from algebra and statistics if you have, as these topics are used in both data science and machine learning.

• Machine Learning:

  The algorithms of machine learning have proved accurate in data analysis in the real-world environment..

• Production Systems:

  Understanding an organization's data processing cycle is what this is all about. Additionally, it will improve your data science abilities.

• Panda, Numpy, and Matplotlib:

  These are the programming languages that comprise codes and algorithms that you can also use for your projects.

• Python:

  Using your familiarity with Python programming, you will learn data science more rapidly in this course.

How to Learn Data Science in 3 Months?

A data science professional applies mathematical and statistical methods to data in order to conduct analysis. The most important individual in every organisation is the data scientist. You must be knowledgeable in the field of data science to succeed as a data scientist. If you follow the recommendations in this post, you can learn data science in three months.

• Begin with data analysis
• Get advanced in machine learning
• End up with using the real-world tools recommended by data scientists

These resources are available for your project. You may learn more about these tools in this manner. You can learn data science in three months if you read this article and adhere to the guidelines it contains.

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• Begin with Data Analysis

  To become a data scientist, you first need to become a data analyst. If your basics of data analysis are strong, then you can learn data science efficiently. Some institutes offer a degree in data science. First, to become a successful data analyst, you need to know the concepts of data analysis. You need to know the following concepts of data science

• Statistics and Mathematics

  This tool is mostly used by data scientists to acquire data analysis competence. Online lectures, articles, and videos may teach you about HIVE and PIG. As was already said, you need to be familiar with data analysis ideas in order to understand data science. You must thus be familiar with these technologies in order to learn data analysis.

• Knowledge of Python

  If you know Python as this is taught in the degree of computer science, you will be good at data analysis because Python is the basic language used by data scientists. So you must know Python. For learning Python, you can attend some online courses or listen to online lectures.

• A simple Idea of HIVE

  Data scientists mostly use this tool to get the expertise of data analysis. You can get knowledge of HIVE and PIG from online videos, articles, and lectures. As discussed earlier, to learn data science, you must know the concepts of data analysis. So you are required to have know-how about these tools as it's part of learning data analysis.

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• Data Gathering

  To pursuance the knowledge of data analysis, you should have the skills that how data will be gathered. Use some types of techniques to gather data correctly. If data is not hoarded accurately, then you may fail to get the required result.

• MS Excel

  Simply assuming that this tool has a spreadsheet for data entry does not provide it any capability. You don't need to learn Python if your data sets are tiny. You may use Microsoft Excel to analyse your data.

• Visualization of Data

  This technique will be preferable if your data sets are too long. Using data visualization tools, you can get an idea and make or break the data sets. Acquire advanced skills in machine learning.

  You should begin machine learning if, after the first month, you are proficient at data analysis. Machine learning makes use of artificial intelligence to obtain data and statistics. You must possess the following machine learning skills.

  • Fundamentals of computer
  • Skills in programming
  • Know-how of possibility and statistics
  • Skills of data calculation

  Attending various online lectures and tutorials about machine learning and its facets can help you develop these abilities.

• Tools of Data Science

  In the third month, when you are good at data analysis and machine learning, you are ready to start using the tools of a real-world environment recommended by expert data scientists. Some most common tools are as follows:

• Tableau:

  The main purpose of this tool is to create data visualisations. With the help of this application, you may create graphs and charts that effectively convey data.

• SAS:

  It is a programming language tool named SAS. It is specifically used for the operations of statistics.

• Gplot2:

  This tool was created specifically for use with the R programming language. It offers sophisticated data visualisation capabilities.