How to learn Data Science

Introduction:-

Data Science: Data science is a broad field that refers to the collective processes, theories, concepts, tools and technologies that enable the review, analysis and extraction of valuable knowledge and information from raw data. It is organized towards helping individuals and organizations make better decisions from stored, consumed and managed data.

“Data Science is formerly known as datalogy”.

What does it mean for you?

It means that the skills you acquire and improve are way more important than the actual information you learn. It also means that “learning data science” is not about learning data science.

It’s about:

· Improving your coding skills.

· Improving your business skills.

· Improving your mathematical/statistical skills.

· Improving your data visualization, presentation, communication and soft skills.

Statistics: A branch of mathematics that deals with the collection, classification, analysis, and interpretation of numerical facts or data, and that, by use of mathematical theories of probability, imposes order and regularity on aggregates of more or less desperate elements.

Artificial Intelligence: The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Description:

To Learn Data Science it is must to acquire knowledge of the given points:

1) Learn basic mathematics and statistics required for data science

2) Develop a basic understanding of machine learning algorithms.

3) For intermediate level we need to learn R, Python, Big data, etc. types of algorithms.

Diagram:

Ø Statistical Science: Statistical Science is used to process complex problems the real world so that Data Scientists and Analysts can look for meaningful trends and changes in Data. In simple words, Statistics can be used to derive meaningful insights from data by performing mathematical computations on it.

Difference between population and Sampling in statistics:

Ø R Programming: R is a GNU-licensed free software programming language and software environment primarily used for statistical computing as well as for graphics. It is widely used by statisticians and data miners for creating or developing statistical and data analysis tools and software.

· How “R programming” is used in data science?

R is actually a programming environment and language made specifically for graphical applications and statistical computations. It is a leading tool for machine learning, statistics, and data analysis. By using R we can create objects, functions, and packages. It is not only statistic package is an open source.

Ø Python: Python is an interpreted language, that means to it runs code one instruction at a time. Python can perform data visualization, data analysis and data manipulation; NumPy and Pandas are some of the libraries used for manipulation. Python serves various powerful libraries for machine learning and scientific computations.

Ø NoSQL: A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. NoSQL database are increasingly used in big data and real-time web applications. These systems are sometimes called “Not only SQL” to emphasize that they may support SQL-like query languages, or sit alongside SQL databases in polyglot persistent architectures.

Ø Big Data Analytics: It allows data scientists and various other users to evaluate large volumes of transactions data and other data sources that traditional business systems would be unable to tackle. These technologies make up an open-source software framework that’s used to process huge data sets over clustered systems.

Future scope of data science:

Data Science comprises of different disciplines which include Statistics, Machine Learning, Data Analysis, Computer Science, and Research. So, there is a lot of scope for Data Science career everywhere.

Conclusion:

· Data is the newest priceless commodity.

· Data science is the study of data.

· Data scientists allow companies to make smarter business decisions.

· Data scientist has an important position in the company.

I enjoyed a lot to make a blog on a very important topic of “How to learn data science”.

Thank you…