So you’ve decided to step into the arena of Data Science? Here’s all what you want to know before pursuing your dream. The study of Data Science course in bangalore demands a strong grasp over concepts requiring mathematical understanding, such as algebra, calculus, trigonometry, distributions, probabilities, linear algebra.

Some of the topics falling under the category of machine learning are listed below:

• Geolocation handling
• Time series
• Clustering
• Regression
• Inference
• Tests
• Neural Networks
• Models Comparison
• Computer vision
• Deep learning
• Natural language processing
• Random Forests
• CART
• Feature selection
• Map/Reduce

The next step that follows the understanding of these concepts, is to bring them into fruition. To accomplish this, requires mastery over certain IT tools. They are listed as follows:

• Software
• Programming

The skills falling under the Software category are Spark SQL and SPSS.

Spark: Spark is one of the SQL’s or structured query languages. It is an open-sourced engine that is specifically designed for dealing with the analytics and processing of the data on a large-scale basis. It is a module designed for the purpose of a well organized and put together data processing.

SPSS: Having been schemed out for both interactive as well as non-interactive bases, SPPS (Statistical Package for the Social Science) is capable of the manipulation and analysis of extremely complex data together with simplistic instructions.

Java: Java is a programming language of general purpose related to the computer, it has a good grounding in the many concepts that are required for the study of Data Science.

R: R is defined as a scripting language. Similar to Spark, it is open-sourced. However, it is used for the visualization of data and also for the purpose of predictive analysis. This language also ministers to the development of statistical software and analysis of data.

SAS:  SAS stands for Statistical Analysis System. It is defined as a software suite, developed for the purpose of predictive analysis, business intelligence, multivariate analysis, advanced analytics, and data management. Its job includes alteration, management and retrieval of the data from a number of sources in addition to performing statistical analysis on it.

Python: This programming language is directed at being object-oriented. Although often considered similar to PERL, it rose to fame due to its clear readability and syntax. It is mainly intended for desktop applications as well as for the purpose of web development.

The job of a Data Scientist also requires the knowledge of the following:

• Web Languages
• Data visualization
• Databases

Semantic Web

Semantic Web: It acts as a protraction of the WWC / W3C (World Wide Consortium). It ministers in the creation of data stores on the web. Its job includes assigning instructions that the machine can follow later on.

NOSQL: These are defined as distributional or non-relational databases. These databases help in the storage as well as retrieval of data. It provides real time data access along with a high performance.

SQL: SQL or Structured query languages are used for the purpose of retrieval of data, same as its non-relational counterpart. It is also used for updating data in a database.

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360DigiTMG – Data Science, Data Scientist Course Training in Bangalore
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