Let us go into the details and explore the learning path of a Data Scientist in a systematic order.
The learning path of a data scientist is well planned and structured. It is divided into three steps, which the aspirants will be taught accordingly in given time duration. The three steps involved in the learning path of Data Science Course in Bangalore are listed down below, they are as follows:
- Command and skills over Excel (Microsoft): Present under the name of Microsoft, Excel can be described as a spreadsheet. It is used for the purpose of calculations, and for the storage of financial data.
- Skills in SAS (software suite): This is a type of software suite. It is utilized for the purpose of analysis related to statistical aspects. It is capable of reading data that belong to databases, and spreadsheets.
- Skills in R (programming language): This programming language is used for the purpose of statistical computing along with graphics.
- Python (common programming language): It is considered to be the most common type of programming language with high-level efficiency. It is concerned with a general purpose.
- Pig / Hive (tools included in Hadoop): Pig as well as Hive are considered to be the major components of Hadoop. They are used for the management of the big data as well as for the analysis.
- Command and skills over Access (Microsoft): Microsoft Access is a system that is used for the purpose of database management. It is a system software under the name of Microsoft that provides development tools and a graphical user interface.
The second step is inclusive of the following concepts:
- Basic Data Cleaning and statistics: No data scientist can start work without knowing the basic concepts that are to be applied. This holds true in the case of subjects like Mathematics and statistics, as well as Data Cleaning.
- Predictive Analysis / Modeling and Analysis of data: The major role that a Data scientist plays is centered on data. This data is then to be analyzed by him, and amounted to a readable format for the audience.
- Tableau and Qlikview: These tools are used for the better understanding of acquired data.
- Hadoop and Hive: Hadoop is considered to be one of the high speed tools along Spark, while Hive is a tool useful for the analysis as well as for managing the big data.
- Spark SQL and Spark: Spark is said to be a high speed cluster-computing system that beats Big Data Hadoop by a 100 times. It is concerned with a general purpose, while also distributing data amid the cluster.
The third and final step of the learning process includes the following:
Unstructured Data: Data that does not possess a determinate organization or definite model system is called as unstructured data.
Python: Using this object oriented programming language one can perform numeric and scientific computing, and browser automation. Development of sites or web development can also be done with the help of Python. It can also be used in desktop applications.
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