Data Science course (11)

Top data science tools used in Bangalore

by with No Comment Data Science

Data science is a field that requires the practice of scientific methods, algorithms, systems, and processes for extracting insights and knowledge from both unstructured and structured data. It is an interdisciplinary and revolutionary field that combines statistics, mathematics, information science, computer science, and domain expertise for uncovering hidden patterns, insights, and correlations from data. 

What are data science tools?

 Data science tools and technologies are software applications enabling users to extract, analyze, and process huge volumes of data and information. These important tools and technologies help analyze hidden patterns, build predictive models, and uncover valuable insights from raw data. These tools are utilized for various purposes and tasks like determining customer segments, forecasting market trends, and customer churn.  

In this article, you will read about the top ten data science tools that are used widely in different industries 

  1. Python:

An interpreted, general-purpose, high-level programming language is Python. It is a simple-to-learn and understandable language that offers a wide variety of frameworks, tools, and libraries that have immense use in machine learning and data science projects. In addition, Python includes several libraries and packages for data analysis, manipulation, machine learning, data visualization, etcetera, making this data science tool a perfect choice for data analysts and scientists. It includes strong libraries used for image processing, language processing, deep learning, etc. Python is used in data analytics and data science projects because it is a universal programming language and has a strong user and developer community. 

  1. Apache Spark:

Developed in 2009, Apache spark is an important data analytics and processing tool. This open-source distributed computing platform was originally developed at the University of California and enabled professionals to process huge data sets. It is a fast in-memory data processing engine designed for data science professionals to facilitate ease of use. It offers different libraries for streaming machine learning, graph processing, and SQL. It Includes high-level APIs in Python, R, Scala, and Java. 

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  1. TensorFlow:

There are diverse applications of this data science tool. This open-source machine learning library is used to make data analytics and data science projects successful. TensorFlow offers powerful tools, libraries, and technologies that assist data analysis, predictive analytics, and data visualization. TensorFlow is a common choice for data engineers and data scientists because this tool has high scalability and flexibility. The TensorFlow application includes natural language processing and image processing. It comprises algorithms that are used for supervised learning, deep learning, and unsupervised learning.

  1. Hadoop:

Hadoop helps in storing massive amounts of data within a distributed space. This data science tool enables distributed processing of data with the help of the MapReduce programming model. In other words, it can run continuously even in case of failure of a specific node in the cluster.

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  1. Tableau:

This is a powerful and commonly used data visualization tool used for creating interactive dashboards and other visuals. Tableau enables data science professionals to analyze data and information quickly, develop visuals, and collaborate. This data science tool has immense use in the business sector for analyzing data and making informed business decisions. It is used for exploring as well as understanding data and information in a better way. 

  1. Apache Hadoop:

This is a powerful data science tool that comprises of distributed computing platform that enables data processing as well as data analytics. It is an open-source program that comes with distributed processing of massive amounts of data across different computer systems. Hadoop uses a distributed file system to facilitate data storage amounts and MapReduce to facilitate data processing. Apache Hadoop is used for analyzing huge sets of data from distinct sources. Some applications of Apache Hadoop in the field of data science are machine learning, web indexing, and data mining.

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  1. AWS:

AW stands for Amazon Web Services, a popular cloud-based computing platform that facilitates data computing, storage, networking, and many other services. It enables users to access computing resources like virtual machines, databases, and storage. This is a secure, reliable, and cost-effective cloud-based platform that helps business to manage their tasks. It enables users to scale up or down their infrastructure and make payments for the resources that they are using. There is a wide range of services and tools that AWS comprises to enable users to develop, deploy as well as manage applications within the cloud platform.

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  1. Excel

Excel is a popular data science tool that helps in managing different tasks like data processing, data calculation, and visualization. It is used mostly for analyzing data, so it is an efficient and highly used data science analytical tool. It has different filters, tables, slicers, and formulas. Excel is a highly popular data science tool that is used for spreadsheet calculation and data visualization. 

  1. SAS

 A closed-source software designed mainly for performing analytical tasks is SAS. It supports different data format types and is known as the fourth generation of programming languages, as the cost of SAS is quite high. Therefore, big and large companies mainly use this data science tool. SAS is an efficient and trustable closed-source tool that provides different analytical libraries as well as devices to users for organizing data. 

  1. RapidMiner 

Rapid miner is a powerful and widely used integrated data science tool developed mainly for performing predictive analysis, advanced analytics such as text analytics, data mining, visual analytics, and machine learning without requiring any programming. This data science platform can work with any data source, such as Microsoft SQL, IBM, Excel, Access, Terra data, Sybase, MySQL, Dbase, SPSS, Oracle, etc. This powerful tool helps generate analytics based on real-life data conversion settings. 

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Conclusion:

Data and science professionals must extract, organize and analyze huge data sets to derive meaningful insights. As they have to examine and handle different data types, they work with various tools and technologies. The most common data science tools beginners use are SQL, R, and Python. In the present technological world, data is the new oil. Because of the rising demand and importance of data science and data analytics by all businesses, organizations and companies’ recruiters are hiring more data science professionals. It can be overwhelming for data science beginners as they have to deal with a variety of tools and technologies. The above-mentioned list will help both budding and experienced data scientists choose and get trained on the right tool. 

Data Science Training in Bangalore

Top 3 Data Science Courses for Beginners

by Data Science

Looking to pursue your career as a data scientist? Right? Data science is diverse in that knowledge and its practical applications have separate significance. Beginners don’t know what to do and how to do everything at the start. They don’t even know data science to go through multiple topics. However, to help you understand data science, we are going to discuss top courses.
Do you have a passion for data science? If yes, this course is going to be much easy to understand and implement in our practical life. As we know, data science has dominated our lives through technological devices. So, it will be important to start your career in data science. Here are the following courses to start. Learn more about Data Science Course in Pune

Data science specialization:

One of the top courses for data scientists is Data Science Specialization. You can find this course on one of the most popular teaching sites Coursera. Through the use of this course, you can understand the applications of data science using R programming. However, knowledge of Algebra can be helpful to you in this regard. Here are some of its main features that you need to understand.
You will practically examine and use R programming to clean and analyze your data.
To collect your data, you will get an easy approach to GitHub to apprehend how it works.
You will able to publish your data science projects.
Perform regression analysis with the help of building regression models.
If you are looking for deep knowledge and the contribution of programming to data science, you can go through this course. With the price of $49 per month, you can have certificates as well.

 

Introduction to Data Science

Another top-level course with high ratings from hundreds of students in Introduction to Data Science. This course is accredited and provides you with valuable certificates to use for future jobs. The instructor is going to empower you with live lectures and ask questions instantly. Isn’t it a cool offer for you? Here are some main points for you to learn in this course.
You will get a complete understanding of the basic problems and techniques to solve them with the help of data science.
How to use and when to supervised and unsupervised learning methods of statistics.
Ability to understand Python use with the data science and multiple other aspects of data science.
The price for this course is $750. For more details Data Science Course in Chennai

 

CS109 Data Science

The amazing feature of this course is its provider Harvard without any cost. However, you can’t get free certificates but it is a masterpiece to learn. If you are looking for some knowledge, it is the best match for you. Here are some of its main features, you are going to learn.
You are going to analyze data, collect it, and understand it after cleaning.
Effective data science projects and building of the multiple aspects of a project are significant in this process.
Learning of Bayes Theorem and learning of regression models will help you understand data science deeply.

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Data Science

Data Science for Beginners in Bangalore

by Data Science

Data Science for beginners

Data Science is a trending technology and the Data Scientist job is considered the sexiest job of this modern era. As more attention is drawn towards, many aspirants want to learn Data Science and make a career in this field. But how to learn Data Science?. This article will give you an idea of how to start Information Science, it is a roadmap for beginners.

There are a plethora of resources available on the internet, but beginners might get perplexed with the abundant material available on the net and don’t have any idea how to start. This article will showcase the steps to learn Data Science Training in Pune.

What is Data Science?

It is the technology used to extract valuable insights from enormous amounts of data that is used to make data-driven decisions by businesses. 

Prerequisites:

Learning Information Science is not a difficult task. If you have prior knowledge of Maths and Statistics, then it would be easy for you to start Data Science. All you need is time, extra effort, and practice. Here is a list of few topics that you have to learn to become proficient in Data Scientist.

Topics

Python 

Python is a prominent and popular programming language across the world. It is considered a powerful tool for Data Scientist Course. Another language R is also very important. Python is easy to understand and it has varied applications. If you can learn the fundamentals of Python programming language, it would be quite beneficial to you.

Maths

Mathematics plays a very critical role in Data Science. However, you don’t need to be an expert in Maths, but basic knowledge is essential. When the data is analyzed using Python, the data is converted into matrix forms. So, if you have knowledge of these matrixes then it will be easy for you. You need to have basic knowledge of Calculus, Linear Algebra, Probability, and Statistics. These concepts you can learn from various online sites for free.

Python Libraries

There are various Python Libraries that are used to make complicated tasks of Data Science simple. If you are good at Python, then let’s know about Python Libraries.

Numpy

The first Python library that you have to learn is Numpy. It is a numerical library and does numerical operations. Numpy library is used to work with Linear Algebra. Linear Algebra is part of Maths that deals with Matrices.

Pandas

After you are equipped with Numpy, then start exploring Pandas. Pandas is a Python library that is used for quick data analysis, data pre-processing, and data cleaning. Pandas library helps to load and clean data sets and make data frames.

Matplotlib and Seaborn

The data is represented in graphical format with several charts and plots. This is known as Data Visualization. For this, Python provides two brilliant libraries called Matplotlib and Seaborn. Matplotlib is a comprehensive library used for creating static, animated, and interactive visualizations. It offers many inbuilt graphs and plots that make the process easy.

Seaborn works like Matplotlib and has various numerous capabilities. 

Machine Learning algorithms

Machine Learning algorithms are helpful in analyzing and extracting valuable information. Machine learning is the scientific method that provides computer programs the ability to learn from previous experience and exhibit tasks.

There are numerous Machine Learning algorithms. No need to learn all of them, only a few which are important, you need to focus. They are Linear Regression, Logistic regression, Support Vector Machine (SVM), Random forests, Neural networks. K-nearest neighbors, etc. These algorithms can be easily executed by the Scikit-learn library. This library has many inbuilt programs that help Machine Learning algorithms to be implemented easily. Visit here more details Data Science Training in Chennai

Python does have other  libraries like Keras, TensorFlow for Deep Learning purposes. 

It is a vast topic and has many subfields. If you want to learn in-depth about Data Science, then it is better for you to get trained at any reputed training institute that offers a Data Science Courses in Bangalore. If you can get Certifications, it will add value to your portfolio and helps you in grabbing high paid jobs in top-notch companies.

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Navigate To:

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Phone: 1800-212-654321

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