What is the suitable Programming Language to become a Data Scientist?

Question

70% of data scientist and data analysts use Python as their primary coding language. It is the most used programming language that help data analyst to increase their skill-set.

Can anyone suggest the programming language to become a data scientist?

Comments

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Answer 1

SQL is a good programming language to become a data scientist.

The best programming language for a data analyst is Structured Query Language (SQL) because of its ease of communicating with databases.

However, Python is a better option for other main data analysis functions, such as analyzing, manipulating, cleaning, and visualizing data.

Much of the world's data is stored in databases. SQL (Structured Query Language) is a domain-specific language that allows programmers to communicate with, edit and extract data from databases.

Having a working knowledge of databases and SQL is a must if you want to become a data scientist.

There isn't a single “best” programming language for data science, but Python is also a powerful tool with syntax that's easy to learn as a beginner.

This makes it a great choice for beginners and experienced data scientists alike.

C++ is not used widely for data science because most data scientists don't have a Computer Science background.

Hence, complex languages that require a fundamental knowledge of programming aren't their strongest suit.

However, a lot of data scientists still prefer using C++ for data science over any other language.

Data scientists are a new breed of analytical data expert who have the technical skills to solve complex problems – and the curiosity to explore what problems need to be solved.

They're part mathematician, part computer scientist and part trend-spotter.

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains.

Because of the often technical requirements for Data Science jobs, it can be more challenging to learn than other fields in technology.

Getting a firm handle on such a wide variety of languages and applications does present a rather steep learning curve.

Answer 2

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Answer 3

The specific technologies and programming languages they specialize in may vary from company to company. Some common technologies and programming languages that software development companies often specialize in include:

1.           Programming Languages: Java, Python, C#, JavaScript, Ruby, PHP, Swift, Kotlin, etc.

2.           Web Technologies: HTML, CSS, JavaScript, Angular, React, Vue.js, Node.js, ASP.NET, Django, Flask, etc.

3.           Mobile App Development: iOS (Swift, Objective-C), Android (Java, Kotlin), React Native, Flutter, Xamarin, etc.

4.           Database Technologies: MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, Firebase, etc.

5.           Cloud Technologies: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), etc.

6.           Frameworks and Libraries: .NET, Spring, Django, Laravel, Express.js, Flask, Ruby on Rails, Vue.js, React.js, AngularJS, etc.

7.           DevOps and Deployment: Docker, Kubernetes, Jenkins, Git, CI/CD pipelines, AWS Elastic Beanstalk, Heroku, etc.

8.           Machine Learning and Data Science: Python (NumPy, Pandas, TensorFlow, scikit-learn), R, PyTorch, Keras, etc.

9.           IoT (Internet of Things): Arduino, Raspberry Pi, MQTT, Node-RED, AWS IoT, etc.

Remember, the specific technologies and programming languages a software development service provider specializes in will depend on their team's expertise and the requirements of the projects they have worked on in the past.

Answer 4

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