Tools You Must Know To Become A Data Scientist.
Teachnook Data Science

Tools You Must Know To Become A Data Scientist.

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In this article, we will cover the most essential tools you must know to become a data scientist.

Data Science is a vast field. Many people confuse Data Science as Data Analytics or Data Science is only about AI and ML but, that's not true.

Data Science is Beyond AI and ML it includes statistics, specialized programming languages, mathematics and of course, Artificial intelligence and machine learning and much more.

Tools You Must Know To Become A Data Scientist.

Tableau and Power BI

Power BI and Tableau help data scientists by showing data in pictures, making it easier to find important stuff. They also let people work together and tell stories with data. But for really tricky jobs, data scientists use special tools like Python and R.

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Python And R

Python and R are essential in data science. They clean and analyze data, perform statistics, build machine-learning models, and create visualizations. They handle big data, integrate various sources, and offer interactive notebooks. Their communities and resources support customized analysis, making them crucial for data scientists.

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MatLab

Matlab helps data scientists by offering tools for data manipulation, statistical analysis, machine learning, and visualization. Its functions and toolboxes streamline tasks like preprocessing, modelling, and exploring data, making it valuable for data scientists' research and decision-making processes.

Tensor Flow

TensorFlow is pivotal in data science, powering machine learning and deep learning tasks. It simplifies creating neural networks for tasks like image recognition, natural language processing, and predictive modelling. Its flexibility, libraries, and GPU support accelerate experimentation and model deployment, enhancing data scientists' capabilities.


Question for the reader- Which language is used in data science?

Scroll down to know the answer :)


Juypter

Jupyter enhances data science by providing interactive notebooks for code, analysis, and visualization. It supports Python, R, and more, enabling data scientists to document workflows, share insights, and experiment collaboratively. Jupyter's versatility accelerates data exploration and model development, fostering efficient and transparent data-driven research.

There are still many Tools like SQL, D3.js, Apache Spark, Apache Hadoop, Rapid Miner and many more


Data Science is one of the most interesting and challenging careers with high-paying jobs. All you need is, to have the hunger to learn and implement new things.


Answer - The Language used in Data Science is Ruby, Python etc


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Teachnook wishes every data Scientist or upcoming data scientist a bright career.

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by - Sohan Sukte.





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