How data science is a new solution in the world


What is data science is all about?

In the simplest term, data science is a mixture of data mining and computer science.

Data is continuously created since the first computer was invented. Initially, companies relied on Data Mining, which simply meant generating new information. But in today's environment, websites and apps are not just brochures, notifications boards, or online media tools. They are now a way for millions of users to meet and share experiences. Users now interact with websites, create content, comment, like, search, etc., all of which creates an enormous amount of data that companies are looking to exploit to add more values ​​to products.

In 2010, the term "big data" was coined for such a large amount of data around us, and paved the way for the emergence of "data science", which could extract insights from large, unstructured data sets to support business. Data science is now and in the future related to data collection, analysis and modeling. However, the most important part is its applications like "machine learning", which made it possible to make machines more accurate through a data-based approach, and deep learning, which has become a category of "machine learning" that transforms our daily lives and the way we test things .

Data scientists jobs in industries

  • Collection: The most important task of the data scientist is to collect data from various sources.
  • Exploration and transformation: Structured and unstructured data must be cleaned and transformed to eliminate anomalies in the data.
  • Analytics: This is the primary part of the job. Based on the converted data, data scientists try to understand metrics like what users are doing or searching for and why they leave, then offer a logical solution like what can be done to engage more users and give them a better experience.
  • Learning and improvement: A / B testing allows data scientists to experiment with different models and verify which ones work best.
  • Acting and visualization: The whole task is not about creating advanced models, but keeping things simple in a way that customers and others can understand.
  • Artificial Intelligence and Machine Learning: This is the last part of the task as data scientists use complex algorithms and machine learning principles to improve the performance of machines in a particular task.

What can you learn from online training in data science?

Data science is about using statistics, creating symbols, developing models, and ultimately solving problems. To achieve this goal, the training focuses on providing in-depth training for students with the following tools:

  • Hadoop, MapReduce and Spark are used for data manipulation.
  • The SQL programming language is used in programming and designing the database system.
  • Python is the most powerful language in machine learning.
  • R and Excel are useful for analyzes and data modeling.
  • Other important tools are SAS, Minitab, and XL Miner.

Online training covers all the important concepts mentioned above, as well as giving students the opportunity to work on live projects. Employment assistance is also available to help students find jobs in leading companies after the completion of the training.


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