What Data Science is all about?

In the simplest term, Data Science is the combination of Data Mining and Computer Science.

Data is being generated continuously ever since the first computer was invented. Initially, companies depended on Data Mining which simply meant generating new information. But in today's environment, websites and apps are not just pamphlets, or notice boards or online informing tools. They are now a medium for millions of users to come together and share their experience. Users are now interacting with the websites, creating content, commenting, liking, researching etc. And all this is resulting in the creation of a huge amount of data which the companies are looking forward to exploiting in order to add more values ​​to their products.

In 2010, the term Big Data was coined for such a large amount of data present around us, and it paved the way for the rise of Data Science, which can draw insights from the massive unstructured datasets to support the businesses. Data Science, in the present and coming times, is about collecting, analyzing, and modeling of data. The most important part, however, is its applications such a Machine Learning, which has made it possible to make machines more accurate through a data-driven approach, and Deep Learning, which has become a class of Machine Learning which is transforming our everyday life and the way we experience things.

Jobs of Data Scientists in Industries

  • Collection: The most important job of a Data Scientist is to collect the data from various sources.
  • Exploration and Transformation: The structured and unstructured data has to be cleansed and transformed in order to get rid of anomalies present in the data.
  • Analytics: This is the core part of the job. Based on transformed data, the Data Scientists try to understand the metrics like what the users are doing or looking at and why they are leaving, and then provide a logical solution like what can be done to engage more users and give them a better experience.
  • Learning and Optimization: A / B testing allows Data Scientists to perform experiments on various models and check what models work the best.
  • Representation and Visualization: The whole task is not about creating advanced models, but to keep things simple in a way that customers and others can understand.
  • Artificial Intelligence and Machine Learning: It is the last part of the task where Data Scientists use complex algorithms and machine learning principles to improve the performance of machines on a particular task.

What Can You Learn From Online Training on Data Science?

Data Science is all about using statistics, creating codes, developing models, and eventually, solving problems. To achieve this goal, the training focuses on giving students in-depth training of the following tools:

  • Hadoop, MapReduce and Spark are used for the purpose of handling data.
  • SQL programming language is used in programming and designing a database system.
  • Python is the most powerful language in Machine learning.
  • R and Excel are helpful in analytics and data modeling.
  • Other important tools are SAS, Minitab and XL Miner.

The online training covers all the important concepts mentioned above, along with giving students the opportunity to work on live projects. Placement assistance is also available to help students find jobs at leading companies after the training is completed.