We are living the digital age where Data is the new electricity. In fact, over the last decade need for Data Analysis has risen exponentially. A Data Science has fast become most sought after expertise and at Cyber Radar University you will find the right tools and training to become a Data Sceintist.
You might be thinking, why should you enrol in a Data Science course? As you know, with the amount of data that is being generated and the evolution in the field of Analytics, it has become essential for industries to be able to understand and analyse date to arrive at correct decisions.
How does Facebook automatically tag the face of an individual? How does a website like Netflix recommend videos to its subscribers? How do banks identify which customers are likely to be the most loyal, and which are likely to leave for a competitor? Have you ever wondered how such predictions can be made? Well, the answer is simple it’s all magic of Data Science. Data Science can be defined as a blend of mathematics, business acumen, tools, algorithms and machine learning techniques that can be of major use in the formation of big business decisions.
Data Science online course at CRU you will gain expertise in dealing with both structured as well as unstructured data. It’s an amalgamation of statistical tools and business acumen and knowledge.
By the end of the course, you will be able to:
Develop skills for real-career growth
Learn from experts active in their field
Learn by working on real-world problem
Receive 24x7 active support
Data Scientists are in high demand in virtually every job-sector–not just in technology. In order to break into this high-paying, in-demand job market; you need the right credentials and training. Cyber Radar University Data Science takes an all-round approach to training with equal emphasis on academic and industry experience. . We at CRU also put emphasis on training in Python which has become a required skill for 46-percent of jobs in Data Science.
AI, Data Science and machine learning all work in tandem. Machine learning is the field of data science that feeds computers huge amounts of data so they can learn to make insightful decisions similar to the way that humans do.
For example, most humans learn as children what a flower is without thinking about it. However, the human brain achieves that learning through experience—by collecting data—on which specific features are associated with flowers.
A machine can do the same thing with human help. As humans feed the machine massive quantities of data, it can learn that various petals, stems and other features are all connected to flowers.
In other words, humans feed training data or raw data to the machine, so it can learn all of the data's associated features. Then, if the training was successful, testing with new data should reveal that the machine can distinguish the features it learned. If not, it needs more or better training.