data science training in bangalore

Posted by digitaltucr on January 3rd, 2019

Having become an accomplished term in a span of over three decades, data, science is defined as an independent discipline. It is known to expand the field of statistics, thus incorporating advances in computing with the input of data.

It is a blend of algorithms, their development, technology as well as the data interface. Therefore, we can conclude that it is a blend of three major kinds of skills, namely Business acumen, Technology (Hacking skills) and expertise in the field of mathematics. Concepts such as Hadoop, data exploration, hypothesis testing, Spark and regression models are explored in this field.

Being a data scientist is all about being speculative. Asking queries, embarking on discoveries and lastly learning new data - if you’ve got these aspects in you, you have a higher chance of becoming a successful data scientist.

The concept of Data Science and its Importance

 

o   Data requires flexibility, it is in turn used to study aspects such as inferences, complex behaviors, and trends. It is also used to generate insights that help in better understanding of information, thus acting as a boon to the business marketers allowing them to make smarter choices.

o   Personalized recommendations and messages directed to you based on your input. Market giants such as Netflix and Amazon implement this to get a better analysis of their audience and lure more customers in. Music platforms like Spotify follow suit by providing music recommendations based on the existing data.

o   Target Corporation works on identifying the unique shopping patterns or behaviors within their segments. This helps them determine as to what drives the user's interest.

o   Traffic suggestions issued by Google maps.

o   E-commerce recommendations are seen in sites like Netflix, Myntra, Amazon, Snapdeal, Flipkart, etc.

o   Recognition of images on social media giants like Facebook, etc.

What is Data Science Capable of?

Data Science is used for the following purposes:

Airlines:

v  For prediction of analytics, and formation of analytics model for tracking delays in schedule, as in the case of flight delays or rescheduling of the flights.

v  For the purpose of planning routes: whether to schedule direct or connecting flights.

v  Deciding which standard / class of plane to purchase that gives better performance.

Logistics:

Logistic Companies such as FedEx rely on the data science and data analytics model to cut costs, or for the optimization of roads for better operational efficiency.

 

v  For determining the best routes possible to reach the destination.

v  For deciding on the best suited time for delivery to the destination.

v  For singling out the best mode of transportation to reach the destination of delivery.

Often time’s people cannot differentiate between an analyst and a data scientist, and confuse one for the other.

A data scientists' responsibilities include - Data exploration, analysis, Data product engineering, Advanced Algorithms learning, and data insight. Whereas data insight, data exploration, analysis, and business administration that includes domain-specific responsibility is required for becoming an analyst. Furthermore, equity research and campaign management are the skills needed in the financial and marketing analyst field.

Resource Box

Data Science is a go-to career for people that consider themselves as deep thinkers and are patient enough to complete the puzzle piece by piece. Data science course will assist you in accelerating your career in the field of Data Science.

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