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Computer Science and Engineering in AI & Data Science

B.Tech Computer Science & Engineering in Artificial Intelligence and Data Science  is four year undergraduate course designed to make the professional technically sound to extract information and insights from large datasets and also make future predictions and smarter decisions.

Artificial Intelligence

AI is the study of how to make computers perform tasks that humans consider difficult through the creation of intelligent agents. The study of AI began in the 1950s, and it has improved dramatically over time with better statistical methods and greater computing power.

AI is now used for all sorts of things, such as intelligent opponents in video games, accurate medical diagnosis, speech commands on mobile phones, and keeping email inboxes clear of spam. People who use AI often want it to perform repetitive tasks that take a lot of time for a person to do, or to solve problems which seem almost impossible to solve with a calculator. For example, AI can be used to:

  • Intelligently guess the products that someone may want to buy
  • count cells in a microscope picture
  • find the optimum number of taxis that a city needs
  • read the license plates of cars in a video
  • Predict the quantity of ingredients a restaurant needs to order to minimize waste, but not run out of stock.

Data Science basically is an amalgamation of mathematics, programming, statistics and design which are applied in order to successfully manage digital data collection.

The main 3 components involved in data science are organizing, packaging and delivering data. Overall, it is a multidisciplinary blend of data inference, algorithm development and technology in order to solve analytically complex problems. The advent of Big Data and Machine Learning has further fuelled the growth of Data Science. Today, Data Science is being used across all parallels of various industries, including business, healthcare, finance, and education.

The most common use case of Data Science that has crept into your everyday life is a Recommendation Engine. Whenever you’re on Amazon or Netflix, do you see those personalized recommendations saying “Things you may like”? Well, that’s a classic example of Data Science algorithms tracking and understanding user search and buying patterns and then customized recommendation lists.

Model building process in Data Science

The Scope of Jobs with Artificial Intelligence and Datascience

A mixture of many fields of science that deals in formulas, patterns, statistics, math and business give birth to one of the most demanding subjects known as data science.

Data science draws inspiration and its basis mainly from the fields of statistics and business intelligence and combines computer science and other modern technologies like artificial intelligence and machine learning to make smarter decisions.The data is analysed and the results of the analysis are used to draw conclusions and make decisions based on the supporting data.

In a world that is increasingly becoming a digital space, organizations deal with zettabytes and yottabytes of structured and unstructured data every day. Evolving technologies have enabled cost savings and smarter storage spaces to store critical data.

Currently, in the industry, there is a huge need for skilled and certified Data Scientists. They are among the highest-paid professionals in the IT industry. According to Forbes, ‘the best job is now  of a Data Scientist with an average annual salary of Rs 7 Lakh. Only a few people have the capability to process it and derive valuable insights out of it.

Job Roles

  • Business Analytics Professional

A business analytics professional has the skills to make use of the information from the data to generate insights about the business. To be a data focused business analytics professional, you must know the technical components related to managing and manipulating data.

Recruiters: Walmart, Conduent, Genpact etc.

  • Business Intelligence Professional

A Business Intelligence Professional analyse the past trends using Data Visualization tools like Tableau, Power BI etc to develop and implement business strategies. They also monitor all the performance metrics of the company and provide insight to the respective department.

Recruiters: Accenture, ZS Associates, Sun Pharma etc.

  • Data Scientist

Data Scientists help build complicated data models and simulations in a Big Data environment. Focusing more on math and statistics, these data scientists have a particular interest in reading statistics and building & deploying machine learning models.

Recruiters: HDFC Bank, Amdocs, Oyo etc.

  • Big Data Analysts

Job responsibilities of a Big Data Analyst include collaborating with data scientists and data architects to ensure streamlined implementation of services and executing big data processes.

Recruiters: Novartis, Allerin Tech, Amazon AWS etc.

Due to the abundance of data in all the marketing campaign., Analytics enable the marketing professionals to evaluate the success of their marketing initiatives. This is accomplished by measuring performance.