Data scientists find and interpret rich data sources and are skilled in mathematics, statistics, and computer science. Students electing this option will take courses and do research in mathematics, computer science, and information systems.
Mathematics,Calculus,Linear Algebra,Simple neural networks, Principal component analysis,Multivariate calculus,Eigen values& eigen vectors etc.
Fundamentals of Statistics, Random Variables,Distributions,Normal Distribution,Central limit theorem etc.
Statistical tools, and the programming languages are the backbone when we need to represent, model, manipulate & think about large quantities of data.
R programming language, developed by Ross Ihaka and Robert Gentleman in 1993, is widely used for applications related to data science. R provides support for an extensive suite of statistical methods, inference techniques, machine learning algorithms,statistics, time series analysis, data analytics, graphical plots to list a few. These features make it a great language for data exploration and investigation.
Python programming has various frameworks & features to expand in web application development, graphical user interfaces, statistics ,data analysis, data visualization etc. Python is extensively used by many organizations for various purposes.Python is a must-learn programming language for the professionals working in the Data Science domain.
Statistics, Estimation Methods,Confidence Interval,Hypotheses Test,Regression Analysis,Time Series Models & Applications,,ARIMA Model,Monte Carlo simulation,Generalized linear models,Bayesian Network Analysis,Markov Process,Stochastic Process,Bootstrapping,Hidden Markov Chains,Couplas,Extreme Value Theory,Multivariate Calculus etc
The digital revolution has created vast quantities of data. Extracting knowledge and insight from this avalanche of information is the goal of data science, a rapidly growing field with applications in such areas as marketing, education, and sports, as well as scientific fields such as genomics, neuroscience, and particle physics in addition to statistics. Working with large data sets, they will build mathematical models, use advanced statistical methods, and implement machine learning algorit
Statistical data analysis are immensely useful in solving economic problems such as wages, price, time series analysis, demand analysis.We can use the skills in areas of work in Insurance, mortality,marketing, public health, biology, even sports. Employment of statisticians is projected to grow 31 percent from 2018 to 2028, much faster than the average for all occupations. Growth is expected to result from more widespread use of statistical analysis to make informed business, healthcare etc.
Data science profoundly influences everything from business decisions to national security to what consumer products we buy. It impacts retail markets,solves public health dilemmas,Improves our manufacturing process to produce a better product.We can better predict future disease outbreaks using the real-time exchange of clinical health information.A recent study on hiring trends in India indicates that 97,000 positions related to data science are currently vacant due to a dearth of skills.
Machine Learning & Deep Learning are attracting more traction lately because of the recent innovations that have made headlines. Siri, Humanoids, Chatbots, Robotics are some to name a few. The varied applicability of mathematics & AI in a multitude of industries including entertainment, transportation, finance, retail etc. makes this technology a hot job & career destination. AI and machine learning have the potential to create an additional $2.6 trillion in value for marketing & sales by 2020.
AI is going to change the world more than anything in the history of mankind.Artificial Intelligence helps in finding solutions to complex business problems in a more human-like fashion..AI is applied on intelligent implementations, which includes robots, smart cars, consumer electronics etc. along with various apps and business solutions. A 2019 report from Gartner shows that enterprise applications for AI have grown 270% in four years, fueling a level of demand that outstrips the supply.
The adoption of Artificial Intelligence (AI) technologies is widely expanding in our society.
Neural Networks,Image recognition,speech recognition,Natural Language Processing.
In depth- R Programming,Python Programming,Advanced applied statistical techniques.
Indepth-Data science course
Due to Corona virus disease (COVID-19) epidemic students & professionals spend more time at home in an attempt to slow the spread.In view of that we planned this summer course to be delivered fully online.