The branch of knowledge which depends solely on the scientific methods, operations, problem-solving effectiveness, and setups to extract understanding and comprehension from data covering an excessive range of application zones is what is meant by data science.
Data scientists are experts who deal with large data, by analyzing them as sets of structured or unstructured pieces of information. The analysis, processing, and modeling of data and interpreting the outcomes in order to generate sufficient suggestions for businesses and corporations are the main job responsibilities of a data scientist.
The common job profiles after having educated in data science are either to be a data scientist who designs data modeling tasks to design algorithms and predictive models and execute conventional methods of data analysis or a data analyst who handles large sets of data and use them in the recognition of trends and to arrive at relevant interpretations to notify prudent business findings.
When job satisfaction and happiness quotient are considered, they enjoy average happiness at work. The result of a survey shows 3.3 out of 5 to range the level of satisfaction at work. When considered in terms of income, these are well-paid jobs, as the average pay of data professionals is $116,100 annually making it a flourishing and profitable career to be pursued.
The stress level is also high as they tend to have work pressure when they are to solve a big hitch in order to complete a project, especially when there are high presumptions. The growth in this sector is surely going to be competitive enough in the days to come, as the need for data experts is in constant demand. A data scientist has to verify the queries and come up with the answers and find out the source of the data. They should be well aware of the mining, cleaning, and presenting of data. Corporate programs utilize data professionals to derive, organize and explore unstructured data available in large amounts. The required skills for an effective data scientist are that they should be well aware of the programming languages such as Python, SQL, Scala, Java, and MATLAB.
Several institutions and universities are providing courses for a better understanding of data science. Some of them are enlisted below;
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1. Data Science at Georgetown University
The program offered by the Georgetown University presents the students with a certificate in Data Science. It offers the skills to analyze the data by collecting, cleaning, modeling, and presenting it. The knowledge to handle python language for programming, and all the necessary gears on par with the industrial standards for creating and presenting data analytics, predictive models, and visualizations. The communication skills are also improved alongside the ability to face actual issues while handling machine language. The educators are experts in the arena and are part of the data science community, with ample and more practical experience in handling projects in data science. The course brings about an overall and complete development in the learner to become competent in the data science career market.
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2. MS in Data Science at Eastern University
The course seems highly relevant in today’s technological world, as the requirement for data science specialists are booming. The masters provided at Eastern University is up to the mark and educates the learners in coding languages, serious understanding of DS-standard programming, mathematics, statistics, data analysis, and machine learning.
The program by the university has been ranked #1 in Online Data Science Program because of its uniqueness and self-paced approach becoming a perfect pick for any aspirant. An average salary of $105,676 is expected after the completion of the prescribed program. The course fee comes around $9,900.
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3. Data Science Major at the University of California, Berkeley
The University of California, Berkeley delivers the Data Science Major program including the basics of technical information on the ethical and human contexts of data science and its applications. The program follows a flexible pattern making it easy for any kind of student and is intended to strengthen the demand surrounded by the development of data in every walk of life. The change ultimately will be of help to those who are not proficient in data analysis but have only a basic understanding of the collection, managing, and usage of data and to take apt decisions at the appropriate time with excellent communication. The students are also made capable to apply the acquired knowledge in real-life situations that they are bound to face. The students can reach up to necessary solutions for the problems arising in the practical aspects of their careers. They are well-practiced with knowledge about statistical inference, computational processes, data management strategies, domain knowledge, and theory. They are also made thorough of the topics such as artificial intelligence, machine learning and computing permeate and these directly or indirectly influence the society.
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4. Foundations of Data Science -The Data Science Institute at Columbia University
The course focuses on different conventional and mathematical models of data processing along with hurdles in the engineering of the processing of large-scale data systems. The course also projects the learning of five important markets involved as Cybersecurity, Financial Analytics, Health Analytics, New Media, and Smart Cities which are all part of the central economic innovation in New York. Several deep research learning is also carried out regarding the issues about data science and engineering.
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5. M.S. in Statistics: Data Science at Stanford University
The course provided at the University is delivered by the Statistical Department. The program allows a deep insight into subjects such as mathematics, statistics, computing skills alongside programming abilities. The electives in the course are designed according to the varied tastes of students opting for the data science major. A GPA score of 3.0 or above is commendable for the maintenance of study.
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6. Micro Masters Program in Statistics and Data Science at Massachusetts Institute of Technology
The program to teach data analysis and machine learning clubbed with probability and statistics in order to be masters in solving difficult issues related to data is taken over by the Massachusetts Institute of Technology. The course is developed for the ease of online delivery and divided into 4 sessions. It takes the learners through the basic understanding of the required methods in data science and practical experience with data analysis and machine learning. Machine learning algorithms combined with techniques of data analysis topics turn the leaner into a well-efficient data science practitioner and an inseparable part of an organization.
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7. M.S. Program Data Science at University of Southern California
The program is offered by the Department of Computer Science providing the students with a strong base in computer science and emphasizing particular algorithms, statistics, and system analysis. It also dives deep into the techniques of acquiring, storing, accessing, analyzing, and visualizing the actual data with reference to real-world situations such as energy, environment, health, media, medicine, and transportation.
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8. MS in Data Analytics Engineering at George Mason University
The program put forward by the Volgenau School of Engineering powered by the George Mason University is aimed at developing a combination of different disciplines together in a single course and an innovative approach to Data Analytics Engineering. The learners are sure to improve their abilities to make decisions at an apt time based on data handling. Topics related to data mining, information technology, statistical modeling, predictive analytics, optimization, risk analysis, and data visualization are considered too. The career options that open out in front of them include positions in finance, marketing, operations, business, government intelligence, and other organizations handling and creating large amounts of data as data scientists and analysts.
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9. Data Science, MSE at University of Pennsylvania
The MSE in Data Science by the University of Pennsylvania opens up a wide range of opportunities in consulting, science, policy-making, or communications. The course requires a two-year time duration involving detailed learning about machine learning, data analytics, statistics and a wide variety of electives joined with an excellent chance to apply all these leaned theories into practical use in the learner’s interested specialization sector. The specialization areas include; network science (the Warren Center for Network and Data Science), digital humanities (the Price Lab for Digital Humanities), biomedicine (the Institute for Biomedical Informatics), and public policy (the Penn Wharton Budget Model and the Annenberg Center for Public Policy) and along with this; there are conventional chances available in Computer and Information Science and Electrical and Systems Engineering. There are opportunities for continuing course work as well as the chance to work on a thesis in the practical aspect of the data science sector.
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10. Master in Interdisciplinary Data Science (MIDS) at Duke University
The center develops a group of creative minds who can find solutions easily for any upcoming hurdles with accurate strategy in handling data. The learners are converted into unique thinking minds who can be leaders in computational techniques and data management. The training is tedious and powerful such that the understanding of the field of data science becomes thorough and strong. They are given opportunities to face repeated practice in vital matters, working as a team, communicating abilities, and joint leadership to alter themselves into excellent and most wanted and valuable data scientists in the domain.
The course is prearranged in such as way that it helps to connect scientific learning with proficiency in the approaches of data science. The faculties involved in the education process are the top-notch teachers who are experts in the fields of computer science, statistics, math, economics, political science, sociology, medicine, neuroscience, law, and history. As a whole, there would be an improvement in the communicative, crisis averting, significant thinking, creativity, and data analysis of the learner.
