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Best Master’s in Data Science Programs for 2021

By Kat Campise, Data Scientist, Ph.D.

A masters in data science is an interdisciplinary degree program designed to prepare students for a data focused career. The coursework focus is on computer science, math, and statistics. There are both full-time and part-time options available depending your timeline and budget. There is also a growing number of online data science masters programs available.

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The Bureau of Labor and Statistics projects that the job outlook for data scientists will grow faster than average until the year 2028. As of February 2021 the average salary for a data scientist is $113,609. Strong salaries and above average job growth make now a good time to enter the field.

While each school and program have unique admissions requirements, there are some similarities. All data science masters programs require a background in statistics, mathematics, or computer science. You may be asked to submit letters of reference and writing or other samples of work such as programming projects. At first, its best to focus on the course offerings while narrowing down your program options.

Once you have a list of schools with the desired coursework, then review the admission requirements. Not all programs require a GRE or GMAT score. For example, George Washington University is one of many programs listed below where the GRE is not required. For help preparing for the GRE check out our test prep guide here.

At their core, all programs will focus on foundational data science. But within the field, there is also a tremendous amount of room to develop a specialty which could lead to different career opportunities. For example, NYU students take 6 electives in their area of interest such as in business, health, or analytics. When evaluating different programs, take note of the elective options to find a fit aligning with your interests.

A masters in data science is a professional degree. So, paying attention to how the program will create a long-term career foundation is critical. Its not enough to just take classes and work on projects. Graduate programs should also help build professional networks and provide contacts. Common career placement components include the following:

Most data science masters degree programs can be completed anywhere between 18 months and 3 years of full-time coursework. Increasingly, programs are launching part-time options, such as the University of Washington. This provides a great opportunity for working professionals.

Tuition is often the leading factor in making decisions about graduate school, and its an important one. The below list contains cost-per-credit information for each data science masters program. One thing to consider is that a higher cost-per-credit does always mean higher quality or guarantee better outcomes. Thats why evaluating all the components of a data science program are useful. Location, elective availability, and career services, are all key factors. Most accredited data science programs have some sort of financial aid or scholarships available. Visit our STEM Scholarship guide for more financial aid information.

This page is a current, comprehensive listing of accredited and masters degree programs in data science. The information is sourced from the most recent years of university course catalogs. Note that this is not a masters in data science program ranking.

American University Washington, D.C.Master of Science in Data ScienceAmerican Universitys M.S. in Data Science program is jointly administered by the School of Public Affairs and College of Arts and Sciences. Students take courses in statistical methods, programming, regression, machine learning, and political analysis. The aim is to master the theoretical knowledge and practical skills used by data scientists. These skills can apply to academia, industry, and government.

Program Length:30 Credit HoursDelivery Method:CampusGRE:Optional2020-2021 Tuition: $1,759 per creditCourse Offerings

Brown University Providence, Rhode IslandMasters Program in Data Science Students can earn a Masters Degree in Data Science as part of the Data Science Initiative at Brown University. There are nine credits required along with a capstone project in order to pass the program. The capstone project allows for hands-on experience and should entail at least 180 hours of work to receive one-course credit.

Program Length: 9 CreditsDelivery Method:CampusGRE: Recommended2020-2021 Tuition: $66,702 per yearCourse Offerings

California Baptist UniversityRiverside, CaliforniaM.S. in Data Science and Knowledge EngineeringCalifornia Baptist Universitys M.S. in Data Science and Knowledge Engineering is a 2 year program. The design is to help students develop their skills dealing with data, algorithms and presenting results. Students will learn to use these results to guide decision making. The core requirements begin with 3 courses focused on engineering research and advanced data based systems. The bulk of the program is 17 units in data management, data mining, statistics and information systems coursework. Finally, the program concludes with 6 units dealing with the thesis component of the program.

Program Length:32 UnitsDelivery Method:Campus2020-2021 Tuition: $695 per unitCourse Offerings

Carnegie Mellon University Pittsburgh, PennsylvaniaMaster of Computational Data Science (MCDS)The (MCDS) program provides students with the skills to handle the next generation of big data. Three majors include: systems, analytics or human-centered data science. Students work with industry leaders to complete a capstone project. They also use international challenge competitions as a means to gain experience and grow their portfolio.

Program Length: 144 UnitsDelivery Method:CampusGRE: Required2020-2021 Tuition: $25,750 per semesterCourse Offerings

Chapman University Orange, CaliforniaMaster of Science in Computational and Data SciencesCandidates for the masters in computational and data science at Chapman University begin by completing 13 core credits. These courses focus on basic methodologies and techniques of computational science. Students also complete 12 credits of electives. This is followed by a 6 credit thesis or additional elective credits in an emphasis area of their choice. They also offers a unique accelerated M.S. in data science open to Chapman undergraduate students. Students can take up to 12 credit during their senior year. They can then earn a data science M.S. in just one year after earning their undergraduate degree.

Program Length: 31 Credit HoursDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,630 per unitCourse Offerings

City College of New York New York, New YorkMasters Program in Data Science and EngineeringTThe Masters Program in Data Science and Engineering is for students with a background in science, engineering, or mathematics. The core education covers fundamental data science and engineering computational and statistical skills. Students will apply these skills in a hands-on manner by combining the core knowledge with domain knowledge. This will be developed through two or more elective courses. Before graduation students must complete a capstone project or thesis. Through this they must show a thorough understanding of the mastery of data science methodology.

Program Length: 30 CreditsDelivery Method:CampusGRE: Not Required2020-2021 Tuition: $5,365 per semester (New York Resident) $830 per credit (Non-resident)Course Offerings

City University of New York New York, New YorkM.S. Program in Data ScienceThrough the Graduate Center of the City University of New York, students earn a Masters in Data Science in 30 credits. There are four foundational courses and two elective courses. A capstone project can be an internship or a research project to extend learning beyond the classroom. As a public university, CUNY offers very affordable tuition resulting in an exceptional value for students.

Program Length: 30 CreditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $470 per Credit (New York Resident), $855 per Credit (Non-resident)Course Offerings

Claremont Graduate University Claremont, CaliforniaMasters of Science in Information Systems & Technology: Concentration in Data Science & AnalyticsClaremont Graduate University offers a Masters of Science in Information Systems & Technology. Five differed concentrations are offered including data science and analytics. This program teaches students how large quantities of data can be leveraged to solve business and societal problems. Hands-on experience is offered through the Data Science Lab. This gives students the opportunity to assist businesses with the data science concepts they have learned. Full-time students generally complete the program in 1-1.5 years. This increases to 1.5-3 years for part-time students.

Program Length: 36 UnitsDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,980 per unitCourse Offerings

Clemson University Clemson, South CarolinaMaster of Science in Biomedical Data Science and InformaticsThe MS in biomedical data science and informatics is a 30-credit non-thesis program that takes 1.5-2 years to complete. Students take courses in 4 different areas. These span computing, engineering, mathematics, biology, and public health. Applicants must have a bachelors in health science, computing, mathematics, statistics, engineering, or a related field. It is recommended to also have competency in a second of these areas. Program requirements include a year of calculus and college biology. Student must also have experience in computer programming.

Program Length: 36 UnitsDelivery Method:CampusGRE:Required2020-2021 Tuition: $668 per credit ( South Carolina Resident), $995 per credit (Non-resident)Course Offerings

College of Charleston Charleston, South CarolinaMasters in Data Science and AnalyticsThe College of Charlestons Masters in Data Science and Analytics program teaches students to scrape, process, organize, and analyze large data sets for the purpose of identifying patterns and trends. Students also learn the skills of problem-solving tools in mathematics and computer science. Learned skills can include gathering information, sports analytics, precision medicine, stock market predictions, and leveraging big data.

Program Length: 36 CreditsDelivery Method: CampusGRE: Recommended for US Students, Required for International Students2020-2021 Tuition: $574 per credit (South Carolina Resident), $1,506 per credit (Non-resident) Course Offerings

Columbia University in the City of New York New York, NewYorkMS Masters in Data ScienceAt Columbia University the Masters in Data Science is a part of the Data Science Institute. This unique program applies data techniques to the students field of interest and is affiliated with 11 other graduate programs at Columbia. Students will conduct original research culminating in a capstone project. This program includes 30 credits with a variety of electives, including: cybersecurity, data media and society, financial and business analytics, health analytics and smart cities.

Program Length: 30 credit hoursDelivery Method:CampusGRE: Required2020-2021 Tuition: $2,104 per credit Course Offerings

Cornell University Ithaca, New YorkMaster of Professional Studies (MPS) in Applied Statistics (Option II: Data Science)M.S. track in Biostatistics and Data ScienceCornell University offers a Master of Professional Studies (MPS) in Applied Statistics (Option II: Data Science). Students who participate in this program obtain world class training in applied statistics and gain a solid foundation in theoretical statistics while receiving a certification in SAS. A real world data analysis project will be completed by students in this program. The main components of this degree are core courses and an in depth MPS project.

Program Length: 30-37 CreditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $28,275 per semesterCourse Offerings -Applied StatisticsCourse Offerings BioStatistics and Data Science

Dartmouth University Lebanon, New HampshireQBS Masters of Science in Health Data ScienceAt Dartmouths Geisel School of Medicine, the 15-month QBS Masters of Science in Health Data Science program builds core skills of data science in the areas of Big Data wrangling, database programming, high-performance computing, data visualization, exploratory statistics, statistical modeling, and machine learning. All courses build up students verbal, visual, and written skills. To graduate from the program, students must complete 9 required courses, including a capstone that integrates all learned knowledge. Students must take up to 9 elective courses during the 5 quarters in residence. Summer internships are also available.

Program Length: 15 MonthsDelivery Method:CampusGRE: Required2020-2021 Tuition: $19,258 per termCourse Offerings

Duke University Durham, North CarolinaMaster in Interdisciplinary Data Science (MIDS)Duke University offers a two-year Master in Interdisciplinary Data Science (MIDS). Students will complete eight core courses covering key topics in machine learning, data wrangling, database management, team management, statistics, data communication, analytical thinking, and ethics. Additionally, students select approximately eight electives to further their expertise within their focus of choice.

Program Length: 17 CoursesDelivery Method:CampusGRE: Required2020-2021 Tuition: $27,840 per semesterCourse Offerings

Embry-Riddle Aeronautical University Daytona Beach, FloridaM.S. in Data ScienceEmbry-Riddle Aeronautical University offers a Masters of Science degree in Data Science that is designed to use the latest computational and analytical tools for solving data intensive problems. The program aims to build knowledge and skills in data collection, pre-processing, analysis, visualization, and ethical implication of modern data. The M.S. in Data Science consists of 15 credits of required coursework plus 3 additional credits of track-specific required courses as well as 12 credits of electives and/or thesis research.

Program Length: 30 CreditsDelivery Method: CampusGRE: Not required 2020-2021 Tuition: $576 per credit (Military), $689 per credit (Civilian) Course Offerings

Fitchburg State University Fitchburg, MassachusettsMaster of Science in Computer Science with a Data Science ConcentrationThe Masters Degree Program in Computer Science at Fitchburg builds skills for a career in the high-technology marketplace. Students study managing data, mining data, integrating, and analyzing big data across various fields of business, medicine, bioinformatics, government, education, marketing, security, and financial management. The Data Science concentration builds on data analysis, visualization, database development, machine learning, and data mining. The program offers evening classes with day courses during the summer. Students must complete 34 credits over a time frame of 2 years to 6 years.

Program Length: 34 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $319 per creditCourse Offerings

George Washington University Washington D.C.Master of Science in Data ScienceAt George Washington University students can participate in the Master of Science in Data Science program. This is an interdisciplinary curriculum that spans six different specialties. Participants of this program partner with major organizations in the DC area. This program offers practical application of problem solving, communication and teamwork skills, which concludes with a capstone project with real world experience. One-on-one mentoring is also available to all students.

Program Length: 30 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $1765 per creditCourse Offerings

Georgetown University Washington D.C.Master of Science in Analytics, Concentration in Data SciencesStudents in the Georgetown M.S. in Analytics program build a solid knowledge in data analytics fundamentals and then add skills in visualization, big data computing, and machine learning. Important soft skills such as communication, teamwork, and problem solving techniques are part of the training throughout. Students complete five core Analytics courses and five electives, allowing them to customize their curriculum with elective coursework in Analytics, Computer Science, Math & Statistics, Economics, Biostatistics, Public Policy, Business, and more. The program has strong relationships with industry partners throughout Washington, D.C., and regularly hosts seminars, workshops, and career fairs to prepare students for internships and post-graduate employment. Graduates of the program pursue careers in fields including business intelligence, precision medicine, policy analytics, finance, marketing, online banking, big data infrastructure, and education.

Program Length: 30 creditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $2,139 per creditCourse Offerings

Grand Valley State University Allendale, Michigan.Master of Science (M.S.) in Data Science and AnalyticsGrand Valley State Universitys Master of Science in Data Science and Analytics provides students with fundamental background knowledge of analytics for working with massive sets of complex data. Statistics or computing students may gain additional cross-disciplinary background while a student of any discipline may develop skills to solve data-sensitive problems. The M.S. in Data Science and Analytics may be applied to health, social, political, and environmental issues from the scientific and technological viewpoint. Students of this program must complete 36 credits in statistics, computer science, and professional science. Applicants wishing to obtain entry into the data science and analytics program must hold at least a 3.0 GPA, possess a resume with detailed work experience and accomplishments, a personal statement of career goals, two professional recommendations, and two prerequisite courses.

Program Length: 36 creditsDelivery Method:CampusGRE: Not Required2020-2021 Tuition: $702 per creditCourse Offerings

Harvard University Cambridge, MassachusettsMaster of Science in Data ScienceHarvard recently announced the creation of a new Master of Science degree in Data Science. The degree, which will be guided by faculty from the computer science and statistics department, will be housed in the Institute for Applied Computational Science (IACS) at the John A. Paulson School of Engineering and Applied Sciences (SEAS).

Program Length: 12 coursesDelivery Method:CampusGRE: Required2020-2021 Tuition: $27,440 per termCourse Offerings

Illinois Institute of Technology Chicago, IllinoisMaster in Data ScienceIn Illinois Techs Master of Data Science program, students become well-rounded data scientists. They study fundamental mathematics, statistics, and computer science at a high-level, learn how to apply them to real-world problems, and master communicating effectively with diverse clients and collaborators. Students learn to question underlying assumptions and reformulate issues, explore and improve the structure of available data, create and evaluate models, draw conclusions, and determine how their findings can be productively used in the real world. All participants perform a practicum project with partners from industry and non-profit organizations.

Program Length: 33 creditsDelivery Method:CampusGRE: Required, unless waived2020-2021 Tuition: $1,575 per creditCourse offerings

Indiana University Purdue University IndianapolisIndianapolis, IndianaMaster of Science in Applied Data ScienceAt IUPUI, students learn to manage massive stores of data in the cloud and the data life cycle when you earn a M.S. in Applied Data Science.The plan of study includes eight required courses on the following topics: informatics, data visualization, relational databases, statistics, web and database development, project management or research design, statistical learning, and cloud computing. Six credit hours of the total 30 are approved electives. The M.S. in Applied Data Science can also be combined with specializations in either Sports Analytics or User Experience Design.

Program Length:30 credit hoursDelivery Method:Campus2020-2021 Tuition: $368 per credit (Indiana Resident), $1,006 per credit (Non-resident)Course Offerings

Lipscomb University Nashville, TennesseeMaster in Data ScienceThe masters in data science at Lipscomb University requires ten courses, eight of which are common to all students in topics such as information structures, statistical analysis and decision modeling, research methods in informatics, big data management and analytics, and data mining and predictive analytics. Applicants must either hold a related advanced degree, or an undergraduate degree in a relevant field of study with either five years of work experience or high GRE scores.

Program Length: 30 CreditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,288 per creditCourse Offerings

Loyola University of Maryland Baltimore, MarylandMaster of Science in Data ScienceIn a world where big data is getting bigger, Loyola University Marylands Data Science Masters program engulfs students in a quickly evolving discipline. The program carefully fuses computer science with statistics and business. Students will be prepared to utilize computer programming skills to reconstruct disorganized web data into orderly, understandable information. By using statistical modeling using R, students will possess the ability to address unlimited data issues in their given organization. With Loyolas 31-credit program, graduates will instill a robust database of knowledge in data science. The program has two specializations: the Technical specialization and an Analytics specialization

Program Length: 10 3-credit courses and one 1-credit courseDelivery Method:HybridGRE: Not required2020-2021 Tuition: $1,000 per creditCourse Offerings

Maharashi University of Management Fairfield, IowaMS in Computer Science Data Science TrackThe Data Science specialization of the Masters of Science in Computer Science program at Maharashi University of Management focuses on 4 core courses: Big Data, Big Data Technologies, Big Data Analytics, and Machine Learning. Students may also take courses in Algorithms, Web Application Programming, and Database Management System.

Program Length: 44 CreditsDelivery Method: CampusGRE: Required 2020-2021 Tuition: $41,000 $44,000 per program Course Offerings

Michigan Technological University Houghton, MichiganMasters in Data ScienceMichigan Techs masters in data science provides students with a strong foundation in data mining, predictive analytics, cloud computing, data-science fundamentals, communication, and business acumen. The degree requires four core courses and four chosen courses in topics such as biostatistics, web application development, machine learning, computer security, and computer simulation in physics. Applicants must have an undergraduate degree in business, science, or engineering, giving them at least basic knowledge in statistical and mathematics techniques, computer programming, information systems and databases, and communications.

Program Length:30 creditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,212 per creditCourse Offerings

New College of Florida Sarasota, FloridaMaster in Data ScienceAn MS in Data Science from New College of Florida provides its students with the fundamental knowledge and technical skills needed for long-term success in the data science industry. The programslimited size (15 students per year) and project-centered instruction insures students experience one-on-one interaction with faculty working with real world data to solve a range of real world problems.During the final semester, students participate in a paid practicum where they implement the concepts they have learned to obtain industry experience working as part of a data science team.

Program Length: 36 Credit HoursDelivery Method:CampusGRE: Not required2020-2021 Tuition: $474 per credit ( Florida Resident), $1,169 per credit (Non-resident)Course Offerings

New Jersey City University Jersey City, New JerseyMS in Business Analytics and Data ScienceStudents can complete NJCUs masters in business analytics and data science in either 16 months or part-time over 2 years. The masters requires 12 courses and a final capstone project. Students complete coursework in business analytics and data science, programming, data collection, warehousing, and cleansing, applied regression and time series, machine learning, experimental design, data visualization, and finally 4 electives. Applicants must have completed an undergraduate degree, but no specific field is required.

Program Length: 16 monthsDelivery Method:CampusGRE: Required2020-2021 Tuition: $709 per credit ( New Jersey Resident), $ 1,136 per credit (Non-resident)Course Offerings

New York University New York, New YorkMaster of Science in Data ScienceA Master of Science in Data Science at New York University is a new academic discipline. The Center for Data Science was established with the intersection of computer science, statistics and mathematics in mind. The program is divided into six core courses which focus on mathematical and programming backgrounds. Students have the option to pick from six electives based on their area of interest. The curriculum is focused on how methods work and the best way to implement/customize them. Students will gain a better understanding of why people make decisions and will also be able to predict future outcomes.

Program Length: 36 Credit HoursDelivery Method:CampusGRE: Required or GMAT2020-2021 Tuition: $1,856 per creditCourse Offerings

Northeastern University Boston, MassachusettsMS in Data ScienceThe masters program at Northeastern requires 5 core courses in algorithms and data processing, machine learning and data mining, and information visualization. Students are also required to take 3 electives. Every masters student takes placement exams upon entering, and may need to take introductory courses in programming for data science, and linear algebra and probability for data science if scores are below a B.

Program Length: 32 creditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,632 per creditCourse Offerings

Oklahoma State University Stillwater, OklahomaMS in Business Analytics and Data ScienceOklahoma State University offers a Masters in Business Analytics with a hands-on application of data analysis in a multi-platform environment. The program includes deep exposure to SAS tools as well as programming languages such as Python, R, SQL, and Tableau. As part of this program students are able to earn a Data Science Certificate, a Data Mining Certificate, and a Predictive Analytics Certificate.

Program Length: 37-40 Credit HoursDelivery Method:CampusGRE: Required or GMAT2020-2021 Tuition: $405 per credit (Oklahoma residents), $1,031 per credit (Non-resident)Course Offerings

Rensselaer Polytechnic Institute Troy, New YorkM.S. in Information Technology Concentration in Data Science and AnalyticsRensselaer Polytechnic Institute offers an M.S. in Information Technology Concentration in Data Science and Analytics. Data science and analytics is one of 12 concentrations in MS in Information Technology. This program balances the study of management strategies and technology leadership with advanced coursework in an IT concentration. Students are required to complete a suite of core and capstone courses. Three to five additional courses must be selected to complete a concentration. A professional and research track are offered for the M.S. in IT degree.

Program Length: 30 CreditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $2,250 per creditCourse Offerings

Rutgers University New Brunswick, New JerseyMaster of Business And Science DegreeRutgers offers both an MBS in analyticsdiscovery informatics and data sciencesand a masters in data science. The MBS requires 6 courses in business, such as market assessment and principles of accounting, as well as 5 courses in data science, such as regression analysis, cloud computing and big data, and database design and management. The masters in data science is composed of 6 foundational courses, which focus on data retrieval, cleaning, and modeling, machine learning, interactive visualization tools, and pattern recognition. In addition, 6 electives are required for the masters, which provide depth in a specialization such as statistics, algorithms, optimization, machine learning, data privacy, computer graphics, and vision.

Program Length: 43 credits Business and Science, 12 courses Data ScienceDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,015 per credit (Resident), $1,256 per credit (Non-resident)Course Offerings Business and Science

Saint Louis University St. Louis, MissouriHealth Data ScienceSaint Louis University offers a unique 2-year masters in health data science. Students cover 3 main topics, specifically analytics, computing, and health sciences. Each of these blocks is comprised of 3 courses, such as predictive modeling, machine learning, programming, health data management, high performance computing in healthcare, medical diagnosis and treatment, and communication and leadership in the health care industry. Students receive advanced training in data manipulation, data visualization, data mining, machine learning, predictive analytics, and programming in R, SQL and Python.

Program Length: 30 creditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $1,160 per creditCourse Offering

Saint Peters University Jersey City, New JerseyMaster of Science in Data Science with a concentration in Business AnalyticsAt Saint Peters University students can earn a Master of Science in Data Science with a concentration in Business Analytics degree. This program focuses heavily on business analytics, at which time students learn to integrate scientific methods from statistics, computer science and data based management to help make business decisions. Classes are housed in the Data Science Institute, a state of the art data science laboratory. The curriculum of this program leads students to pathways of internships and employment opportunities.

Program Length: 12 CoursesDelivery Method:CampusGRE: Not required2020-2021 Tuition: $1,177 per creditCourse Offering

St. Johns University Queens, New YorkData Science, Master of ScienceGraduates of St. Johns M.S. in Data Science program will possess skills in analyzing large datasets and developing model solutions to support decision making. Additionally, students will have a specialization in either marketing analytics or healthcare analytics. The program requires 30 credits in Data Analysis/Applied Statistics, Database Design/Data Warehousing, Data Mining/Predictive Modeling, 6 credits of elective courses, 6 credits of Specialization, and a 3-credit capstone course.

Program Length: 30 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $1,265 per creditCourse Offering

Stanford University Stanford, CaliforniaM.S. in Statistics: Data ScienceStanfords M.S. in Statistics: Data Science degree is a relatively new program which was developed with the structure of MS in Statistics and the MS program in ICME (Institute for Computational and Mathematical Engineering). The focus of this program is to assist students in strengthening their data science fundamentals, as well as their mathematical, statistical and computational skills. A unique component of this program is that students are offered various electives and may choose based on their field of interest.

Program Length: 45 creditsDelivery Method:CampusGRE: Required2020-2021 Tuition: $1,166 per creditCourse Offerings

St. John Fisher CollegeRochester, New YorkMaster of Science in Applied Data Science St. John Fishers Master of Science in Applied Data Science degree is designed to transform students with or without quantitative backgrounds into effective Data Scientists. The program works well for those with undergraduate experience looking to bolster their career prospects, as well as individuals seeking career advancement in their respective industries. The blend of hybrid and traditional courses benefits the working professional and the full time student.The program typically takes most students two calendar years to complete, although full time students may be able to complete it in one calendar year.

Program Length:36 CreditsDelivery Method:CampusGRE:Not required2020-2021 Tuition $975 per creditCourse Offerings

Stevens Institute of TechnologyHoboken, New JerseyData Science Masters Program The interdisciplinary Data Science Masters Program at Stevens Institute prepares students for careers in fintech, business intelligence and analytics, academia, and database management. Students may also gain skills for government positions requiring strong skills in data analysis. Students may pursue one of four optional concentrations in Fundamentals of Data Science, Data Acquisition and Management, Data Security, and Business Applications. Research credits are available. Both thesis and non-thesis options are available. The curriculum requires 30 graduate credits in an approved plan of study.

Program Length:30 CreditsDelivery Method:CampusGRE:Required2020-2021 Tuition: $1,652 per credit Course Offerings

South Dakota State University Brookings, South DakotaMS in Data ScienceSouth Dakota State Universitys MS in Data Science degree provides graduates with statistical, mathematical, and computational skills. This one year program is innovative, professionally relevant, and valuable. Students will learn operation research, predictive modeling, data mining, forecasting big data programming, management and data visualization. The focus will be on application and interpretation of modern data analysis techniques.

Program Length: 30 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $337 per credit ( South Dakota Resident), $648 per credit (Non-resident)Course Offerings

SUNY University at Albany Albany, New YorkData Science Master of ScienceThe State University of New York at Albany offers a Data Science Master of Science that provides students with foundations in Topological Data Analysis, Machine Learning, and Statistical Methods. Students are expected to complete 36 credits, including a course in computational methods. Students choose one of three practicum courses and two elective courses. According to SUNY, the practicum course serves as the capstone experience. This experience includes comprehensive analysis of data sets with oral presentations or poster presentations of results.

Program Length: 36 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $471 per credit (New York Resident), $1,073 per credit (Non-resident)Course Offerings

Texas Tech University Lubbock, TexasMaster of Science in Data ScienceTexas Techs Master of Science in Data Science offers an emphasis on statistics, technology, and business education. During this one year program students learn how to use advanced technologies to manipulate data, utilize statistical methods to interpret data and obtain necessary business skills. Graduates of this program have found careers in data science, business analytics, business intelligence and big data fields.

Programs Length: 36 CreditsDelivery Method:CampusGRE: Required or GMAT2020-2021 Tuition: $333 per credit ( Texas Resident), $755 per credit (Non-resident)Course Offerings

Tufts University Medford/Somerville, MassachusettsM.S. in Data ScienceTufts School of Engineerings Master of Science program in data science prepares students for careers in data analysis and data-intensive science. The program focuses on statistics and machine learning, with courses in data infrastructure and systems, data analysis and interfaces, and theoretical elements. Students can enroll through the Department of Computer Science or the Department of Electrical and Computer Engineering.

Programs Length: 1+ years, 30 semester-hour unitsDelivery Method:CampusGRE: Required2020-2021 Tuition: $52,724 per academic yearCourse Offerings

University of Alabama at Birmingham Birmingham, AlabamaM.S. in Data Science (MSDS)The University of Alabama at Birminghams M.S. in Data Science program consists of 30 credit hours. The thesis-option consists of 24 credit hours of computer science course work plus six credit hours of thesis research, and the non-thesis option consists of30 credit hours of computer science coursework. The entire program takes approximately one and a half to two years to complete. Students have the option to take a full course load in summer, allowing them to complete the program in three semesters. Coursework includes studies in machine learning (including deep learning), data mining,modeling and quantitative analysis of massive datasets, application and technology in strategic decisions, collecting and managing massive datasets, and implementing practical solutions to current big data problems using algorithmic techniques and software development tools.The program includes a set ofcore required coursesand provides an opportunity for students to select from a wide range of electives related to data analytics, biostatistics, bioinformatics, business intelligence, and cyber security.

Programs Length: 30 CreditsDelivery Method:CampusGRE: Not required2020-2021 Tuition: $450 per credit (Alabama resident), $1030 per credit (Non-resident)Course Offerings

University of Albany Albany, New YorkMaster of Science in Data ScienceThe State University of New York, University at Albany, offers a Master of Science in Data Science program that builds a foundation of three major fields of Data Science: Topological Data Analysis, Machine Learning, and Statistical Methods. The program requires at least 36 credits of coursework. The Core Requirement involves one course in Modern Computing for Mathematicians. Other course studies include Topological Data Analysis, Machine Learning, Statistics, Practicum, and Electives. Lastly, the capstone requirement involves comprehensive analysis of data sets along with oral presentations or poster presentations of such results.

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Best Master's in Data Science Programs for 2021

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Great Learning collaborates with MIT Professional Education to offer Applied Data Science Program – PRNewswire

The 12-week long virtual program is designed to helplearnersunderstand how to become successful, data-driven decision-makers

BOSTON, April 21, 2021 /PRNewswire/ -- Great Learning, a leading global ed-tech company for professional and higher education, announces the launch of MIT Professional Education's Applied Data Science Programwith curriculum developed and taught by MIT faculty, and delivered in collaboration with Great Learning.The comprehensive curriculum for the twelve-week program will be delivered on weekdays, followed by sessions over the weekends by Great Learning mentors and industry experts.

As per QS World University Rankings for 2019-2020, MIT was named the world's top university for the eighth year in a row based on factors such as academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students

The curriculum for the Applied Data Science Program starts with basics such as Statistics and increases in complexity as it moves into Graph Neural Networks. It is designed for working professionals and entrepreneurs aspiring to learn contemporary and advanced Data Science topics. After successful completion of the program, learners with prior experience in programming and statistics should be able to understand various Data Science techniques and their applications to real-world problems, and how to implement various Machine Learning techniques to solve complex problems and make data-driven business decisions. The program offers hands-on exposure to industry-relevant projects created by Data Science and Machine Learning experts via live and personalized mentored learning sessions.

Speaking about the collaboration Mohan Lakhmaraju, Founder and CEO, Great Learning said, "We started Great Learning 7 years ago with a vision of making high-quality, outcome-driven, impactful learning accessible to all. We are excited to collaborate with MIT Professional Education in the delivery of this program. Collaborations with prestigious institutions such as MIT, assist us in realizing our vision of enabling access to high-quality education and impressive learning outcomes for anyone willing to work hard and upskill."

"The Advanced Data Science Program offered by MIT Professional Education brings together cutting-edge content and teaching from MIT faculty, while reflecting the educational ideals of MIT's founders who were focused on, above all, education for practical application," said Malgorzata Hedderick, Director of Short and International Programs at MIT Professional Education. "We look forward to collaborating with Great Learning on the delivery of the program, and the additional benefit participants will receive from Great Learning's program mentors."

The program will help prepare professionals for sought-after roles including Data Analyst, Data Scientist, Machine Learning Engineer, and Analytics/Data Science Manager. It will also help aspiring entrepreneurs who are looking to build and lead impactful organizations and businesses in tackling complex business problems. Upon successful completion of the program, learners will receive a Certificate of Completion from MIT Professional Education.

Interested professionals and practitioners are invited to learn more about the program from Prof. Devavrat Shah,Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, and Great Learning experts at a webinar on April 21st, 2021, at 11:00 am (ET) by registering at https://register.gotowebinar.com/register/3440095220363437325?source=pr

About MIT Professional Education

For 70 years, MIT Professional Education has been providing technical professionals worldwide a gateway to renowned MIT research, knowledge and expertise, through advanced education programs designed specifically for them. In addition to industry-focused, two-to-five-day live virtual and on-campus Short Programs, MIT Professional Education offers professionals the opportunity to take multi-lingual online-blended learning courses and programs through Digital Plus Programs, attend courses abroad through International Programs, enroll in regular MIT academic courses through the Advanced Study Program, or attend Custom Programs online and in-person designed specifically for their companies. For more information, please visit:professional.mit.edu.

About Great Learning

Great Learning is a leading global ed-tech company for professional and higher education. It offers comprehensive, industry-relevant, hands-on learning programs across various business, technology and interdisciplinary domains driving the digital economy. Great Learning's programs are developed in collaboration with the world's foremost academic institutions, and are constantly reimagined and revamped to address the dynamic needs of the rapidly evolving business landscape. Relying on its vast network of expert mentors and highly qualified faculty, Great Learning has delivered an unmatched learning experience for over 1 million learners from over 160 countries around the world.

Media Contact:

Rishita Chiranewala [emailprotected] PR Head Great Learning

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JG Wentworth hires Senior VP of Analytics and Data Science to lead their Digital Evolution – The Reporter

CHESTERBROOK, Pa., April 20, 2021 /PRNewswire/ --JG Wentworth, a market leading provider of financial services in the debt relief and structured settlement markets, today announced Gaurav Marballi joined the company to serve as its Senior Vice President of Analytics and Data Science.

"In this new role, Gaurav will be responsible for driving and leading our data and analytics strategy across all products. He will facilitate our migration to a data and analytics focused organization, which utilizes sophisticated predictive tools and methodologies to drive growth and long-term profitability," said Randi Sellari, CEO. "We are very excited to have Gaurav's leadership and experience as our company continues to find new ways to leverage the JG Wentworth brand awareness and grow the brand to new heights while remaining focused on our pursuit to providing individuals with life-changing financial options".

"I feel privileged to join JG Wentworth on their mission to use data and analytics to accelerate their digital transformation efforts," said Gaurav. "I look forward to working with Randi and the JG Wentworth team to expand on the ability to compete in an emerging digital economy, in ways that generate significant value for customers, while also achieving timely and actionable insights."

Gaurav, a graduate of the University of Mumbai with an MBA from Harvard Business School, joins JG Wentworth from Priceline where he led the analytics team that developed transformational data-driven strategies and machine learning capabilities across key functions including sales, marketing, pricing, and competitive intelligence. Prior to Priceline, he led analytics and product teams for a wide variety of companies, including Standard and Poors, Capital IQ, McGraw-Hill, and Barnes and Noble Education. He spent his early career in telecom where he developed technology to secure customer data on mobile phones, for which he holds two US patents.

About JG Wentworth

JG Wentworth is a financial services company that focuses on helping customers who are experiencing financial hardship or need to quickly access cash. Its services include debt relief, structured settlement payment purchasing, annuity payment purchasing, lottery and casino payment purchasing. J.G. Wentworth was founded in 1991 and currently has offices in Chesterbrook, Pennsylvania, Radnor, Pennsylvania and Rockville, Maryland.

For more information about J.G. Wentworth visit http://www.jgwentworth.com or use the information provided below.

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SOURCE The JG Wentworth Company

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Master The Science Of Machine Learning With These Training Classes – IFLScience

Our interactions in (and out) of the tech world all rely heavily on machine learning (ML), the science of getting computers and devices to mimic human behavior. In fact, experts are now putting more of an emphasis on machine learning versus the more widely-used artificial intelligence (AI) acronym. Even Twitter is now taking a closer look at its machine learning algorithms, giving users more agency over the way its ML affects their experience on the platform.

Suffice to say, its an important science that plays a pretty big role in our day-to-day lives. If youre interested in understanding how it all works and potentially becoming the next innovator in ML check out the on-sale Machine Learning Master Class Bundle. Complete with eight courses, this class pack covers everything from mathematical foundations in ML and AI to working with industry-popular platforms TensorFlow and Python.

First things first: understanding the math behind machine learning and artificial intelligence will give you the proper foundation for diving deep into this interesting science. From linear algebra to multivariate calculus, youll learn the algorithms that power self-driving cars and virtual assistants. Armed with this skill set, youll be ready to create your own AI projects.

With data science at the forefront of nearly every industry today, youll learn real-life lessons from the course on data visualization with Python. Once you have the basics down, like Pythons visualization library Matplotlib, youll work on advanced concepts that youll later apply to your own work.

Another important platform, TensorFlow for beginners teaches you everything you need to know about the software library used by Google, Snapchat and Twitter. This course includes insights on AI musts like speech recognition and how to add such AI features to applications. Youll solidify your skills by building your own project.

With this bundle, youll become a top contender for jobs in the machine learning space (and you might just learn how to boost your love life, too). Right now, you can get lifetime access to the full The Machine Learning Master Class Bundle at $39, down 91% from the original MSRP.

Prices subject to change.

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Data scientists: Bring the narrative to the forefront – TechCrunch

Peter Wang is CEO and co-founder of data science platform Anaconda. Hes also a co-creator of the PyData community and conferences, and a member of the board at the Center for Humane Technology.

By 2025, 463 exabytes of data will be created each day, according to some estimates. (For perspective, one exabyte of storage could hold 50,000 years of DVD-quality video.) Its now easier than ever to translate physical and digital actions into data, and businesses of all types have raced to amass as much data as possible in order to gain a competitive edge.

However, in our collective infatuation with data (and obtaining more of it), whats often overlooked is the role that storytelling plays in extracting real value from data.

The reality is that data by itself is insufficient to really influence human behavior. Whether the goal is to improve a business bottom line or convince people to stay home amid a pandemic, its the narrative that compels action, rather than the numbers alone. As more data is collected and analyzed, communication and storytelling will become even more integral in the data science discipline because of their role in separating the signal from the noise.

Yet this can be an area where data scientists struggle. In Anacondas 2020 State of Data Science survey of more than 2,300 data scientists, nearly a quarter of respondents said that their data science or machine learning (ML) teams lacked communication skills. This may be one reason why roughly 40% of respondents said they were able to effectively demonstrate business impact only sometimes or almost never.

The best data practitioners must be as skilled in storytelling as they are in coding and deploying models and yes, this extends beyond creating visualizations to accompany reports. Here are some recommendations for how data scientists can situate their results within larger contextual narratives.

Ever-growing datasets help machine learning models better understand the scope of a problem space, but more data does not necessarily help with human comprehension. Even for the most left-brain of thinkers, its not in our nature to understand large abstract numbers or things like marginal improvements in accuracy. This is why its important to include points of reference in your storytelling that make data tangible.

For example, throughout the pandemic, weve been bombarded with countless statistics around case counts, death rates, positivity rates, and more. While all of this data is important, tools like interactive maps and conversations around reproduction numbers are more effective than massive data dumps in terms of providing context, conveying risk, and, consequently, helping change behaviors as needed. In working with numbers, data practitioners have a responsibility to provide the necessary structure so that the data can be understood by the intended audience.

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Carleton University and IBM Partner in AI, ML and Data Science for a Future-Ready Workforce – HPCwire

OTTAWA, April 15, 2021 Carleton University and IBM Canada today announce a five-year multimillion-dollar collaboration agreement to enhance Carletons Institute for Data Science and equip students for essential jobs in emerging digital careers such as artificial intelligence (AI), machine learning and data science.

The agreement establishes a framework for joint research and educational initiatives to boost the Universitys cross-disciplinary AI and Data Science programs and technology-rich learning environment.

Were excited to expand our partnership with IBM Canada, said Carleton President Benoit-Antoine Bacon. AI, machine learning and cloud technology are transforming how we live and work, and this alliance will provide students with the research and learning opportunities needed to thrive in the jobs of tomorrow and future proof Canadas workforce and economy.

Steven Astorino, IBM Canada Lab Director and Vice President of Development for Data and AI, said: As businesses continue to accelerate their digital transformation, there is an increasing demand for access to talent and emerging skills in growth areas of data science, AI and machine learning. With the expansion of our collaborative relationship with Carleton University, IBM will provide leading-edge technology, industry expertise and apprenticeship and training opportunities to help address the digital skills gap in Canada and build domestic talent for secure, high-paying careers in AI and data science that are already in high demand.

Carleton and IBM Canada will develop new technological tools and training for graduate students and researchers. Additionally, during the first year of this agreement, IBM Canada is committed to providing:

The agreement creates opportunities for collaboration on research projects and academic initiatives to develop skills and foster work-integrated learning experiences. In addition, IBM Canada will be a member of a Data Science Advisory Board to provide guidance to the Institute and support delivery of the universitys new standalone research masters and doctorate programs in Data Science.

For more information on the Carleton University Institute of Data Science, please go to: https://carleton.ca/cuids/.

About Carleton

Carleton University is a dynamic, research-intensive institution that engages in partnerships to address the worlds most pressing issues. The universitys corporate collaborations bring together world-class companies, researchers and a new generation of talent with its 32,000 students to deliver innovations and results that are driving a more prosperous, sustainable future.

Source: Carleton University and IBM Canada

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Yelp data shows more than half million new businesses opened in the past year – CNBC

Kevin Kahovec and Mary Kate McGovern chat at Rizzo's Bar & Inn in Wrigleyville as coronavirus disease (COVID-19) restrictions are relaxed in Chicago, Illinois, March 6, 2021.

Eileen T. Meslar | Reuters

More than 500,000 new businesses opened across the United States in the past year, new data from Yelp showed, as the economy recovered from the depths of the Covid pandemic.

In its Economic Average Report, released Wednesday and compiled from the listings on its service, Yelp saw 516,754 new business openings from April 1, 2020, through March 31, remarkably down only 11% year over year. About 28%, 146,486, were in the first three months of 2021, down just 2% from a year earlier.

"Our data shows that more new businesses opened in the U.S. during the first quarter of 2021 than at any other period over the last 12 months, providing an optimistic outlook that local economies are back on solid ground after a tumultuous year," Yelp data science vice president Justin Norman told CNBC. "After a challenging year, 2021 is off to an encouraging start for the local economy."

Yelp's data found that more than 69,000 new restaurants and food businesses opened in the past year. While that's down 14% from the prior year, it's still strong given those businesses were among the hardest hit by the coronavirus lockdowns in the early days of 2020 and the subsequent virus mitigation measures.

"It seems like the year-over-year rise in new business openings mirrors the current housing market frenzy," Norman said. "People are inspired to take advantage of low rents and create new jobs by putting their personal savings towards starting a new business venture."

Across the country, different states have seen different rates of reopening in the first quarter. But Yelp data found that every state except North Dakota saw a higher number of openings in Q1 than they did in the fourth quarter of last year. Not surprisingly, the states with the highest number of business openings were among those that eased restrictions throughout March or earlier, such as Michigan, Mississippi and South Carolina.

Since March 1, 2020, nearly 258,200 businesses have reopened, with over 50,000 of them in the first quarter of this year, reaching the highest levels since last summer.

Yelp has been publishing economic reports since the start of the pandemic, which caused the temporary or permanent shutdown of hundreds of thousands of businesses across the country. Yelp measures reopened businesses by counting U.S. businesses that were temporarily closed and opened again through March 31, 2021, and each reopened business is counted on the most recent day of its reopening.

"Business reopenings also rose across the country and even spiked in Q1 2021," Norman said.

The types of businesses that have reopened strongly in Q1 mostly reflect sectors that were adversely impacted by the shutdowns, including bars, coffee houses, and breakfast and brunch spots.

Tax services in particular saw a huge increase in reopenings. "In Q1, more banks and tax services have reopened to provide in-person assistance that, coupled with an especially confusing 2020 tax season, helps explain why we've seen a spike in reopenings for tax professionals and banks," Norman said.

Again, Yelp data showed that certain states experienced an increased level of businesses reopenings, based on their easing of Covid restrictions. Some states, including Arkansas, Delaware and Mississippi, experienced over 65% of their total reopenings in just the last three months.

In addition to measuring the number of new businesses and business reopenings, Yelp's data also shows how consumer interests are changing and how demand was starting to return for some pre-pandemic activities in the first quarter. Yelp measures consumer interest by counting actions that users take on the site in order to connect with businesses.

The real estate and home improvement trends continued to look strong, with Yelp data showing that states saw a 90% increase in interest in real estate brokers, and a 100% increase in junk removal services. In most states, demand for handymen and electricians was also up.

"I think the trend we're seeing with rising consumer interest in home and local services will be dependent on where you live and how flexible companies are with allowing employees to work from home," Norman said.

"With recent headlines that more than half of all U.S. adults have received at least one Covid vaccine, it makes sense that people are still improving their homes," he added. "Americans are getting ready to get back to dinner parties, hosting indoor events, and a summer that will hopefully be better than the last."

Yelp also saw quarterly upticks in interest for some unique experiences and businesses. Interest in wineries increased over 300%. Some states saw a more than 700% increase in interest in international grocery stores. Certain states saw a 2,000% increase in interest in horseback riding. Missouri and Kansas saw a 200% uptick for interest in pickleball.

Yelp data also shows an 18% increase in consumer interest in fitness and exercise in Q1, Compared with a baseline of December 2020, interest in nail salons, motorcycle rentals and driving schools saw brief spikes but have leveled out. Yelp also saw interest in guns and ammunition spike in January, followed by a leveling out in later months in the quarter.

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Data Scientist: The best Job of 21st Century – – VENTS Magazine

The Harvard Business Review mentioned long back that Data Scientist is the sexiest job of this century. And the reason for that is as the billions of devices are hugely generating data, the need to manage data & infer from it is becoming essential. Furthermore, it is a high-paying field & also there are going to be numerous jobs in the coming future; hence the Harvard Business Review mentioned it so in their edition. So if you are looking to shift your career or begin your career and think of taking a Data Science Course, this article should be a must-read for you. Dont think twice; just grab your drink, sit back for a few minutes & read on!

What is Data?

Data is basically any information. It is a matter written on a piece of paper, calculations made on an article, a memory in the brain. Or it can be an image, a video, or an excel sheet. Basically Data is anything informative. Particularly, since the last two decades, the term Data is referred to as computer information. Specifically, the text files, audio files, video files, software, images & so on. And the study of this is taught in the Data Science course. Further, Data is being referred to as any computer information stored in the hard disk/RAM in the binary format i.e., 0s & 1s. Data in the field of science is broadly classified into two categories.

The Data is in organized form like the one that is produced in the excel sheets. Specifically, the row-column data. And a significantly less percentage of the data in the world is structured.

Basically, this is the unorganized Data. Specifically, the text files, images, audio files, video files, CSV files, etc., come under this category. Specifically, a large percentage of data of the world is unstructured. And a Data Science course mainly deals with collecting, analyzing & inferring from structured & unstructured data.

What is Data Science ?

Basically, Data Science is the study of vast volumes of data collected from text files, audio files, etc. Particularly, the heavy volume of Data is processed using modern techniques & tools, and valuable information is observed. And this information is used to make vital business decisions. Specifically, this study enhances pattern discovery & predictive analysis, which ultimately helps in making better decisions. And this is the core of any Data Science course.

Moreover, this has applications in almost every sector. And it may be Automobiles, Manufacturing, Textile, Software, Sports, Telecommunication, Electronics, Finance, Media, Marketing, Advertising, Entertainment, etc. Furthermore, Modern & high-quality algorithms are employed in inferring valuable information. The main aspects of DS are Analysis, Warehousing, and Visualization.

The primary tasks that Data Science allows are as follows:

Prerequisites to learn Data Science

Basically, to undergo a Data Analytics course , you need to have some specific skills/methodologies. And they are as follows.

Particularly, an adequate level of programming knowledge is necessary to learn this science. Basically, experience in any language is a good sign. And the languages may be C, C++, Java, Javascript, etc. Specifically, Python & R are feasible languages as they are very much used in DS & Machine Learning.

Basically, DS is more about tabulating the data, which are the results of many algorithms used in the study. Moreover, a good level of statistical knowledge gives a good start in this field. And if you are an expert or professional in statistics, then it becomes an added advantage. Furthermore, this allows extracting better intelligence & results from the Data. Lastly, most of the Data Science Course suggest you know at least the basics of Statistics.

Basically, the Database is the foundation of DS. The entire DS process begins with Databases. Moreover knowing any of the SQL or NoSQL is an added advantage. Languages like MySQL, NoSQL, MongoDB, PostgreSQL, Oracle, etc. are should & must to learn DS. Particularly, if you are from a software or computer applications background, it will be easier for you to pick up on them.

Mathematics is a critical factor in DS. And the mathematical models allow you to infer information from the Data which you already know. Moreover, the Mathematical model will enable you to select the appropriate algorithm to be applied to get the desired results. If you come from a mathematical background, then it will be an added advantage.

Basically, Machine Learning (ML) is said to be the backbone of DS. And having a good understanding of ML is a great plus point. And some of the Data Science Course teach ML in their curriculum.

What does a Data Scientist basically do ?

Basically, A Data Scientist analyzes the data & extracts meaningful insights to help make better business decisions. And this will be the core of any Data Science Course.

The basic steps that a Data Scientist takes are:

Conclusion

Finally, after looking at the various aspects of Data Science, we can conclude that Data Science is undoubtedly an exciting field. And DS in the coming years will be an inevitable aspect for any sector. Specifically, it is because DS enhances decision making which thereby accounts for increased profits. And we recommend you to take the suitable Data Science Courses that various institutes offer.

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7 Principles To Be Invincible In The Data Science World – Analytics Insight

In every industry today, data science is a hot topic. Rightfully so, because it is bringing industries like artificial intelligence, machine learning, big data, and data visualization to life. To be a successful data scientist, having the will to learn and unlearn is crucial. So if youre about to begin your data science career, these 7 mantras will help you stay steady through the big picture, and if youre an experienced professional, here are some tips you can include in your day-to-day data work.

If you start working on data, create models, and prepare descriptive analysis assuming the data is clean, you can come up with wrong hypotheses. Instead, looking for discrepancies in data can present a lot of important patterns. For example, if a column has more than 50% values missing, an analyst A will think about dropping the column. But if the same error was in a data collection instrument, spotting it would help the business improve. Finding out such errors will open opportunities for questions that might lead to a bigger picture.

In data science, one has to tell stories through data. The companys board of directors and stakeholders will be expecting statistics plans and insights from you which will only be understood by them if you ace effective visualization to show them your datas story and effective communication skills to narrate your opinions. When you spend a lot of time collecting, cleaning, exploring, and modeling data, finding interesting patterns and presenting it will mundane visualization will be ineffective.

Remember this, every business problem is different and it should be optimized differently. For example, if a client wants you to optimize for active users, you should judge better and advise him to optimize the percentage of active users instead to know how the clients product is performing. Having the right metric in place before modeling a data science project is crucial in getting accurate insights.

Embrace the scientific side of data, not just the technological side. According to Colin Melody, senior manager in data science at Deloitte, data science must remember the scientist part of their job. At all times, you are looking to provide evidence which supports an idea. This means, from end-to-end, you must challenge your assumptions, your data, test, and retest, refine, and start again. There is a myriad of tools and technologies available for data scientists and, while it is not necessary to know how to use all of them, try to get a sense of what it might take to grow your toolbox.

While youre mastering all the concepts needed to be a pro data scientist, master when to take your knowledge out. Data science is a field that has new and different advancements every day. There is a possibility that you wont know everything and waiting for it will not accomplish anything. The wait for know enough is not a constant factor. The term is too subjective to risk building a good project or apply for a role. So once your foundation is ready, be out there and apply your knowledge wherever possible.

Data science is not an independent field. That means data science is an interactive interdisciplinary field that depends on other fields like maths, statistics, and scientific learning. Any data science sub-field will require you to tap into machine learning, artificial intelligence, and NLP. So it is advisable to keep yourself up-to-date with everything surrounding the field, not just the bare minimum.

The data part of data science is obvious, but its also about the entire problem and the solution youre trying to find out. Understanding the needs of the end-user will help you solve the problem. It will not be easy at first, but with an inquisitive mind, ponder over the dataset and build the model step by step by understanding how the end result will interact with your model.

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Why the World Needs More Data Scientists and How Professionals Can Take Advantage of This Opportunity. – Influencive

Who is a Data Scientist?

The word data scientist is a recently familiarized term and refers to professionals who are adept at assimilating massive bulks of data, organizing them and finally analyzing themchunks of structured and unstructured data coming their way to be relieved.

The data scientists retrieve the data from the mass, process them, and model them into decipherable form and finally evaluate them to reproduce results employed by organizations and companies in their strategies and plan to survive in the market.

What is the job of a Data scientist?

The data scientists are professionals working for several organizations and firms who tackle heaves of unprocessed data, condense them into meaningful and applicable data and deliver them to the organization or firm which they implement in their functioning.

One of their chief jobs is to elucidate their technical evaluations and finding to their non-technical employers for this. They must be well versed in their zone of work, alongside being able to elaborate it properly with proper communication skills.

The umbrella of the data scientist houses several designations that functions in different sectors:

Data Scientist: It is the work of a data scientist to seek the pertinent question and the answers for the same all, in the form of data. That is then structured into information by them and communicated to the data Analysts who delineates it to the organization, which further discusses them with the stakeholders of their institutions and makes decisions for their businesss growth and regulation.

Data Analyst: A data analysts functions bridge the gap between that of a data scientist and a business analyst. They receive the question from the firms and organizations as well as the technical findings for the same; their work is to analyze and evaluate the crude technical data and formulate results that can be utilized as business strategies. They are the translators and commuters of the technical findings from the data scientists to practical strategies and actions.

Data Engineer: They are the observers of data the change in it, the fluctuations, evolutions, advancements and alterations in the concerned data. The information regarding the data is engineered and channelized by them to the Data scientists, who further start working with the new data.

What are some of the basic skills necessary for a Data scientist to have?ProgrammingRisk AnalysisEffective communication skillsGood Research abilities

There are a large number of skilled data scientists emerging. Lately, prospective students often have mentions of several courses and diplomas on data science in their CVs Data Science Courses in Delhi, from institutes like Madrid Software, or similar create very good impressions about the students on the employers alongside their skills.

How are some ways in which the data scientist can help professionals with their work?

Detection of which is fraud and which is risky from the associations that an organization or firm plans to indulge in is a vital job that the data scientist masters. They provide their valuable suggestions to the firms, who get careful about their association this saves them from losses, bad reputation, and cheats, thereby uplifting their business. Lately, the data scientists have had major contributions in regions of augmented reality.

The professionals, who are willing to up their names in the market by including evolved and developed technologies in their business and functioning, can benefit from a data scientists works. Another area of expertise of the data scientists have been in the field of gaming. Thereby, the professionals can inherit valuables from the data scientists in the field of gaming too.

The professionals in the industry of drug development can benefit a lot from the data scientists because drug dealing involves a lengthy and complex procedure that can be simplified by a data scientist capable of condensing the work into an easier procedure with their advanced technological functioning and mechanisms.Thereby, the data scientists are a very crucial organ for professional firms, who want more work in lesser time.

Published April 17th, 2021

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