As the world entered the era of big data, the need for its storage also grew. It was the main challenge and concern for the enterprise industries until 2010. The main focus was on building a framework and solutions to store data. Now when Hadoop and other frameworks have successfully solved the problem of storage, the focus has shifted to the processing of this data. Data Science is the secret sauce here. All the ideas which you see in Hollywood sci-fi movies can actually turn into reality by Data Science. Data Science is the future of Artificial Intelligence. Therefore, it is very important to understand what is Data Science and how can it add value to your business.

In this blog, I will be covering the following topics.

By the end of this blog, you will be able to understand what is Data Science and its role in extracting meaningful insights from the complex and large sets of data all around us.To get in-depth knowledge on Data Science, you can enroll for live Data Science Certification Training by Edureka with 24/7 support and lifetime access.

Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. But how is this different from what statisticians have been doing for years?

The answer lies in the difference between explaining and predicting.

As you can see from the above image, a Data Analyst usually explains what is going on by processing history of the data. On the other hand, Data Scientist not only does the exploratory analysis to discover insights from it, but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future. A Data Scientist will look at the data from many angles, sometimes angles not known earlier.

So, Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning.

Lets see how the proportion of above-described approaches differ for Data Analysis as well as Data Science. As you can see in the image below, Data Analysis includes descriptive analytics and prediction to a certain extent. On the other hand, Data Science is more about Predictive Causal Analytics and Machine Learning.

Now that you know what exactly is Data Science, let now find out the reason why it was needed in the first place.

This is not the only reason why Data Science has become so popular. Lets dig deeper and see how Data Science is being usedin various domains.

Lets have a look at the below infographic to see all the domains where Data Science is creating its impression.

There are several definitions available on Data Scientists. In simple words, a Data Scientist is one who practices the art of Data Science. The term Data Scientist has been coined after considering the fact that a Data Scientist draws a lot of information from the scientific fields and applications whether it is statistics or mathematics.

Data scientists are those who crack complex data problems with their strong expertise in certain scientific disciplines. They work with several elements related to mathematics, statistics, computer science, etc (though they may not be an expert in all these fields). They make a lot of use of the latest technologies in finding solutions and reaching conclusions that are crucial for an organizations growth and development. Data Scientists present the data in a much more useful form as compared to the raw data available to them from structured as well as unstructured forms.

To know more about a Data Scientist you can refer to this article on Who is a Data Scientist?

Moving further, lets now discuss BI. I am sure you might have heard of Business Intelligence (BI) too. Often Data Science is confused with BI. I will state some concise and clear contrasts between the two which will help you in getting a better understanding. Lets have a look.

Lets have a look at some contrasting features.

( logs, cloud data, SQL, NoSQL, text)

This was all about what is Data Science, now lets understand the lifecycle of Data Science.

A common mistake made in Data Science projects is rushing into data collection and analysis, without understanding the requirements or even framing the business problem properly. Therefore, it is very important for you to follow all the phases throughout the lifecycle of Data Science to ensure the smooth functioning of the project.

Here is a brief overview of the main phases of the Data Science Lifecycle:

Phase 1Discovery:Before you begin the project, it is important to understand the various specifications, requirements, priorities and required budget. You must possess the ability to ask the right questions.Here, you assess if you have the required resources present in terms of people, technology, time and data to support the project.In this phase, you also need to frame the business problem and formulate initial hypotheses (IH) to test.

Phase 2Data preparation:In this phase, you require analytical sandbox in which you can perform analytics for the entire duration of the project.You need to explore, preprocess and condition data prior to modeling. Further, you will perform ETLT (extract, transform, load and transform) to get data into the sandbox.Lets have a look at the Statistical Analysis flow below.

You can use R for data cleaning, transformation, and visualization. This will help you to spot the outliers and establish a relationship between the variables.Once you have cleaned and prepared the data, its time to do exploratory analytics on it. Lets see how you can achieve that.

Phase 3Model planning:Here, you will determine the methods and techniques to draw the relationships between variables.These relationships will set the base for the algorithms which you will implement in the next phase.You will apply Exploratory Data Analytics (EDA) using various statistical formulas and visualization tools.

Lets have a look at various model planning tools.

Although, many tools are present in the market but R is the most commonly used tool.

Now that you have got insights into the nature of your data and have decided the algorithms to be used. In the next stage, you will apply the algorithm and build up a model.

Phase 4Model building: In this phase, you will develop datasets for training and testing purposes. Here you need to consider whether your existing tools will suffice for running the models or it will need a more robust environment (like fast and parallel processing).You will analyze various learning techniques like classification, association and clustering to build the model.

You can achieve model building through the following tools.

Phase 5Operationalize:In this phase, you deliver final reports, briefings, code and technical documents.In addition, sometimes a pilot project is also implemented in a real-time production environment. This will provide you a clear picture of the performance and other related constraints on a small scale before full deployment.

Phase 6Communicate results:Now it is important to evaluate if you have been able to achieve your goal that you had planned in the first phase. So, in the last phase, you identify all the key findings, communicate to the stakeholders and determine if the results of the project are a success or a failure based on the criteria developed in Phase 1.

Now, I will take a case study to explain you the various phases described above.

What if we could predict the occurrence of diabetes and take appropriate measures beforehand to prevent it?In this use case, we will predict the occurrence of diabetes making use of the entire lifecycle that we discussed earlier. Lets go through the various steps.

Step 1:

Attributes:

Step 2:

This data has a lot of inconsistencies.

Step 3:

Now lets do some analysis as discussed earlier in Phase 3.

Step 4:

Now, based on insights derived from the previous step, the best fit for this kind of problem is the decision tree. Lets see how?

Lets have a look at our decision tree.

Here, the most important parameter is the level of glucose, so it is our root node. Now, the current node and its value determinethe next important parameter to be taken. It goes on until we get the result in terms of pos or neg. Pos means the tendency of having diabetes is positive and neg means the tendency of having diabetes is negative.

If you want to learn more about the implementation of the decision tree, refer this blog How To Create A Perfect Decision Tree

Step 5:

In this phase, we will run a small pilot project to check if our results are appropriate. We will also look for performance constraints if any. If the results are not accurate, then we need to replan and rebuild the model.

Step 6:

Once we have executed the project successfully, we will share the output for full deployment.

Being a Data Scientist is easier said than done. So, lets see what all you need to be a Data Scientist. A Data Scientist requires skills basicallyfrom three major areas as shown below.

As you can see in the above image, you need to acquire various hard skills and soft skills. You need to be good at statistics and mathematics to analyze and visualize data. Needless to say, Machine Learning forms the heart of Data Science and requires you to be good at it. Also, you need to have a solid understanding of the domain you are working in to understand the business problems clearly. Your task does not end here. You should be capable of implementing various algorithms which requiregood coding skills. Finally, once you have made certain key decisions, it is important for you to deliver them to the stakeholders. So, good communication will definitely add brownie points to your skills.

I urge you to see this Data Science video tutorial that explains what is Data Science and all that we have discussed in the blog. Go ahead, enjoy the video and tell me what you think.

What Is Data Science? Data Science Course Data Science Tutorial For Beginners | Edureka

This Edureka Data Science course video will take you through the need of data science, what is data science, data science use cases for business, BI vs data science, data analytics tools, data science lifecycle along with a demo.

In the end, it wont be wrong to say that the future belongs to the Data Scientists. It is predicted that by the end of theyear 2018, there will be a need of around one million Data Scientists. More and more data will provide opportunities to drive key business decisions. It is soon going to change the way we look at the world deluged with data around us.Therefore, a Data Scientist should be highly skilled and motivated to solve the most complex problems.

l hope you enjoyed reading my blog and understood what is Data Science.Check out our Data Science certification traininghere, that comes with instructor-led live training and real-life project experience.

Original post:

What Is Data Science? A Beginner's Guide To Data Science ...

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.

discoverdatascience.org is an advertising-supported site. Clicking in this box will show you programs related to your search from schools that compensate us. This compensation does not influence our school rankings, resource guides, or other information published on this site. Got it!

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

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.

View original content to download multimedia:http://www.prnewswire.com/news-releases/jg-wentworth-hires-senior-vp-of-analytics-and-data-science-to-lead-their-digital-evolution-301272699.html

SOURCE The JG Wentworth Company

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

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

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