Learn more about the Bachelor of Science in Data Science.

Data Science is an interdisciplinary field of study about methods and systems to extract knowledge or insights from large quantities of data coming in various forms. Temple's B.S. in Data Science is designed for students interested in developing expertise in data science. The Computation and Modeling concentration provides the tools necessary to create accurate, robust, and detailed models of real systems in a scientific or professional field. A strong core of mathematics, physics, computational methods and techniques, and data analysis will enable students to model any complex physical system. Elective courses will allow students to specialize in a specific area of interest.

Undergraduate Contact Information:

Department of Computer and Information SciencesDr. Jamie Payton, ChairScience Education and Research Center, Room 304215-204-8450

Dr. Gene Kwatny, Vice ChairScience Education and Research Center, Room 304215-204-8450

Dr. Anthony Hughes, Faculty AdvisorScience Education and Research Center, Room 344215-204-7910anthony.hughes@temple.edu

Department of PhysicsDr. Bernd Surrow, ChairScience Education and Research Center, Room 406215-204-7736

Dr. Adrienn Ruzsinszky, Vice ChairScience Education and Research Center, Room 708215-204-8479

Dr. Matthew Newby, Faculty AdvisorScience Education and Research Center, Room 476215-204-2642matthew.newby@temple.edu

Students must complete all University requirements including those listed below.

All Temple students must take a minimum of two writing-intensive courses at Temple as part of their major. The specific writing-intensive course options for this major are:

45 Upper Level (2000+) credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), or the College of Engineering (ENG).

90 credits within the College of Science & Technology (CST), the College of Liberal Arts (CLA), or the College of Engineering (ENG).

All students in the College of Science and Technology are required to take a one credit first year seminar. SCTC1001 CST First Year Seminar is the appropriate course option for every entering first year CST major. Transfer students should use SCTC2001 CST Transfer Seminar to fulfill this requirement. Other courses that fulfill this requirement may be found on the CST College Requirements page.

Courses listed under the major requirements for the degree will be included in the calculation of the major GPA. Courses that could not apply toward the major as an elective or a required course are not counted in the calculation of the major GPA.

To graduate with Distinction in Major, students are required to have a 3.50 or higher grade point average (GPA) both in the major and overall, as well as be recommended by the department of Computer & Information Sciences.

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Data Science with Concentration in Computation and Modeling, B.S ...

Gain the skills to transform data into insights and to advance your career in a fast-paced, growing industry with the Master of Science in Business Analytics at Temples Fox School of Business. With its market-driven, customizable curriculum, this program focuses on explanation, interpretation and deep knowledge of data analytics, training translators able to move fluidly from data to decisions and from decisions to profit.

Data-driven decision-making results in positive outcomes for organizations, and the Business Analytics MSleverages the ever-increasing importance of data as a strategic asset. Through case studies, coursework and real-world projects, you will acquire advanced skills and techniques that can provide data-driven insights into business problems.

Business Analytics MS graduates are prepared to meet the growing demand for talent in the data science space: analyzing, deriving, discovering, managing and predicting insights from the complex data available to modern corporations. Shape your ideal career through this flexible degree program, which is offered via classes at Temples Center City Campus.

The Master of Science in Business Analytics will equip you with the knowledge and practical expertise to make an immediate impact on your career and set you on the path to long-term professional success.

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Business Analytics MS | Temple University

COLLEGE OF SCIENCE AND TECHNOLOGY

Learn more about the Professional Science Master's in Bioinformatics and Biological Data Science.

Bioinformatics and Biological Data Science are the disciplines of science where computers are joined with the latest discoveries in genomics, biochemistry and biophysics. These rapidly growing fields bring together elements of biology, chemistry, computer science, physics and statistics. The Bioinformatics and Biological Data Science degree at Temple University, a leader in the field, is a two-year Professional Science Masters (PSM) degree that features:

Time Limit for Degree Completion: 2 years

Campus Location: Main

Full-Time/Part-Time Status: The degree program can be completed on a full- or part-time basis. Most of the classes are offered in the evenings or on weekends to enable full-time working professionals to be enrolled in the program.International students are required to register as full-time students.

Interdisciplinary Study: Students in the Temple University Bioinformatics and Biological Data Science masters degree program benefit from an advanced curriculum developed by leading Temple faculty in the Departments of Biology, Chemistry, and Computer and Information Sciences. The program has been designed to provide students with extensive skills in computer programming as well as deep knowledge in genomics and structural biology. All three areas are required in this challenging and exciting field. Because the degree is a Professional Science Master's, the program also offers:

Accreditation: Temple University is fully accredited by the Middle States Commission on Higher Education.

Areas of Specialization: The PSM degree program offers concentrations in:

Students selecting a concentration are required to take the two courses (6 credits) listed under the chosen concentration on the Program Requirements grid. Students may also opt to take one course from each concentration and thereby complete the requirements for the degree without a transcripted concentration.

Job Prospects: Official job placement is not offered, but Bioinformatics and Biological Data Science are areas of rapid job growth and have become essential parts of healthcare research and the biotechnology and pharmaceutical industries. Graduates of PSM programs are in high demand, underscoring the PSM as an attractive career path for those who do not wish to become academic researchers or pursue a doctorate.

Non-Matriculated Student Policy: Non-matriculated students may enroll in a total of three courses (9 credits) with permission of the instructor and the Biology Department.

Financing Opportunities: Financial assistance in the form of Research or Teaching Assistantships is not offered at this time.

Application Deadline:

Fall: March 1; December 15 international

Late applications may be considered for admission.

APPLY ONLINE to this graduate program.

Letters of Reference:Number Required: 2

From Whom: Letters should be obtained from college/university faculty or faculty who are familiar with the applicant's competency. If the applicant has an established career in a related field, the applicants immediate supervisor should provide one of the letters.

Coursework Required for Admission Consideration: Applicants should have a strong background in one or more STEM fields: Science, Technology, Engineering and Mathematics.

Bachelor's Degree in Discipline/Related Discipline: The Bioinformatics and Biological Data Science PSM program has been designed for recent graduates and professionals who have a bachelor's degree or equivalent in a STEM field.

Statement of Goals: In approximately 500 to 1,000 words, specify your interest in the Bioinformatics and Biological Data Science PSM program, career goals, and academic and professional achievements.

Standardized Test Scores:GRE: Required. A combined minimum score of 305 on the quantitative and verbal reasoning sections is expected.

Applicants who earned their baccalaureate degree from an institution where the language of instruction was other than English, with the exception of those who subsequently earned a masters degree at a U.S. institution, must report scores for a standardized test of English that meet these minimums:

Interview: An in-person or SKYPE interview is required.

Transfer Credit: Graduate credits from an accredited institution may be transferred into the Bioinformatics and Biological Data Science PSM program. The credits must be equivalent to coursework offered by the Biology Department at Temple University. A grade of "B" or better must have been earned for the credits to transfer. The PSM in Bioinformatics and Biological Data Science Steering Committee makes recommendations to the Department Chair for transferring credit on an individual basis. The maximum number of credits a student may transfer is 6.

General Program Requirements:Number of Credits Required Beyond the Baccalaureate:30

Required Courses:

Culminating Events:Capstone Project:BIOL9995Capstone Project constitutes a culminating event of the Bioinformatics and Biological Data Science PSM and requires the submission of a written project and oral presentation of the results. Capstone research may be completed in any laboratory at Temple University at the invitation of the Principal Investigator (PI) or through an internship/co-op/full-time job in the field of Bioinformatics or Biological Data Science in industry, the healthcare system, or a government agency. Since all Bioinformatics and Biological Data Science PSM classes are offered in the evening, students can avail themselves of these opportunities during the day. The process of locating internships is facilitated by the Bioinformatics and Biological Data Sciences PSM program based on the choice of optional concentration, specific research and career interests of the individual student.

Link:

Bioinformatics and Biological Data Science PSM

Data Science is an interdisciplinary field that focuses on extracting knowledge from data sets which are typically huge in amount. The field encompasses analysis, preparing data for analysis, and presenting findings to inform high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic, and business.

Data is everywhere and is one of the most important features of every organization that helps a business to flourish by making decisions based on facts, statistical numbers, and trends. Due to this growing scope of data, data science came into picture which is a multidisciplinary IT field, and data scientists jobs are the most demanding in the 21st century. Data analysis/ Data science helps us to ensure we get answers for questions from data. Data science, and in essence, data analysis plays an important role by helping us to discover useful information from the data, answer questions, and even predict the future or the unknown. It uses scientific approaches, procedures, algorithms, the framework to extract the knowledge and insight from a huge amount of data.Data science is a concept to bring together ideas, data examination, Machine Learning, and their related strategies to comprehend and dissect genuine phenomena with data. It is an extension of data analysis fields such as data mining, statistics, predictive analysis. It is a huge field that uses a lot of methods and concepts which belong to other fields like in information science, statistics, mathematics, and computer science. Some of the techniques utilized in Data Science encompasses machine learning, visualization, pattern recognition, probability model, data engineering, signal processing, etc.Few important steps to help you work more successfully with data science projects:

Data scientists straddle the world of both business and IT and possess unique skill sets. Their role has assumed significance thanks to how businesses today think of big data. Business wants to make use of the unstructured data which can boost their revenue. Data scientists analyze this information to make sense of it and bring out business insights that will aid in the growth of the business.

Now, lets get started with the foremost topic i.e., Python Packages for Data Science which will be the stepping stone to start our Data Science journey. A Python library is a collection of functions and methods that allow us to perform lots of actions without writing any code.1. Scientific Computing Libraries:

2. Visualization Libraries:

3. Algorithmic Libraries:

{data: array([[ 0., 0., 5., , 0., 0., 0.],[ 0., 0., 0., , 10., 0., 0.],[ 0., 0., 0., , 16., 9., 0.],,[ 0., 0., 1., , 6., 0., 0.],[ 0., 0., 2., , 12., 0., 0.],[ 0., 0., 10., , 12., 1., 0.]]), target: array([0, 1, 2, , 8, 9, 8]), target_names: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), images: array([[[ 0., 0., 5., , 1., 0., 0.],[ 0., 0., 13., , 15., 5., 0.],[ 0., 3., 15., , 11., 8., 0.],,[ 0., 4., 11., , 12., 7., 0.],[ 0., 2., 14., , 12., 0., 0.],[ 0., 0., 6., , 0., 0., 0.]],[[ 0., 0., 0., , 5., 0., 0.],[ 0., 0., 0., , 9., 0., 0.],[ 0., 0., 3., , 6., 0., 0.],,[ 0., 0., 1., , 6., 0., 0.],[ 0., 0., 1., , 6., 0., 0.],[ 0., 0., 0., , 10., 0., 0.]],[[ 0., 0., 0., , 12., 0., 0.],[ 0., 0., 3., , 14., 0., 0.],[ 0., 0., 8., , 16., 0., 0.],,[ 0., 9., 16., , 0., 0., 0.],[ 0., 3., 13., , 11., 5., 0.],[ 0., 0., 0., , 16., 9., 0.]],,[[ 0., 0., 1., , 1., 0., 0.],[ 0., 0., 13., , 2., 1., 0.],[ 0., 0., 16., , 16., 5., 0.],,[ 0., 0., 16., , 15., 0., 0.],[ 0., 0., 15., , 16., 0., 0.],[ 0., 0., 2., , 6., 0., 0.]],[[ 0., 0., 2., , 0., 0., 0.],[ 0., 0., 14., , 15., 1., 0.],[ 0., 4., 16., , 16., 7., 0.],,[ 0., 0., 0., , 16., 2., 0.],[ 0., 0., 4., , 16., 2., 0.],[ 0., 0., 5., , 12., 0., 0.]],[[ 0., 0., 10., , 1., 0., 0.],[ 0., 2., 16., , 1., 0., 0.],[ 0., 0., 15., , 15., 0., 0.],,[ 0., 4., 16., , 16., 6., 0.],[ 0., 8., 16., , 16., 8., 0.],[ 0., 1., 8., , 12., 1., 0.]]]), DESCR: .. _digits_dataset:nnOptical recognition of handwritten digits datasetnnn**Data Set Characteristics:**nn :Number of Instances: 5620n :Number of Attributes: 64n :Attribute Information: 88 image of integer pixels in the range 0..16.n :Missing Attribute Values: Nonen :Creator: E. Alpaydin (alpaydin @ boun.edu.tr)n :Date: July; 1998nnThis is a copy of the test set of the UCI ML hand-written digits datasetsnhttps://archive.ics.uci.edu/ml/datasets/Optical+Recognition+of+Handwritten+DigitsnnThe data set contains images of hand-written digits: 10 classes whereneach class refers to a digit.nnPreprocessing programs made available by NIST were used to extractnnormalized bitmaps of handwritten digits from a preprinted form. From antotal of 43 people, 30 contributed to the training set and different 13into the test set. 3232 bitmaps are divided into nonoverlapping blocks ofn4x4 and the number of on pixels are counted in each block. This generatesnan input matrix of 88 where each element is an integer in the rangen0..16. This reduces dimensionality and gives invariance to smallndistortions.nnFor info on NIST preprocessing routines, see M. D. Garris, J. L. Blue, G.nT. Candela, D. L. Dimmick, J. Geist, P. J. Grother, S. A. Janet, and C.nL. Wilson, NIST Form-Based Handprint Recognition System, NISTIR 5469, n1994.nn.. topic:: Referencesnn C. Kaynak (1995) Methods of Combining Multiple Classifiers and Theirn Applications to Handwritten Digit Recognition, MSc Thesis, Institute ofn Graduate Studies in Science and Engineering, Bogazici University.n E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika.n Ken Tang and Ponnuthurai N. Suganthan and Xi Yao and A. Kai Qin.n Linear dimensionalityreduction using relevance weighted LDA. School ofn Electrical and Electronic Engineering Nanyang Technological University.n 2005.n Claudio Gentile. A New Approximate Maximal Margin Classificationn Algorithm. NIPS. 2000.}

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What is Data Science? - GeeksforGeeks

Convergence of data science with education sector is phenomenal, says expert  The Hindu

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Convergence of data science with education sector is phenomenal, says expert - The Hindu