Data Science Certificate Online

Enhance your real-world programming competencies to solve problems and build applicable career-ready skills in our online Data Science Certificate program.

Apply by: 5/6/24
Start classes: 5/20/24
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Program Overview

Here is what you need to know about this online Data Science Certificate

Total Tuition: $15,225
Program Duration: As few as 11 Months
Credit Hours: 15

Design IT solutions for a variety of real-world problems with the insight and experience of multiple platform types you will gain in our online Data Science Certificate program. Designed for working adults, this flexible, fast-paced program imparts coding skills and a mix of statistical analysis and data preparation experience in presenting visual results.

This certificate offers a broad study of data science, including mobile development, database services, enterprise and web solutions, and demonstrates how these systems integrate and work together. With a projected high demand for computer and information technology knowledge, a Data Science Certificate is a valuable asset for any IT job seeker as companies increasingly rely on cloud computing, big data and information security. Coursework can also be applied toward a master’s degree.

In this online Data Science Certificate program, you will learn how to:

  • Explain data relationships based on real-world variables
  • Use statistical methods to develop data models
  • Construct and transform views of relevant data sources based on independent variables
  • Prepare data learning based on data views
  • Explain data relationships based on real-world variables
  • Use statistical methods to develop data models
  • Construct and transform views of relevant data sources based on independent variables
  • Prepare data learning based on data views

Online technology programs also available:

La Salle University offers a variety of specialized technology programs. Check out all of our technology online programs.

Total Tuition: $15,225
Program Duration: As few as 11 Months
Credit Hours: 15
Need More Information?

Call 844-466-5587

Call 844-466-5587

Tuition

Find out how easy it is to pay for this career-boosting certificate

Our Data Science Certificate online program offers affordable, pay-by-the-course tuition which is the same for in-state and out-of-state students. All program and course fees are included in the total tuition cost.

Tuition breakdown:

Total Tuition: $15,225
Per Credit Hour: $1,015

Tuition breakdown:

Total Tuition: $15,225
Per Credit Hour: $1,015

Calendar

There is sure to be a start date that works for you

La Salle University online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.

Now enrolling:

Next Apply Date: 5/6/24
Next Class Start Date: 5/20/24
TermStart DateApp DeadlineDocument DeadlineRegistration DeadlineTuition DeadlineClass End DateTerm Length
Spring II3/18/243/4/243/8/243/8/243/14/245/9/248 weeks
Summer I5/20/245/6/245/10/245/10/245/16/247/14/248 weeks
Fall I8/26/248/12/248/16/248/16/248/22/2410/20/248 weeks
Fall II10/21/2410/7/2410/11/2410/11/2410/17/2412/15/248 weeks

Now enrolling:

Next Apply Date: 5/6/24
Next Class Start Date: 5/20/24

Have questions or need more information about our online programs?

Ready to take the rewarding path toward earning your degree online?

Admissions

These simple steps are all you need to apply for this Data Science Certificate

Applications for the Data Science Certificate are evaluated on a holistic basis. The Admissions Committee takes into account interest, aptitude and potential for achievement in graduate studies. The requirements include:

Admission Requirements:

  • Bachelor’s degree from an accredited institution
  • Minimum 3.0 GPA*
  • No GMAT required

Prior to evaluation by the Admissions Committee, applicants must submit the following:

  • Transcript(s) from the college/university where you earned your bachelor’s degree and, if applicable, master’s degree. You will be notified if you need to submit additional transcripts for advising purposes.
  • Minimum 3.0 GPA*
  • No GMAT/GRE required
  • A current professional resume
  • Provide a personal statement (about 500 words in length) explaining why you are interested in this program, your qualifications and how this program will assist with your professional goals

Documentation can be sent via email to [email protected]. If you need to submit official documents by mail, send them to:

La Salle University
Office of Adult Enrollment
Box 112
1900 West Olney Avenue
Philadelphia, PA 19141

Have a question? Call us at 844-466-5587.

Courses

Explore the Data Science Certificate’s career-relevant curriculum

For the Data Science Certificate online, the curriculum is comprised of a maximum of five courses (15 credit hours)—depending on prior academic and professional experience.

Duration: 8 weeks
Credit Hours: 3
This course entails analysis and evaluation of database designs in relation to the strategic mission of the project. Topics include database systems, database architectures, and data-definition and data-manipulation languages. Also included are logical and physical database design, database models (e.g., entity-relationship, relational), normalization, integrity, query languages including SQL, and relational algebra, in addition to social and ethical considerations and privacy of data. This course incorporates case studies and a project using a relational DBMS.
Duration: 8 weeks
Credit Hours: 3
This course introduces the field of data mining, with specific emphasis on its use for Machine Learning algorithms. Techniques covered may include conceptual clustering, learning decision rules and decision trees, case-based reasoning, Bayesian analysis, genetic algorithms, and neural networks. The course covers data preparation and analysis of results. Skills in Microsoft Excel are useful.
Duration: 8 weeks
Credit Hours: 3
This course will require students to learn the R programming language and assess how to use it and find interesting features in data. Students will learn about R and statistical best practices and how to display data in a manner that will help you explain your findings to those who do not have a technical background. Moreover, the course introduces students to modeling and simulation. Topics may include basic queueing theory, the role of random numbers in simulations, and the identification of input probability distributions.
Duration: 8 weeks
Credit Hours: 3
This course introduces students to the field of artificial intelligence (AI). Students will learn how big data and data mining techniques are utilized by machines to create the AI models used by autonomous aircraft and automobiles, personal assistants, IT security software, fraud investigations and credit bureaus. The course will review the history, present day use, and future of artificial intelligence. Through case studies and current events, students will examine the benefits and risks associated with AI. The course will cover issues related to AI and privacy, ethics, and machine bias. Neuromorphic computing, the Open Neural Network Exchange (ONNX), and data analytics will also be discussed.
Choose one of the courses below.

Note: BSA courses may also be used to satisy the elective requirement. For more information, please consult with your advisor.
Duration: 8 weeks
Credit Hours: 3
An introduction to the essential principles of descriptive and inferential statistics needed for effective data analysis and decision making. Applications and case studies using realistic data will be used to demonstrate how statistical methodology is used to generate predictions necessary for decisions via data collection, statistical analysis and interpretation. Topics include applied probability, probability distributions, sampling, estimation, confidence intervals, hypothesis testing, linear and multiple regression, analysis of variance, and model building. Technology, including spreadsheets and dedicated statistical software, will be employed where appropriate. Number of Credits: 3
Duration: 8 weeks
Credit Hours: 3
This course introduces students to mathematical models that can be employed to make informed decisions in a wide variety of data-driven fields, including (but not limited to) finance, banking, marketing, health care, retail, manufacturing, and transportation. Goals such as increasing revenue, decreasing costs, and improving overall efficiency of operations in the face of various constraints are considered. Students learn to recognize when a problem lends itself to a particular type of model, formulate the model, and use appropriate methods to solve or extract information from the model. Particular emphasis is placed on linear programming (with exposure to network models and integer programs) and the simplex method. Forecasting, inventory management, and queueing models, as well as Markov chains, are also studied. Additional topics covered include sensitivity analysis, duality, decision analysis, and dynamic programming. Software (both spreadsheets and a computer algebra system) is employed consistently throughout the course to expedite the solution and analysis process; emphasis will be placed on the practical application of models rather than on the models' mathematical properties.
Duration: 8 weeks
Credit Hours: 3
This course focuses on the development of Web services for use by many different types of Web applications. The course develops basic programming techniques to implement the server side function of the application. The course uses a non-Windows interface for the tools set.
Duration: 8 weeks
Credit Hours: 3
This course encompasses programming models that support database access, including ADO.NET. It covers client/server and multitiered architectures; development of database applications; Internet and intranet database design and implementation; database-driven Web sites; and use of XML syntax related to databases. Examples of the possible tool sets for this tool set are PHP and mySQL on either a Linux or Windows server. The course also considers privacy of data and data protection on servers.

La Salle University is ranked in the top 50 percent of national universities nationwide by U.S. News & World Report (2023).

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