Data Analytics Certificate Online
Gain the hands-on experience and technical skillset critical to the burgeoning field of data analytics. This certificate program quickly prepares you to be a valuable contributor in any organization.
Program Overview
Preview the benefits of this online data analytics certificate program
Providing a direct pathway to an in-demand sector, the online Data Analytics Certificate gives you project-based experience in database fundamentals, programming, visualization, mining and business intelligence. Quickly gain familiarity with Advanced Excel for Analytics, Tableau, SAS, Python, R, SQL, SAP and Oracle, and develop a work portfolio to show future employers.
This AACSB-accredited, STEM-designated program is ideal for high school graduates seeking a fast entry into data analytics and college graduates who want to expand their value. Build on the skills learned in this program by sitting for the respected Oracle Certification exam or transfer credits toward the BBA in Management Information Systems online.
In this online data analytics program, you will:
- Design and implement databases using modeling tools and SQL
- Apply industry-standard spreadsheet software for modeling
- Gain fundamental programming knowledge
- Apply data storytelling for managerial decision-making
- Gain practical experience with various data analysis tools
- Design and implement databases using modeling tools and SQL
- Apply industry-standard spreadsheet software for modeling
- Gain fundamental programming knowledge
- Apply data storytelling for managerial decision-making
- Gain practical experience with various data analysis tools
Potential careers in data analytics include:
- Data Analyst
- Market Research Analyst
- Business Analyst
- Data Specialist
- Data Analyst
- Market Research Analyst
- Business Analyst
- Data Specialist
Also available:
Lamar University offers a variety of undergraduate degree options. Check out our other online undergraduate programs.
Accreditation
The Lamar University College of Business offers you access to a powerful business school alumni network and a business education backed by AACSB International accreditation – the gold standard of quality in business education worldwide.
Tuition
Save time and money with this online program
The following is the tuition breakdown for students pursuing the Data Analytics Certificate online. Our tuition is affordable and can be paid by the course.
| Program | Per Credit Hour | Per Course | Per Program* |
|---|---|---|---|
| Data Analytics Certificate | $314 | $942 | $5,652 |
* University fees are included in the tuition listed. University fees are able to be covered by Financial Aid if you choose to apply and are qualified.
Tuition and fees are subject to change without notice due to action by the Board of Regents or the Texas State Legislature.
Total program cost depends upon transfer hours and program advisement relevant to program requirements. For more information, contact a Lamar University enrollment specialist.
Financial Aid
Ready to get started on your degree program online but need help finding ways to fund your education? We can help you discover student financing sources that include grants, loans and other payment options. Learn more about financial aid here.
Tuition breakdown:
Calendar
Start soon and finish quickly
Our Data Analytics Certificate features multiple start dates to accommodate your busy schedule. Find the start date that works best for you and apply before the application deadline associated with it.
| 8 week courses | Program Start Date | Application Deadline | Document Deadline | Payment Due | Last Class Day |
|---|---|---|---|---|---|
| Spring I | 1/16/25 | 12/26/24 | 1/2/25 | 1/7/25 | 3/7/25 |
| Spring II | 3/17/25 | 2/24/25 | 3/3/25 | 3/10/25 | 5/7/25 |
| Summer I | 5/29/25 | 5/8/25 | 5/15/25 | 5/20/25 | 7/31/25 |
| Fall 1 | 8/21/25 | 8/7/25 | 8/7/25 | 8/15/25 | |
| Fall 2 | 9/29/25 | 9/15/25 | 9/15/25 | 9/23/25 |
Now enrolling:
Have questions or need more information about our online programs?
Ready to take the rewarding path toward earning your degree online?
Admissions
Follow these steps to apply to the data analytics cert
The online certificate in data analytics has specific requirements that applicants must meet to enroll. Please read the admission guidelines to ensure you qualify.
Admission Requirements:
- Online Application
- Official Transcripts
All applicants must complete an application packet, consisting of:
- Complete online application and pay an application fee of $25
- Submit official transcripts from all high schools, colleges and universities you have attended
- Verify specific requirements associated with chosen degree program
High school graduates who have not attended college before are considered entering freshmen – even if they received college credit while in high school through dual credit, AP or IB programs. Transfer students with fewer than 18 hours of college credit also must meet admission requirements for entering freshmen.
Incoming freshmen must do the following to qualify for unconditional admission to Lamar University:
- Receive a diploma from an accredited high school
- Complete at least 14 high school credits in college preparatory courses: 4 credits in English, 3 credits in mathematics, 2 credits in laboratory sciences, 2.5 credits in social sciences (U.S. history, U.S. government, and world history or world geography) and 2.5 credits in college preparatory electives (preferably including 2 credits of foreign language)
- Meet the test-optional admission criteria, or achieve a minimum composite score on the ACT or SAT through the secondary review criteria. (Click here for criteria)
- Submit your high school transcripts via Trex, Speedy, Escript or as a PDF from your high school counselor to [email protected].
Students transferring from other Lamar University programs into a College of Business program must have a minimum overall 2.0 grade point average (GPA) and, if applicable, a minimum 2.0 GPA in business courses.
Students transferring from other colleges or universities into a College of Business program must:
- Have an official copy of all college and/or university transcripts on file by application deadline
- Be eligible to re-enter all colleges and/or universities previously attended
- Have a cumulative GPA of at least 2.0 on a 4.0 scale for all work attempted
- Students who transfer fewer than 18 hours must also submit and meet the entrance credentials and requirements of a first-time college student
Send all required documents to:
Lamar University Online Admissions
PO Box 10017
Beaumont, TX 77710
OR
Submit electronically to [email protected]
Check to see if the program is offered to residents in your state before applying by clicking here.
*All applicants must submit official transcript(s) indicating: 1) The conferred bachelor's or master's degree as required for the program of application from a regionally accredited US institution or its equivalent. 2) The transcript of the most recent attendance if it differs from the institution of the conferred degree. This requirement applies regardless of the length of time in attendance and regardless of whether credit was earned or is desired. However, if a department or program wishes to review additional transcripts from prior attendance for decision purposes, the department or program may directly request the applicant to submit the official transcript(s) to the Office of Admissions for processing. Students must be eligible to re-enter all colleges and universities previously attended. Failure to disclose previous college attendance is justification for revocation of acceptance and dismissal from Lamar University.
Courses
Use cutting-edge software in your data analytics courses
To earn your Data Analytics Certificate, you need to complete 18 credit hours of coursework, including 6 credit hours of core courses and 12 credit hours of elective courses.
Students choose two (2) courses from list.
Students choose four (4) courses from list.
By the end of this course, students will be prepared to:
- Identify and define problems, identify the categories of analytical methods and models and recognize the types of data
- Describe and apply data visualization techniques of categorical and numerical variables
- Apply data mining techniques such as hierarchical cluster analysis, k-means cluster analysis and association rule analysis
- Apply supervised data mining techniques such as k-nearest neighbors, naive Bayes methods and decision trees
- Formulate problems and support decision analysis using different methods. Develop and apply Monte Carlo simulation models
By the end of this course, students will be prepared to:
- Interpret how to use data to summarize, visualize and develop insights
- Effectively use optimization to support decision-making in the presence of a number of alternatives and business constraints
- Identify, evaluate, and capture business analytic opportunities that create value
- Explain data visualization principles and guidelines for effective analysis and presentation
- Develop and interpret a wide range of visualizations in Tableau
- Communicate persuasive, data-driven business insights
By the end of this course, students will be prepared to:
- Develop simple programs with variables, statements and conditional execution
- Construct programs with functions and iteration structures
- Apply complex data structures to programs including strings, lists and dictionaries
- Design panda data frames and data structures
- Demonstrate plotting and data assembly
- Manage missing data, tidy data and data types
- Use text data, pandas apply and group by operations
By the end of this course, students will be prepared to:
- Identify data science methodology
- Explain data science methodology and relevant concepts
- Calculate data mining techniques to perform appropriate data analysis
- Uncover patterns and trends in data sets through hands-on analysis
- Discuss applications of data science
By the end of this course, students will be prepared to:
- Analyze data to generate information and knowledge that will lead to informed decisions for businesses
- Create standard reports for business users
- Derive insightful trends using data mining and machine learning techniques
- Apply the latest in analytics technology in real-world case studies in the areas of entertainment, business, climate change, etc.
- Show how business intelligence can be derived from data warehouses information technology program
- Author enterprise dashboards that are used to summarize and visualize data in a way that supports insight into trends and “what-if” analysis in real time
