If you already have your undergraduate degree in data analytics, computer science, or a related field and are looking to further your education, it may be time to pursue your online master’s in data analytics from Indiana Wesleyan University (IWU). In this Master of Science (MS) in Artificial Intelligence - Data Analytics program, you'll build career-ready skills in generative AI, visualization, natural language processing, and more — all with a Christian ethical foundation.
As you prepare to apply for this program, however, you should learn about admissions requirements, prerequisites, financial aid for working adults, and how to get ready for grad school as a busy professional.
IWU's MS in Artificial Intelligence - Data Analytics is designed for working professionals who are ready to drive innovation across sectors. To qualify for admission, applicants must have a minimum of a bachelor's or graduate degree from an accredited college or university, including an undergraduate grade point average (GPA) or 2.5 or higher.
What do you need to apply to an MS in Artificial Intelligence at IWU? There are a few things you'll need to get started:
Like many rolling admission graduate programs, IWU's MS in Data Analytics accepts applications on an ongoing basis. This means you don't need to submit your materials by a hard deadline to be considered. This may give you more time to focus on gathering the documentation you need and preparing the best application possible.
Aside from required application materials, there are also some optional materials that you may want to consider including with your application to further set yourself apart from other candidates:
There are a number of prerequisite skills that can also be beneficial to have as you prepare to apply for an MS in AI - Data Analytics at IWU. These include:
You likely have relevant quantitative or problem-solving experience, even without formal analytics training. This is particularly true if your current responsibilities involve forecasting, reporting, or process improvement.
If you feel like you could use a refresher on SQL, Python, or any other foundational components before applying for your program, we've put together a practical study plan for working professionals in the sections below.
Even while working full-time, you can build the foundational skills necessary for our MS program by dedicating only 30–60 minutes 5–6 days each week to review.
In this study schedule for full-time workers, you'll explore such weekly themes as:
During the first week of your prep, this is a good time to review:
During week two of your prep, consider focusing on Python fundamentals for analytics, including:
You might also take on some mini-projects to gain practice with Python, such as creating number guessing games or even building a simple calculator. These kinds of practice projects can help you build not just practical skills, but confidence milestones as well.
Moving into week three of your prep, it's time to look more closely at building an experimentation and metrics mindset that will serve you well in your MS program. During this time, it's important to focus on:
Entering the final week of your prep means taking additional steps to prepare your application and portfolio (or project write-ups, if you don't plan on completing a full portfolio). During this stage, you'll:
When it comes to online learning success tips, one of the most important skills you can build is that of time management, especially if you plan on continuing to work full-time while pursuing your master's degree.
Successful time management begins with creating a weekly routine that's realistic and that will be sustainable enough for you to stick with. If you know you'll be working 40 hours on Monday through Friday, for example, you might plan on setting aside larger chunks of time on evenings and weekends to keep up with the demands of your coursework.
Many working grad students find success with scheduling their study time and class time in the same way they would schedule any other obligation. Remain consistent and avoid falling behind by dedicating specific time blocks each week for studying and focusing on schoolwork.
A common concern many working professionals have when considering a graduate degree is friction in the workplace. You might worry, for example, that the demands of school will prevent you from staying on top of your game at work.
This is where proactively speaking with your supervisors, peers, and other members of your team about your program expectations can make all the difference. A lot of times, when employers are kept in-the-loop, they're willing to work with and support employees who are working to advance their skills and knowledge.
In addition to support from your own employer, choosing the right MS program with student-centered support could also make your return to school as a working professional more successful.
At IWU, we're proud to offer not just flexible online coursework, but tailored services that include academic advising and success coaching throughout your time in our program. These advisors understand what it takes to support learners from diverse computer science or even non-technical backgrounds, offering personalized support and guidance every step of the way.
As part of your program at IWU, you'll also enjoy access to plenty of resources you can tap into early to build career-ready skills. This includes a curriculum covering:
If needed, our admissions and advising teams can also recommend specific SQL/Python refreshers, statistics courses, or other sample materials that align with our program expectations.
Even once you've worked through our study/prep schedule and feel ready to apply to the program, there are a couple last-minute things worth keeping in mind as you prepare your application.
First, understand that you don't necessarily have to complete all the prep work covered here to submit your application. If you decide to apply before you've finished prep, simply use your personal statement as an opportunity to explain how you're refreshing your skills and how you plan on using the remainder of your time before the semester starts.
As part of your application, including in your personal statement and letters of recommendation for grad school, it's also important to signal to the admissions committee how you plan to hit the ground running once the semester starts. This may include calling out particular skills that you wish to work on or specific areas of interest that you'd like to pursue.
It's relatively common for applicants to have not used SQL or Python in years, which is why this 30-day plan is designed to refresh fundamentals. Plus, our admissions team isn't expecting expert-level code, just evidence that you can ramp up quickly and are willing to put in the practice.
No, you can often apply and work through prep in parallel. If you decide to go this route, simply use your personal statement to describe how you're refreshing key skills and how you plan to use the time before your classes start.
Yes, you can be a strong applicant even without formal analytics experience. In your application, just be sure to highlight quantitative or problem-solving work in your current role (forecasting, reporting, process improvement) and demonstrate how you're building technical skills through prep and projects.
You should aim for about 30–60 minutes per day, 5–6 days per week. Consistency matters more than long weekend marathons, and small reps will add up quickly.
While you don't necessarily need a full portfolio, even one small project or write-up can significantly strengthen your application. This demonstrates initiative, curiosity, and your ability to turn data into a story, all of which make for a more compelling application.
If your undergrad GPA is lower than you'd like, use your statement to provide context and highlight recent growth in your application. This should include work performance, certifications, prep work, and your readiness plan. Meanwhile, strong references and current/recent achievements may also offset older grades.
Yes, admissions or advising teams can often recommend specific SQL/Python refreshers, statistics resources, or sample materials that match the program's expectations.
If you meet the requirements for admission into IWU's MS in Artificial Intelligence - Data Analytics, and you're serious about advancing your skills and knowledge in this growing field, there's nothing stopping you from taking the next step. Get in touch with our team to learn more about what this online program has to offer, or begin your application for admission today.
Still trying to decide your next steps? Get help finding your ideal program at IWU.
