Herzing’s Data Analytics With AI program is designed to take students from total beginners to industry-ready professionals. Learners benefit from hands-on coursework that combines programming, statistics, cloud technologies, and real-world applications, all with the support of instructors who know how to teach complex concepts in an accessible way.

Zakiya Malek is one of those instructors. With a doctorate in cybersecurity and decades of experience teaching and working with technology, she brings a strong mix of academic expertise and real-world insight to her classes. She helps Herzing students understand not only how to analyze data, but also how to work responsibly with data in enterprise environments.

In this interview, she talks about how the program is structured, what students can expect to learn, and the kinds of roles graduates are prepared for.

Q. Could you summarize your education and professional background?

Zakiya: I hold a PhD in computer science and have over 20 years of academic experience. I have been teaching postgraduate computer science students since 2004 and have authored two books: one on data structures and another on computer organization. In addition, I have published numerous research papers in national and international journals, served as a reviewer and editorial board member for academic publications, and supervised two scholars who successfully completed their PhDs.

Teaching is truly my passion. I am not a teacher only by profession, but by calling. I believe that effective education combines strong theoretical foundations with practical applications, helping students build a deep understanding of concepts while developing the skills to solve real-world problems.

To further enhance my teaching skills, I am taking courses focused on teaching and learning in higher education.

Q. Do most of your students have a background in IT?

Zakiya: No, most students do not come in with a strong IT or technical background. That’s why the program is designed to be very approachable, even for beginners. I focus on breaking complex concepts into simple, step-by-step demonstrations.

In synchronous sessions, I teach live and walk students through tasks step by step, allowing them to work alongside me. If someone gets stuck, they can share their screen so we can troubleshoot issues together in real time. Asynchronous materials include recorded demonstrations and guided exercises that students can review, pause, and revisit as needed.

For additional support, students can ask questions in discussion forums or schedule one-on-one meetings to review concepts and resolve challenges. This blended approach ensures students receive continuous guidance while building confidence and technical skills.

Q. What are the most valuable skills that the data analytics program covers?

Zakiya: We focus on teaching the complete data analytics lifecycle. Students start with the fundamentals, including statistical methods and an understanding of what data is—both structured and unstructured. From there, we move into data cleaning, preprocessing, and building data pipelines, because high-quality analytics always starts with well-prepared data.

As students progress, we cover big data technologies and cloud platforms to reflect how data is managed in real-world organizations. We then introduce machine learning, predictive analytics, and advanced machine learning techniques so students can see how insights are generated from data.

In the final stages of the program, we explore generative AI and the ethical use of data and AI technologies. This end-to-end approach supports students in developing the skills needed to work responsibly with data across the full data analytics lifecycle.

Q. Can you give some examples of projects or assignments that students do?

Zakiya: We design assignments around real-world use cases so students can apply technical concepts in a practical way. In one course, students work with publicly available datasets and use Python in Jupyter Notebooks to perform data analysis and introductory machine learning tasks. They apply appropriate Python libraries to train models, evaluate results using standard performance measures, and create visualizations to interpret and communicate their findings.

In another course, students focus on business intelligence and reporting. They use Power BI to develop interactive dashboards, apply filters and controls, and design visualizations that help translate data into insights that support managerial decision making.

Students are also introduced to big data concepts and distributed computing. They learn how distributed data processing works and gain hands-on experience by configuring a local development environment that simulates big data workflows. This helps them understand how large datasets are processed across multiple systems in practice.

A key midterm project is structured as a real-life case study, such as an online shopping or healthcare scenario. Students collect data from the selected domain and perform data preprocessing tasks, including handling missing values, ensuring consistency across data fields, and applying normalization techniques. In the second phase of the project, they implement analytical or machine learning solutions based on the prepared data.

Q. What kinds of jobs are students qualified for when they complete this program?

Zakiya: They can go for roles like junior data analyst, data analyst, business intelligence analyst, reporting or decision support analyst, junior data scientist, and analytics consultant.

The program is also aligned with skills covered in several industry-recognized certifications, including those offered by Microsoft, Google, and IBM in areas like data analytics, databases, and cloud technologies. The curriculum provides a strong foundation to help prepare them for these certifications, and pursuing them after graduation can further strengthen their professional profile.

Q. What’s the job market like right now for data analysts?

Zakiya: Obviously we’re in the era of AI, but human expertise is still essential to interpret data, validate results, and provide context. Organizations across sectors such as marketing, healthcare, education, government, and technology continue to rely on data to make decisions, which means there are still strong job opportunities for data analysts and related roles.

LEARN MORE ABOUT HERZING’S DATA ANALYTICS WITH AI PROGRAM

Herzing’s online Data Analytics With AI program takes no more than 19 months to complete and includes an internship, so you can get real work experience before you graduate.

Still have questions? Reach out to our admissions team. They can walk you through course schedules, financial aid options, application procedures, and more.

Click below to get more details on the program and chat live with an advisor. We’re here to help!