Lauren Bennett, PhD is product engineering director of Esri's Spatial Analysis and Data Science team. In her role, she oversees research and development of the ArcGIS analytical framework, which includes spatial and spatiotemporal statistics, raster and multidimensional analysis, and machine learning and big data analytics. Lauren received a Bachelor's degree in Geography from McGill University, a Master of Science degree in Geographic and Cartographic Science from George Mason University, and her PhD in Information Science from Claremont Graduate University.

Flora Vale is a principal product engineer on Esri's Analysis and Geoprocessing team. She is passionate about using spatial analysis and data visualization to answer questions and solve problems. In addition to building software, Flora loves teaching analytical methods through conceptual illustrations and believes that anyone can learn how to think spatially and make data-driven decisions. Flora studied Geography and GIS at the University of Maryland and is currently pursuing a PhD in Information Systems and Technology at Claremont Graduate University.

Alberto Nieto is a senior product engineer on Esri's Spatial Statistics team. He holds a Bachelor's degree in Geography from the University of Florida and a Master of Science degree in Analytics from Georgia Institute of Technology. Alberto focuses on building spatial statistics tools and software that help individuals and organizations understand and apply methods to make informed decisions.

Shannon Kalisky was a product management lead on Esri's Analytics and Data Science team. She studied geography at the University of Texas, Austin and holds a Master of Science in Community and Regional Planning from the University of Texas, Austin's School of Architecture.

Ankita Bakshi is a senior product engineer on Esri's Spatial Statistics team. She holds a Master's degree in Environmental Engineering and a Bachelor's degree in Computer Science. Ankita is passionate about solving social, economic, and environmental problems with spatial analysis and data science.

Atma Mani was a lead product engineer on Esri's ArcGIS API for Python team. His experience includes working for private, academic, and government research institutions to apply different facets of geospatial technology—from surveying, remote sensing, and GIS modeling to software development. Atma holds a Bachelor's degree in Engineering from Anna University, India, and a Master's degree in Geography from the University of Northern Iowa.

Jennifer Bell has created hundreds of maps and stories during her ten-year tenure at Esri. Her dedication to helping people visualize their data and tell impactful stories has led her to the role of Lead Product Manager for Web Mapping and Storytelling. Jennifer is passionate about enhancing the Map Viewer and ArcGIS StoryMaps experience and advocating for mapmakers, story creators, and their audiences.

Kevin Johnston, PhD is a senior principal product engineer on the ArcGIS Spatial Analyst development team at Esri, where he has worked for over 30 years. He holds a Master's degree in Landscape Architecture from Harvard and a PhD with a focus in Environmental Modeling from Yale. At Esri, Kevin's focus is developing suitability and connectivity tools. He hopes that the tools he works on support more informed decision-making.

Orhun Aydin, PhD, was a researcher on Esri's Spatial Statistics team and product engineer for R-ArcGIS Bridge. He is passionate about research pertaining to spatial machine learning methodologies and their applications to geosciences.

Vinay Viswambharan is a principal product manager on Esri's Imagery and Remote Sensing team. With more than twenty years of experience in the imagery field, Vinay plays an instrumental role in shaping Esri's imagery product capabilities and development.

There is so much information packed into this six-section course and very rarely did I feel lost. Directions are step-by-step, thorough, and easy to follow. I am highly impressed with the content and look forward to more learning opportunities with Esri.

— Jessica G.

The concepts were new to me but I enjoyed all the exposure and practice.

— Raquel J., Kenya

I liked the exposure to new tools and that the course was clearly put together well. Having the high-level video intros was nice and the tutorials were well crafted.

— Dan M., California

Including the storymaps as part of the course was great because it forced me to realize that communicating the data is just as important as acquiring the data. 

— Francesca R., California

I really enjoyed the video lectures and exercises. The video lectures were full of insights. Exercises were designed well. The instructions were well written.

— Maggie Z.

What I liked most about this MOOC was the knowledge that was offered to me and the informal and relaxed way in which it was done, thank you very much! Keep it up!

— Júlio R.

I was really impressed with this course. It's my first MOOC and if the others are anything like this one, you have a repeat customer! I really liked the videos at the beginning of each course topic. I felt they were a good launching pad and set the scene really well before attempting the exercises.

— Jessica N.

Loved the structure of the lesson. Each exercise built upon the previous exercises. This MOOC will also help in my graduate coursework since I can apply these tools for my classes.

— Suvam P.

The environment was very intimate, and [it] did not feel like a virtual course.

— Hamedreza V.

I enjoyed everything. The course was nicely paced, the questions were relevant, the exercises were fun real-world examples.

— Trevor P.

[I most enjoyed] learning at my own pace and the ability to ask my peers questions if I needed to, and to also try to help my peers if they needed assistance.

— Kathryn W.

I really appreciated the freedom to do this course whenever I was available to do it, and that I could stop in the middle of most exercises and come back as I needed to.

— Marachelle S.