Current instructor

Song Gao

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.71/5 from 28 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

What students say

Original student reviews · all captured dates

GEOG 378
Quality 5/5Difficulty 3/5
Class is well organized and labs are successful tools to challenge students and learn the material. I appreciated the specificity of this course to geography, particularly the real-life examples in labs and connections to previous GIS knowledge.
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GEOG 378
Quality 5/5Difficulty 4/5
Professor Gao is a genuinely compassionate teacher. For some similar 'esoteric' courses in the past I've had professors get annoyed by more fundamental questions/when students are struggling to grasp a concept, but Professor Gao seriously valued every question I heard asked and gave encouraging and comprehensive answers.
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GEOG 378
Quality 5/5Difficulty 4/5
Song is very knowledgeable and talented, with strong geospatial industry experience. I enjoyed his lectures a lot. It is not easy to get A in his class as it requires programming and heavy labs. You need to make great efforts and practice more to achieve the best grade.
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GEOG 378
Quality 1/5Difficulty 5/5
This class is absolutely awful if you do not have prior CS experience. Having taken GEOG 377, I thought I would be prepared and I was dead wrong. The labs are astoundingly difficult (and I'm not dumb by any means, I literally had a 4.0, which this class ruined). Song is a terrible lecturer and I learned absolutely nothing in class.
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GEOG 573
Quality 5/5Difficulty 4/5
This was a good class; I enjoyed it and felt like I learned a lot. I was thankful that the course was taught using Python3 and Jupyter Notebooks. these are great tools to use for spatial analysis and this course improved my abilities to use them for geospatial analysis, particularly Pandas and GeoPandas.
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GEOG 573
Quality 5/5Difficulty 4/5
This was one of the most challenging classes I have taken but I feel more confident in my code writing and more prepared for my future career now because of it.
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Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.

Classes with Song Gao

Pre-dissertator independent research supervised by a faculty member for students who have completed a master's degree but have not reached dissertator status.

Offering recorded · Spring 2027 · Sources

No recorded grade history

Introduction to theory, techniques, and analytical methods for geospatial big data, covering storage, processing, analysis, and visualization using advanced Python programming.

Offering recorded · Spring 2027 · Sources

Past student reviews · Song Gao

Professor Song Gao taught a challenging course using Python3 and Jupyter Notebooks, with students noting the final project helped test new skills. Reviews described the class as well-organized, combining technical geocomputing with real-world applications, and praised the instructor and TA for providing useful academic materials.

historical GPA · grades

Spring 2023–Spring 2026

Individual mentored study for seniors completing theses for Honors in the Major, arranged with a faculty member.

Offering recorded · Spring 2027 · Sources

No recorded grade history

INDEPENDENT WORK is an independent study course arranged with a faculty member.

Offering recorded · Spring 2027 · Sources

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=1 letter grades).

No recorded grade history

Recorded teaching history

Distinct courses recorded per term

Explore courses taught by this instructor →
Browse recorded courses
TermCourseTitle
Spring 2027COMPSCI 899Pre-dissertator Research
Spring 2027GEOG 573Advanced Geocomputing and Geospatial Big Data Analytics
Spring 2027GEOG 682Senior Honors Thesis
Spring 2027GEOG 691Senior Thesis
Spring 2027GEOG 699Directed Study
Spring 2027GEOG 990Research and Thesis
Spring 2027GEOG 999Independent Work
Fall 2026COMPSCI 899Pre-dissertator Research
Fall 2026COMPSCI 990Dissertation
Fall 2026GEOG 378Introduction to Geocomputing
Fall 2026GEOG 560Advanced Quantitative Methods
Fall 2026GEOG 681Senior Honors Thesis
Fall 2026GEOG 692Senior Thesis
Fall 2026GEOG 699Directed Study
Fall 2026GEOG 990Research and Thesis
Fall 2026GEOG 999Independent Work

Teaching history may be incomplete. Course pages contain course-specific feedback and citations.

Instructor identity & provenance
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