The D797 assessment
WGU does not publish assessment formats in the catalog. We confirm the current format for your exact catalog year at intake, and the fixed quote covers whichever assessment D797 carries.
WGU course completion
D797 Artificial Intelligence and Machine Learning Foundations, completed for you
At a glance
Last updated
D797 Artificial Intelligence and Machine Learning Foundations (ICSC 5205, 3 CUs in the September 2026 WGU catalog) is the AI foundations course of the graduate computer science path: term 2 of all three M.S. Computer Science tracks (Artificial Intelligence and Machine Learning, Computing Systems, and Human-Computer Interaction), beside D796 and D486, and term 10 of the accelerated BSCS-to-MSCS bachelor's track, with no prerequisites stated in the catalog. Per the description it covers foundational concepts and practical applications of AI and ML: the historical context and growth phases of AI, the computational theories and logical frameworks behind it, the hardware advances that enabled the leap from basic ML to deep learning, data integrity and data wrangling for ML algorithms, and the societal implications and current ethical considerations. Coursework Ninja completes D797 done-for-you, fixed quote in writing first. From $99. Independent of WGU.
Next question: what does D795 Applied Algorithms and Reasoning ask in term 1 of the same tracks?
Per WGU's published description, Artificial Intelligence and Machine Learning Foundations explores foundational concepts and practical applications of AI and ML, from the historical context and evolution of AI through the growth phases of AI technologies. The course investigates the computational theories and logical frameworks that shaped the AI landscape, examines how hardware advancements enabled the leap from basic ML to deep learning, emphasizes data integrity and data wrangling techniques for feeding ML algorithms effectively, and closes on the societal implications of AI and ML, including current ethical considerations. The catalog states plainly: there are no prerequisites for this course.
Four catalog tables carry D797: term 2 of all three M.S. Computer Science tracks, where it sits beside D796 Unix and Linux and D486 Governance, Risk, and Compliance, and term 10 of the accelerated BSCS-to-MSCS bachelor's track, where it closes the degree. On that accelerated path it is the summit of a verified AI ladder: D429 Introduction to AI for Computer Scientists in term 9, then D682 Artificial Intelligence Optimization in term 9 with D429 as its stated prerequisite, then D797 in term 10. The regular B.S. Computer Science table does not carry it. Message us the code and where you stand, and we quote a flat price in writing.
- Fixed quote in writing before any work, singles from $99
- 3 CUs, term 2 of all three M.S. Computer Science tracks
- AI history to deep learning, data wrangling, ethics, no prerequisites
- Folds into the $3,500 master's package with the 6-month guarantee
Every full package includes the written 6-month guarantee: we finish the remaining CUs under the agreed plan, or you do not pay. Packages: Bachelor's $3,000 · Master's $3,500 · both $5,500 · single assessments from $99.
Coverage
What D797 completion covers
AI history and growth phases
The description opens with the historical context, evolution, and growth phases of AI technologies. The graded layer is the reasoning the history supports, and students who skim it meet it again inside later prompts.
Theories and logical frameworks
The computational theories and logical frameworks that shaped the AI landscape: the conceptual grammar of the course, and the vocabulary the scored work is written in.
From basic ML to deep learning
A named arc of the course: how advancements in hardware enabled the leap from basic ML to the complexities of deep learning. The explanation has to connect the hardware story to the capability jump, not just name both.
Data integrity and wrangling
The practicalities block: the critical role of data integrity and the techniques for data wrangling to feed ML algorithms effectively. Data work here is graded as ML input preparation, not generic cleaning.
Societal implications and ethics
The course closes on the societal implications of AI and ML, discussing current ethical considerations, aiming at a nuanced understanding of the broader impacts. Ethics answered as personal opinion instead of current considerations is the classic miss.
Full degree plan integration
D797 alone is a single from $99. On a remaining M.S. Computer Science list it folds into the flat $3,500 master's package; on the accelerated bachelor's track it rides the $3,000 bachelor's package. Either way the written 6-month finish guarantee covers it.
Stuck on one of these right now?
Send the course code on Telegram or WhatsApp. Single-course completions start at $99 with a fixed quote in writing before any work begins.
Bottlenecks
Where D797 stalls computing students
D797 stalls engineers who use AI tools daily and assume usage is understanding. The course grades foundations, data discipline, and ethics in the field's own vocabulary. These are the stalls we take over most often.
- The history and growth-phase material skimmed, then asked about directly.
- The ML-to-deep-learning leap explained without the hardware advancements the description names.
- Data wrangling treated as a chore instead of the integrity discipline the course grades.
- Ethics sections written as personal takes instead of current considerations in the field.
- The accelerated-track student meeting D797 in term 10, out of energy, one course from the finish line.
Only need one course finished? Single OA / PA / CU completion starts at $99. Message us the course code for a fixed quote. See full package pricing.
Questions, answered
Per the September 2026 WGU institutional catalog, Artificial Intelligence and Machine Learning Foundations (ICSC 5205, 3 CUs) explores foundational concepts and practical applications of AI and ML: the historical context, evolution, and growth phases of AI technologies; the computational theories and logical frameworks behind the field; how hardware advancements enabled the leap from basic ML to deep learning; data integrity and data wrangling techniques for ML algorithms; and the societal implications of AI and ML, including current ethical considerations. The catalog states there are no prerequisites for this course.
Per the current catalog, four tables: term 2 of all three M.S. Computer Science tracks (Artificial Intelligence and Machine Learning, Computing Systems, and Human-Computer Interaction) and term 10 of the accelerated BSCS-to-MSCS bachelor's track. The regular B.S. Computer Science table does not carry it. If your degree plan shows ICSC 5205, this is the course.
WGU does not publish assessment formats in the catalog. We confirm the current format for your exact catalog year at intake, and the fixed quote covers whichever assessment the course carries.
Three different AI courses, three levels. D685 Practical Applications of Prompt (ICSC 2212) is the bachelor's AI-fluency course five computing tables share, about scoped, evaluated prompting. D682 Artificial Intelligence Optimization for Computer Scientists (ICSC 3112) is the bachelor's optimization course on the B.S. Computer Science tables, gated behind D429 Introduction to AI for Computer Scientists per its own catalog description. D797 is the graduate foundations course on the M.S. Computer Science tracks and the accelerated path, with no prerequisites stated, spanning theory, data integrity, and ethics. Same family, different codes and depth.
Tool fluency helps with the applications layer and not much else. The course grades the foundations underneath: theories and frameworks, the hardware story behind deep learning, data wrangling as a discipline, and ethics argued as current considerations rather than opinion. Daily users stall on exactly those rows.
One course starts at $99, with the exact figure fixed in writing once we know where you stand. On a longer remaining M.S. Computer Science list, the master's package is $3,500 flat with the written 6-month finish guarantee covering every course on the plan, this one included.
No. Coursework Ninja is an independent paid completion service, not affiliated with, endorsed by, or sponsored by Western Governors University. WGU provides its own instructors, mentors, and evaluators; we are separate, for students who want this course finished on a fixed date.
Coursework Ninja is an independent done-for-you degree completion service and is not affiliated with, endorsed by, or sponsored by Western Governors University.
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