| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Getting Started with Jev | |||
| 1 - Where Jev Fits.mp4 | 49.3 MB | ||
| 2 - Course Introduction.mp4 | 14.7 MB | ||
| 2 - Jev Fundamentals Choice, Noul and Score | |||
| 3 - Project 1 Building a Support Triage System | |||
| 10 - Lesson_010_Experiment_Run_Guide.pdf | 3 KB | ||
| 10 - Lesson_010_Language_Robustness.py | 2 KB | ||
| 10 - Testing Robustness to Language Variation.mp4 | 9.8 MB | ||
| 11 - Lesson_011_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 11 - Lesson_011_Multiple_Judgments.py | 1.2 KB | ||
| 11 - Multiple Judgments from One State.mp4 | 36.6 MB | ||
| 12 - Jev Judges, Software Routes.mp4 | 26 MB | ||
| 12 - Lesson_012_Deterministic_Routing_Test.py | 1.1 KB | ||
| 12 - Lesson_012_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 12 - Lesson_012_Jev_Judges_Software_Routes.py | 6.3 KB | ||
| 13 - Build Project 1 — Support Triage.mp4 | 8 MB | ||
| 13 - Lesson_013_Project_1_Run_Guide.pdf | 3 KB | ||
| 8 - Classifying Support Tickets.mp4 | 13.4 MB | ||
| 8 - Lesson_008_Classify_Support_Tickets.py | 1.9 KB | ||
| 8 - Lesson_008_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 9 - Lesson_009_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 9 - Lesson_009_Unclear_Is_a_Valid_Class.py | 2 KB | ||
| 9 - Unclear Is a Valid Class.mp4 | 35.2 MB | ||
| proj1learner | |||
| README.md | 819.2 B | ||
| jev_adapter.py | 1.7 KB | ||
| main.py | 2.1 KB | ||
| models.py | 409.6 B | ||
| requirements.txt | |||
| 4 - Project 2 Building an Intelligent LLM Gateway | |||
| 14 - Classifying Task Complexity.mp4 | 12.3 MB | ||
| 14 - L014_P2-T01.py | 2.4 KB | ||
| 14 - L014_readme.pdf | 2.5 KB | ||
| 15 - Classifying Task Type and Complexity.mp4 | 15 MB | ||
| 15 - L015_P2-T01-with_task_type.py | 4.9 KB | ||
| 15 - L015_readme.pdf | 2.5 KB | ||
| 16 - Deterministic Model Selection.mp4 | 21.1 MB | ||
| 16 - L016_P2-T02_nojev.py | 2.5 KB | ||
| 16 - L016_readme.pdf | 2.5 KB | ||
| 17 - L017_P2-T03.py | 6 KB | ||
| 17 - L017_readme.pdf | 2.5 KB | ||
| 17 - Route to Real LLMs.mp4 | 3.2 MB | ||
| 18 - L018_P2-T04.py | 1.8 KB | ||
| 18 - L018_readme.pdf | 2.5 KB | ||
| 18 - Post-Check the LLM Response.mp4 | 2.4 MB | ||
| 19 - Build Project 2 — Intelligent LLM Gateway.mp4 | 5 MB | ||
| 19 - L019_main.py | 3.5 KB | ||
| 19 - L019_readme.pdf | 2.5 KB | ||
| 5 - Project 3 Insurance Claim Triage | |||
| 20 - Facts Are Not Semantic Judgments.mp4 | 19.2 MB | ||
| 20 - L020_P3-T01.py | 4.7 KB | ||
| 20 - L020_readme.pdf | 16.7 KB | ||
| 21 - Combine Facts with Semantic Evidence.mp4 | 3.1 MB | ||
| 21 - L021_P3-T01.py | 4.7 KB | ||
| 21 - L021_P3-T02_NoJev.py | 3.3 KB | ||
| 21 - L021_readme.pdf | 16.7 KB | ||
| 22 - L022_P3-T02_NoJev.py | 3.3 KB | ||
| 22 - L022_P3-T03_NoJev.py | 3.9 KB | ||
| 22 - L022_readme.pdf | 16.7 KB | ||
| 22 - Test Decision Boundaries.mp4 | 3 MB | ||
| 23 - Build Project 3 — Insurance Claim Triage.mp4 | 9.2 MB | ||
| 23 - L023_main.py | 1.8 KB | ||
| 23 - L023_readme.pdf | 16.7 KB | ||
| 6 - Project 4 Semantic Candidate Ranking | |||
| 24 - L024_P4-T01.py | 2.8 KB | ||
| 24 - L024_readme.pdf | 25 KB | ||
| 24 - Semantic Relevance Scoring.mp4 | 2.9 MB | ||
| 25 - L025_P4-T02_NoJev.py | 3.2 KB | ||
| 25 - L025_readme.pdf | 25 KB | ||
| 25 - Ranking Is Not Acceptance.mp4 | 7 MB | ||
| 26 - L026_P4-T03.py | 3.9 KB | ||
| 26 - L026_readme.pdf | 25 KB | ||
| 26 - When the Top Two Are Too Close.mp4 | 7.3 MB | ||
| 27 - Build Project 4 — Semantic Candidate Ranking.mp4 | 6.5 MB | ||
| 27 - L027_main.py | 4.8 KB | ||
| 27 - L027_readme.pdf | 25 KB | ||
| 7 - Capstone From Jev to Real-World AI Systems | |||
| 28 - Capstone Project — Semantic Policy Evaluation.mp4 | 70.8 MB | ||
| 28 - L028_main.py | 3.9 KB | ||
| 28 - L028_readme.pdf | 5.5 KB | ||
| 29 - Where Jev Fits in Modern AI Systems.mp4 | 115.7 MB | ||
| 30 - Congratulations.mp4 | 3.9 MB | ||
| README.md | 3.6 KB | ||
| jev_adapter.py | 2 KB | ||
| main.py | 3.9 KB | ||
| models.py | 614.4 B | ||
| policy.py | 2.6 KB | ||
| test_policy.py | 2.8 KB | ||
| P4-T01.py | 2.8 KB | ||
| P4-T02_NoJev.py | 3.2 KB | ||
| P4-T03.py | 3.9 KB | ||
| jev_adapter.py | 1.6 KB | ||
| main.py | 4.8 KB | ||
| models.py | 204.8 B | ||
| ranking_policy.py | 3.3 KB | ||
| readme.md | 20.2 KB | ||
| test_ranking_policy.py | 3.4 KB | ||
| P3-T01.py | 4.7 KB | ||
| P3-T02_NoJev.py | 3.3 KB | ||
| P3-T03_NoJev.py | 3.9 KB | ||
| claim_policy.py | 1.4 KB | ||
| jev_adapter.py | 2.6 KB | ||
| main.py | 1.8 KB | ||
| models.py | 512 B | ||
| readme.md | 13.8 KB | ||
| test_claim_policy.py | 2.3 KB | ||
| P2-T01-with_task_type.py | 4.9 KB | ||
| P2-T01.py | 2.4 KB | ||
| P2-T02_nojev.py | 2.5 KB | ||
| P2-T03.py | 6 KB | ||
| P2-T04.py | 1.8 KB | ||
| gateway_policy.py | 1.2 KB | ||
| jev_adapter.py | 2.4 KB | ||
| llm_service.py | 512 B | ||
| main.py | 3.5 KB | ||
| models.py | 204.8 B | ||
| readme.md | 1.8 KB | ||
| test_gateway_policy.py | 1.6 KB | ||
| routing.py | 1 KB | ||
| test_routing.py | 1.1 KB | ||
| 4 - Lesson_004_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 4 - Lesson_004_First_Jev_Call.py | 614.4 B | ||
| 4 - Your First Jev Call.mp4 | 5.9 MB | ||
| 5 - Choice, Noul and Score.mp4 | 34.8 MB | ||
| 5 - Lesson_005_Choice_Noul_and_Score.py | 1.2 KB | ||
| 5 - Lesson_005_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 6 - Lesson_006_Confidence_and_Scores.py | 1.9 KB | ||
| 6 - Lesson_006_Experiment_Run_Guide.pdf | 2.9 KB | ||
| 6 - Understanding Confidence and Scores.mp4 | 34.2 MB | ||
| 7 - The Core Architecture Pattern.mp4 | 2.6 MB | ||
| 3 - Environment Setup.mp4 | 6.3 MB | ||
| 3 - Lesson_003_Setup_Guide_Windows.pdf | 32.1 KB | ||
| 3 - Lesson_003_Setup_Guide_macOS.pdf | 32.1 KB | ||
| 3 - Lesson_003_Setup_Test.py | 614.4 B | ||
| 3 - Lesson_003_Setup_Test_Guide.pdf | 29.8 KB |
Jev Masterclass: Build Practical AI Decision Systems
https://WebToolTip.com
Published 10/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 41m | Size: 584.77 MB
Get comfortable with Jev through a ladder of use cases and get ready for implementation.
What you'll learn
Master Jev core primitives (Choice, Score, and Noul) to structure complex, type-safe decision workflows in production
Design, run, test, and extend practical Jev projects in classification, intelligent routing, and model selection, ultimately culminating in a travel-policy caps
Build confidence-aware application logic using thresholds, clarification paths, fallback behavior, and human-review boundaries.
Learn to clearly separate semantic judgment from deterministic business rules
Requirements
The course explains the Jev concepts it uses, so prior Jev experience is not required. 1) A basic understanding of APIs and modern AI/LLM applications is helpful, but deep machine-learning knowledge is not required 2) Access to the Jev/TypeSafe and other required API keys. Access to a computer to run Python and install the Jev / TypeSafe AI SDK, and PIP packages used in the course. 6) Access to computer to run the course programs on. In case, you are interested in understanding what Jev is and how it can be utilized in the AI systems without running the programs yourself, then the pre-requisite will be: 1 above only.
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