← Back
Amazon Part 2
completedAmazon
|60 courses, 20 assessments, 20 practices
|UB/UProSkills
50 rows, 40 unique
| # | Learning Path | Skill | Course | Confidence | Course Length | Section Info | Selection Length | Notes | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Constructing effective prompts using clear instructions, context, and constraints Prompt Engineering | Good | 2.2h | Section 3: Prompt Templates For ChatGPT And Other LLM Models Like Google Bard & Bing Chat., Lectures 7-12 | 25min | - | ||||
| 2 | Iterating on prompts based on output quality Prompt Engineering | Good | 10.3h | Section 6: Prompt Engineering, Lectures 42-45 | 15min | - | ||||
| 3 | Applying prompt engineering principles systematically Prompt Engineering | Good | 13h | Section 15: Phase 3 (A) of GenAI Project - Prompt Engineering | 20min | - | ||||
| 4 | Prompt Engineeringassessment Prompt Engineering | assessment | Good | - | - | - | - | |||
| 4 | Prompt Engineeringpractice Prompt Engineering | Good | 2.2h | Section 4: Prompt Engineering Explained | 8min | - | ||||
| 5 | Critically evaluating AI-generated outputs for accuracy and relevance AI Output Evaluation | Good | 1.6h | Section 3: AI for Positioning and Brand Strategy, Lectures 10-11 | 9min | - | ||||
| 6 | Identifying hallucinations and errors in AI responses AI Output Evaluation | – | Can't find easily | - | - | - | Content gap: no course with satisfactory match found for this skill | |||
| 7 | Validating AI recommendations against organizational requirements AI Output Evaluation | Found with broader criteria | 9.7h | Section 3: Responsible AI Governance and Risk Management, Lectures 51-54 | 23min | Although the rating is lower than 4.4, the content is still relevant to this skill | ||||
| 8 | AI Output Evaluationassessment AI Output Evaluation | Good | - | - | - | - | ||||
| 8 | AI Output Evaluationpractice AI Output Evaluation | Good | 4h | Section 9: Final Exam Prep and Leadership Readiness | 9min | - | ||||
| 9 | Applying human judgment to AI-generated content AI Tool Selection | Good | 1.6h | Section 1: Getting Clear on the Essentials; Section 2: AI for Brand Diagnosis | 25min | - | ||||
| 10 | Evaluating AI tools for specific use cases AI Tool Selection | 6582647 | Found with broader criteria | 1.1h | Section 2: How to evaluate your Agents? | 20min | Although the rating is lower than 4.4, the content is still relevant to this skill | |||
| 11 | Comparing capabilities across different AI platforms AI Tool Selection | Good | 3.8h | Section 4: Generative AI Foundation Models in Google Cloud, Lectures 20-26 | 11min | - | ||||
| 12 | AI Tool Selectionassessment AI Tool Selection | assessment | Good | - | - | - | - | |||
| 12 | AI Tool Selectionpractice AI Tool Selection | Good | 4.1h | Section 4: Amazon Q developer for Java, Lectures 21-23 | 17min | - | ||||
| 13 | Making informed build-vs-buy decisions Responsible AI Practice | Good | 9.3h | Section 1: Introduction; Section 2: Software Lifecycle | 22min | - | ||||
| 14 | Identifying ethical considerations in AI adoption Responsible AI Practice | Good | 1.7h | Section 1: Introduction; Section 2: Ethical AI Principle: Fairness | 29min | - | ||||
| 15 | Recognizing and mitigating bias in AI outputs Responsible AI Practice | Good | 1.9h | Section 3: Safe Use Protocol, Lectures 14-16 | 15min | - | ||||
| 16 | Responsible AI Practiceassessment Responsible AI Practice | assessment | Good | - | - | - | - | |||
| 16 | Responsible AI Practicepractice Responsible AI Practice | Good | 10.3h | Section 13: Preparing for the Exam + Practice Exam - AWS Certified AI Practitioner, Lectures 144-145 | 17min | - | ||||
| 17 | Applying organizational AI use policies Code Generation | Good | 1.9h | Section 3: Safe Use Protocol, Lectures 12-13 | 14min | - | ||||
| 18 | Evaluating AI use cases for ethical implications Code Generation | Found with broader criteria | 6.8h | Section 2: AI Risk Management for Product Teams, Lectures 15-22 | 21min | Although the rating is lower than 4.4, the content is still relevant to this skill | ||||
| 19 | Generating code snippets using AI assistance Code Generation | Good | 16.4h | Section 13: Amazon Q Developer, Business and Quicksight, Lectures 91-93 | 26min | - | ||||
| 20 | Code Generationassessment Code Generation | assessment | Good | - | - | - | - | |||
| 20 | Code Generationpractice Code Generation | Good | 4.1h | Section 4: Amazon Q developer for Java | 25min | - | ||||
| 21 | Evaluating AI-generated code for correctness and efficiency Debugging | Good | 11.8h | Section 3: 2025 SaaS Tech Stack, Lectures 39-42 | 19min | - | ||||
| 22 | Integrating AI-generated code into existing codebases Debugging | Found with broader criteria | 12.8h | Section 5: CURSOR: Your First Cursor Project: Currency Converter App, Lectures 24-26 | 29min | Although the rating is lower than 4.4, the content is still relevant to this skill | ||||
| 23 | Using AI to identify root causes of bugs Debugging | Found with broader criteria | 2.5h | Section 2: Modern Debugging Fundamentals - With AI in the Loop, Lectures 4-10 | 29min | Although the rating is lower than 4.4, the content is still relevant to this skill | ||||
| 24 | Debuggingassessment Debugging | – | Can't find easily | - | - | - | Content gap: no course with satisfactory match found for this skill | |||
| 24 | Debuggingpractice Debugging | – | Can't find easily | - | - | - | Content gap: no course with satisfactory match found for this skill | |||
| 25 | Generating and testing debugging hypotheses Test Development | Not processed yet | ||||||||
| 26 | Providing effective context to AI for debugging assistance Test Development | Good | 8h | Section 13: Amazon Q - Exploring Amazon Q Features, Lectures 44-46 | 20min | - | ||||
| 27 | Generating test cases using AI Test Development | Good | 9.7h | Section 13: Building Test Case Generator AI Agent, Lectures 59-62 | 25min | - | ||||
| 28 | Test Developmentassessment Test Development | assessment | Good | - | - | - | - | |||
| 28 | Test Developmentpractice Test Development | Good | 11.3h | Section 4: Test Driven Development with Jest and TypeScript, Lectures 21-24 | 28min | - | ||||
| 29 | Evaluating test coverage and quality Program Planning | Good | 78.9h | Section 32: Quality Assurance - Testing: Metrics & KPIs, Lecture 228 | 32min | Section/course duration exceeds the target of 0.5h, but best available match for this skill | ||||
| 30 | Identifying edge cases with AI assistance Program Planning | Good | 10.2h | Section 3: Assistants API - A Refresher, Lectures 22-25 | 30min | - | ||||
| 31 | Developing project plans with AI support Program Planning | Good | 3.9h | Section 4: Practical Applications of Generative AI for Project Managers, Lectures 21-23 | 15min | - | ||||
| 32 | Program Planningassessment Program Planning | assessment | Good | - | - | - | - | |||
| 32 | Program Planningpractice Program Planning | – | Can't find easily | - | - | - | Content gap: no course with satisfactory match found for this skill | |||
| 33 | Identifying dependencies and risks Dependency Analysis | Good | 7.8h | Section 5: The planning phase - timelines and schedules, Lectures 28-29 | 8min | - | ||||
| 34 | Generating resource allocation recommendations Dependency Analysis | Good | 7h | Section 6: Resource Management, Lectures 62-69 | 27min | - | ||||
| 35 | Mapping cross-team dependencies Dependency Analysis | Good | 37.5h | Section 21: Annex: Labs, Lecture 118 | 10min | - | ||||
| 36 | Dependency Analysisassessment Dependency Analysis | assessment | Good | - | - | - | - | |||
| 36 | Dependency Analysispractice Dependency Analysis | Good | 168h | Section 19: Java Collections Framework, Lecture 104 | 19min | - | ||||
| 37 | Analyzing critical path implications Risk Management | Good | 11.8h | Section 8: Developing Schedule Logic, Lectures 55-56 | 10min | - | ||||
| 38 | Developing mitigation strategies Risk Management | Good | 8.5h | Section 3: Risk Management Strategies in Scrum, Lectures 15-16 | 19min | - | ||||
| 39 | Identifying program risks using AI analysis Risk Management | Good | 1.9h | Section 1: The AI Risk Overview, Lectures 2-3 | 13min | - | ||||
| 40 | Risk Managementassessment Risk Management | Good | - | - | - | - | ||||
| 40 | Risk Managementpractice Risk Management | Good | 5.6h | Section 6: Module 5: Performance boosters (bonus materials):, Lectures 33-35 | 25min | - | ||||