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72 matches · Showing 55–72
Courses and guides are learning content. Directories organise choices; topic roadmaps and guidance requests do not imply a scheduled class or a confirmed mentor.
- GuideFree guide · read nowGetting reliable JSON and structured output from LLMsTechniques for dependable structured output: schemas, provider features, validation, retries, and graceful failure.View details
- GuideFree guide · read nowAI pair programming: habits that make coding assistants actually helpHow to get useful code from AI assistants — context, small steps, tests, and review — without shipping bugs or security holes.View details
- GuideFree guide · read nowReducing LLM costs without hurting qualityPractical levers — model choice, prompt size, caching, batching, and routing — to control LLM spend, measured against your evaluation set.View details
- GuideFree guide · read nowPython for AI: what to learn first (and what to skip for now)A focused Python learning path for people heading into data or AI work — core language, data libraries, APIs — without drowning in theory.View details
- GuideFree guide · read nowProduction checklist for shipping an AI featureA pre-launch checklist covering evaluation, safety, privacy, observability, cost, and fallbacks for LLM-powered features.View details
- GuideFree guide · read nowPrompting, RAG, or fine-tuning? Choosing the right approachA decision guide for when to improve prompts, add retrieval, or fine-tune a model — based on the problem you're actually solving.View details
- GuideFree guide · read nowUsing AI for software testing: test ideas, test code, and dataGenerate test cases, write test code, create realistic test data, and explore edge cases with AI — while keeping tests meaningful.View details
- GuideFree guide · read nowBuilding accessible AI chat and assistant interfacesAccessibility essentials for AI interfaces: streaming text, focus management, screen reader announcements, and clear controls.View details
- GuideFree guide · read nowOpen-weight LLMs: when to self-host and what it really takesTrade-offs between hosted APIs and self-hosted open-weight models: control, privacy, cost, quality, and operational load.View details
- GuideFree guide · read nowModel Context Protocol (MCP): a practical introductionWhat MCP is, how clients and servers fit together, and what to consider before connecting AI assistants to your tools and data.View details
- GuideFree guide · read nowWinning approach to AI hackathons: scope, build, and demoHow to pick a scope you can finish, build a working demo, and present it well at an AI hackathon.View details
- GuideFree guide · read nowDesigning an AI training plan for employees by roleStructure AI training into a shared foundation plus role-specific tracks, with practical tasks and support after the sessions.View details
- GuideFree guide · read nowAI for MSMEs: affordable ways to save time and growLow-cost AI uses for micro, small, and medium enterprises in India — sales, customer service, accounts support, and planning.View details
- GuideFree guide · read nowHow to find a mentor in tech (and make the relationship work)Where to find mentors, how to ask, what to bring to sessions, and how to turn advice into progress.View details
- GuideFree guide · read nowHow to get useful feedback on your work (not just “looks good”)Ask for feedback in a way that produces specific, actionable input — from mentors, managers, peers, and even AI.View details
- GuideFree guide · read nowGetting better at coding through code review mentorshipHow reviewed code accelerates developer growth, what to ask reviewers, and how to learn from review comments.View details
- GuideFree guide · read nowBecoming a mentor: how senior professionals can guide the next generationWhat mentoring involves, the skills good mentors use, and how professionals with 10+ years of experience can start mentoring.View details
- GuideFree guide · read nowSharing your expertise as a practitioner: teaching, mentoring, and what to expectA realistic look at teaching or mentoring alongside your job — time, preparation, rewards, and how platforms like TechlyUp work.View details