This is just one way to learn these tools. The most important thing isn't that you do everything here. The most important thing is that you start. Do something. Learn something. Move in the right direction. We're not ever looking for perfection. We're looking for incremental mastery of new ideas.
You've got this.
AI for Tech Pros: No-Code Mastery – Comprehensive Lesson Plan
This creates a comprehensive, self-contained lesson plan
tailored for IT professionals like you—with years of tech experience but
minimal coding background. The plan emphasizes no-code tools, leverages your IT
intuition (e.g., troubleshooting workflows), and builds practical AI skills for
real-world applications, like automating IT tasks.
The lesson plan is structured for 7 core days (plus Day 0
orientation), with each day capped at 4 hours to fit busy schedules. It's
achievable over 1-2 weeks, assuming self-paced learning. Total estimated time:
30 hours. Focus on hands-on projects to reinforce concepts and use the pitfalls
to proactively avoid common beginner frustrations.
Approach:
- Target
Audience: IT pros with tech experience but little coding—perfect for
those who've managed systems or networks but want to add AI without
development hurdles.
- Prerequisites:
Basic computer skills; familiarity with tools like Google Sheets. No
coding required.
- Goals:
By the end, you'll build and deploy AI prototypes (e.g., agents,
automations, MVPs) applicable to IT work, gaining confidence as an AI
generalist.
- Materials:
Free-tier tools; a journal in Notion for notes and reflections.
- Pacing
Tips: Dedicate 4 hours/day; take breaks for testing. If needed, use
optional extensions (1-2 days/week) for deeper practice on complex IT apps
like predictive maintenance.
- Support:
Simulate "office hours" by reviewing pitfalls and journaling
fixes. Join communities for peer help.
- Assessment:
Daily assignments build a portfolio; on Day 7, pitch your MVP to yourself.
- Philosophy:
AI as an extension of your IT toolkit—practical, no/low-code, and empowering.
Day 0: Orientation and Mindset Shift (2 hours)
Focus: Bridge your IT experience to AI—no code
needed.
Activities: Review the full lesson plan; set personal goals (e.g.,
"Automate my daily IT reports"). Watch intro videos on AI basics to
shift mindset from traditional IT to AI-enhanced workflows. Join no-code
communities for ongoing support.
Resources and Links:
- Google
AI Essentials (free intro course, no coding): https://grow.google/certificates/ai-essentials/.
- YouTube:
"Become an AI Engineer and build the future!!" (intro to AI
generalist skills): https://www.youtube.com/shorts/_6jvVAIAsSA.
- X
Profiles: @ai_lab_daily (AI tips and tools).
- X
Posts: General AI learning tips: https://x.com/WordStream/status/1950224913937170478.
Assignment: Create a Notion journal page: Answer "How has IT prepared me for AI?" and list 3 goals.
Common Pitfalls/Gotchas:
- Overloading
on Tools Too Early: Don't install everything at once—focus on Day 1
needs first to avoid setup fatigue. (Tip: Prioritize Ollama if your
machine has a GPU for smoother local runs.)
- Ignoring
Account Sign-Ups: Free tiers require email verification; delays happen
if you use a work email with strict filters. (Tip: Use a personal Gmail
for quick access.)
- Underestimating
Goal Setting: Vague goals lead to scattered focus—make them specific,
like "Build an AI for IT ticket summaries." (Tip: Revisit your
journal daily.)
Day 1: AI Fundamentals and Local Playground (4 hours)
Tailored Twist: Relate LLMs to IT databases—querying
data without SQL.
Steps:
- Fundamentals
(1 hour): Learn LLMs and transformers; watch intro resources.
- Prompt
Engineering (1 hour): Practice techniques in OpenAI Playground.
- Deploy
Models (1.5 hours): Use Ollama, Msty, and Bolt; test queries.
- Pipelines
(30 mins): Chain prompts for complex outputs; take a 10-min break if
needed.
Resources and Links:
- Ollama:
https://ollama.com/.
Tutorial: https://ollama.com/docs.
- Msty:
https://msty.app/.
- Bolt:
https://support.bolt.new/building/intro-bolt.
- OpenAI
Playground: https://platform.openai.com/playground.
- YouTube:
"Run AI Models Locally: Ollama Tutorial (Step-by-Step Guide +
WebUI)": https://www.youtube.com/watch?v=Lb5D892-2HY.
Alternative: "Learn Ollama in 15 Minutes": https://www.youtube.com/watch?v=UtSSMs6ObqY.
- X
Profiles: @jstepka (Ollama enthusiast), @PicoGPT (local AI tools).
- X
Posts: Tutorial on local RAG with Ollama: https://x.com/atef_ataya/status/1949420780535558438.
Tips on GPU-accelerated Ollama: https://x.com/Marktechpost/status/1948987763375964413.
- Additional:
AI for Everyone (Coursera, non-technical): https://www.coursera.org/learn/ai-for-everyone.
Assignment: 5 custom prompts; local query on a personal topic (e.g., "Summarize an IT report").
Common Pitfalls/Gotchas:
- Hardware
Mismatch for Local Models: Ollama may run slow on older CPUs—expect
longer load times if no GPU. (Tip: Test with small models like
"llama3:8b" first; switch to cloud if needed.)
- Poor
Prompting Habits: Vague prompts yield junk outputs, like asking
"Explain AI" without context. (Tip: Always specify role, format,
and examples—e.g., "As an IT expert, explain LLMs in bullet
points.")
- Installation
Errors: Bolt or Msty might conflict with antivirus software. (Tip:
Temporarily disable security during install; check tool forums for
OS-specific fixes.)
- Forgetting
Privacy: Local runs are great for sensitive IT data, but default to
cloud for quick tests. (Tip: Avoid uploading proprietary info to OpenAI.)
Day 2: Media Generation and Clones (4 hours)
Tailored Twist: Use for IT visuals (e.g., generate
diagrams for reports).
Steps:
- Images
(1 hour): Prompt and refine in Midjourney.
- Videos
(1 hour): Animate and edit in Runway and Veed.io.
- Voice
Cloning (1 hour): Use ElevenLabs; test outputs.
- Integration
(1 hour): Combine for a full clone; include short breaks between
tests.
Resources and Links:
- Midjourney:
https://www.midjourney.com/.
- Runway:
https://runwayml.com/.
- ElevenLabs:
https://elevenlabs.io/.
- Veed.io:
https://www.veed.io/.
- YouTube:
"Midjourney AI Tutorial 2025 - Beginner to Advanced Course": https://www.youtube.com/watch?v=877HAXmKwwM.
"The ULTIMATE Beginners Guide to Midjourney in 2025": https://www.youtube.com/watch?v=vUj4VNXXC1c.
- X
Profiles: @timagine_ai (Midjourney coach), @powerfulprompts (prompt
sharing).
- X
Posts: Tips on AI images with Midjourney: https://x.com/WordStream/status/1950224913937170478.
Prompt ideas: https://x.com/ai_lab_daily/status/1950265450199470576.
- Additional:
Udemy zero-code AI projects: Search for "Modern Artificial
Intelligence with Zero Coding" on https://www.udemy.com/.
Assignment: 30-sec clone video (e.g., IT tutorial avatar); experiment with variations.
Common Pitfalls/Gotchas:
- Discord
Overwhelm for Midjourney: As an IT pro, you might skip the bot
commands—prompts fail without "/imagine". (Tip: Watch a 5-min
Discord tutorial; start in a private server.)
- File
Size Limits: Uploading large audio for ElevenLabs cloning hits
free-tier caps quickly. (Tip: Trim samples to 30 seconds; use low-res for
tests.)
- Inconsistent
Outputs: AI media can vary wildly—e.g., clones sounding robotic if
prompts lack detail. (Tip: Refine with specifics like "Natural,
professional tone with pauses.")
- Integration
Glitches: Veed.io exports may not play well with other tools. (Tip:
Export in MP4; test compatibility early.)
Day 3: Automations for IT Workflows (4 hours)
Tailored Twist: Build expense trackers as
"ticket automators" using your IT flow knowledge; extend to
predictive IT tasks like ticket forecasting.
Steps:
- Intro
(45 mins): Triggers and actions overview.
- Setup
(1 hour): Create n8n workflow; compare with Zapier.
- Build
Tracker (1.5 hours): Integrate AI for categorization using Make, Tally,
and Akkio for predictions (e.g., forecast IT downtime).
- Modules
(45 mins): Explore advanced features like loops; pause for testing.
Resources and Links:
- n8n:
https://n8n.io/. Tutorial: https://docs.n8n.io/advanced-ai/intro-tutorial/.
- Zapier:
https://zapier.com/.
Make: https://www.make.com/.
- Tally:
https://tally.so/. Akkio: https://www.akkio.com/.
- YouTube:
"How to Build AI Automations for FREE (Step-by-Step)": https://www.youtube.com/watch?v=Fy1UCBcgF2o.
"N8N FULL COURSE 6 HOURS": https://www.youtube.com/watch?v=2GZ2SNXWK-c.
2025 Update: "How to Build a Local AI Agent With n8n (NO
CODE!)": https://www.youtube.com/watch?v=qqjzohCle48.
- X
Profiles: @n8n_io (official), @LucasAutomation (n8n tips).
- X
Posts: Automation tips: https://x.com/alenbaby_/status/1950153104764060021.
Lead capture tutorial: https://x.com/ogurbych/status/1950302536193495234.
Assignment: Build a second automation (e.g., IT ticket forecasting with Akkio); document with screenshots.
Common Pitfalls/Gotchas:
- Connection
Failures: n8n/Zapier integrations break if API keys expire or
permissions are wrong—common in IT setups. (Tip: Double-check OAuth during
setup; refresh tokens if errors occur.)
- Over-Automating
Early: Trying complex flows before basics leads to loops that crash.
(Tip: Start with 2-3 nodes; test incrementally, like in IT debugging.)
- Data
Privacy Oversights: Automating with Google Sheets shares data—avoid
sensitive IT info. (Tip: Use anonymous test data; enable 2FA on accounts.)
- Free-Tier
Throttling: Zapier limits zap runs; exceed and workflows pause. (Tip:
Monitor usage in the dashboard; opt for Make for more generous limits.)
Day 4: Building AI Agents (4 hours)
Tailored Twist: Agents as "smart
assistants" for IT tasks (e.g., research troubleshooting or predictive
alerts).
Steps:
- Basics
(1 hour): Agents and autonomy concepts.
- Setup
(1 hour): Configure tools in LangChain and AutoGPT.
- Build
(1.5 hours): Research agent with multi-steps using CreateAI,
AgentCloud, and Lindy AI for agentic workflows.
- Refine
(30 mins): Add memory and testing; short break for debugging.
Resources and Links:
- LangChain:
https://www.langchain.com/.
- AutoGPT:
https://agpt.co/. CreateAI:
https://create.ai/.
AgentCloud: https://www.agentcloud.dev/.
Lindy AI: https://www.lindy.ai/.
- YouTube:
"LangChain Agents in 2025 | Full Tutorial for v0.3": https://www.youtube.com/watch?v=Gi7nqB37WEY.
"LangChain Agents: Simply Explained!": https://www.youtube.com/watch?v=Xi9Ui-9qcPw.
- X
Profiles: @LangChainAI (official), @krsnalyst (LangChain tips).
- X
Posts: Agent tutorial: https://x.com/victor_explore/status/1950035554009289086.
Tool-calling agents guide: https://x.com/Marktechpost/status/1948522153030418544.
- Additional:
MIT No Code AI Certificate insights: https://professional.mit.edu/course-catalog/no-code-ai-and-machine-learning-delivering-business-value.
Assignment: Build an agent for a practical IT task (e.g., "Research network error fixes with Lindy AI"); log outputs.
Common Pitfalls/Gotchas:
- Tool
Overload: LangChain's no-code mode still feels
"code-y"—non-coders skip dependencies. (Tip: Use pre-built
templates; focus on AutoGPT for simpler starts.)
- Infinite
Loops: Agents can loop on tasks if prompts aren't bounded, eating API
credits. (Tip: Add "Stop after 5 steps" in instructions; monitor
runs closely.)
- Memory
Mishaps: Forgetting to enable agent memory leads to repetitive
outputs. (Tip: Test with multi-turn queries; relate to IT caching
concepts.)
- API
Rate Limits: CreateAI/AgentCloud hits limits fast in free mode. (Tip:
Space out tests; use local Ollama integration for offline practice.)
Day 5: Advanced Integrations with MCPs (4 hours)
Tailored Twist: MCPs for data fetching, like pulling
IT logs into AI for analysis.
Steps:
- Intro
(1 hour): MCP concepts from docs.
- Build
(1 hour): Personas in Claude and Perplexity.
- Advanced
(1.5 hours): Micro apps and servers with Apify, Kite, VAPI.
- Test
(30 mins): Generate a stylized report; break for verification.
Resources and Links:
- MCP
Docs: https://modelcontextprotocol.io/introduction.
- Claude:
https://claude.ai/.
Perplexity: https://www.perplexity.ai/.
- Apify:
https://apify.com/. Kite:
https://gokite.ai/. VAPI:
https://vapi.ai/.
- YouTube:
"Claude Code MCP: How to Add MCP Servers (Complete Guide)": https://www.youtube.com/watch?v=DfWHX7kszQI.
"Build A Claude MCP Agent That Does Everything!": https://www.youtube.com/watch?v=bATMtzNoap4.
- X
Profiles: @AnthropicAI (official), @claudeai (Claude assistant).
- X
Posts: MCP server tutorial: https://x.com/alexchristou_/status/1949870632524533939.
Node.js MCP tips: https://x.com/cristopher_devs/status/1949083279597932850.
- Additional:
Elements of AI (free basics course): https://www.elementsofai.com/.
Assignment: MCP for generating content from files (e.g., IT log analysis); test personas.
Common Pitfalls/Gotchas:
- Context
Overload: Uploading too much data to Claude crashes sessions—common
for IT folks with big files. (Tip: Chunk data; start with small tests.)
- Misconfigured
Servers: MCP servers fail if ports conflict with IT firewalls. (Tip:
Use default settings; check tool docs for port tweaks.)
- Persona
Inconsistencies: Vague MCP definitions lead to off-topic responses.
(Tip: Define strict roles, like "IT Analyst summarizing logs.")
- Scraping
Limits: Apify hits rate limits on web data. (Tip: Use sparingly; cache
results in Notion for reuse.)
Day 6: Voice Agents and Tech Deep Dive (4 hours)
Tailored Twist: Voice bots for IT support (e.g.,
querying knowledge bases hands-free or alerting on predictions).
Steps:
- Tech
101 (45 mins): APIs and embeddings overview.
- Basics
(1 hour): VAPI setup with advanced prompting; incorporate CodeLlama.
- Build
(1.5 hours): Bot with transcription via Whisper and functions.
- Deploy
(45 mins): Test and refine conversations; take breaks between calls.
Resources and Links:
- VAPI:
https://vapi.ai/.
- Whisper:
https://openai.com/index/whisper/.
CodeLlama: https://ai.meta.com/blog/code-llama-large-language-model-coding/.
- YouTube:
"Build a Voice Agent in 15 Minutes Using VAPI (Easiest
Tutorial)": https://www.youtube.com/watch?v=VNdF3B6-tyQ. "How
to build AI voice agents with Vapi (Full course)": https://www.youtube.com/watch?v=qUQLbPWxbdk.
- X
Profiles: @Vapi_AI (official), @jordan_dearsley (co-founder).
- X
Posts: Voice agent tutorial: https://x.com/tomg_ai/status/1935770536103063637.
No-show reduction tips: https://x.com/shreyas007_raj/status/1928434615133384709.
Assignment: Build a scheduler voice agent (e.g., for IT meetings with predictive alerts); record tests.
Common Pitfalls/Gotchas:
- Audio
Quality Issues: Poor mic input makes Whisper transcription
inaccurate—echoes your IT audio troubleshooting. (Tip: Use a quiet room;
test with clear speech.)
- Prompt
Latency: Overly complex prompts slow VAPI responses. (Tip: Keep system
prompts under 200 words; optimize like IT query optimization.)
- Integration
Gaps: CodeLlama for meta-prompting fails without proper imports (even
no-code). (Tip: Copy from tutorials; fallback to basic prompting.)
- Free-Tier
Call Limits: VAPI caps voice minutes quickly. (Tip: Script short
tests; record offline for practice.)
Day 7: MVP Build and Capstone (4 hours)
Tailored Twist: Build an IT-focused MVP (e.g.,
automated dashboard with predictions).
Steps:
- Ideate
(45 mins): Brainstorm ideas.
- Design
(1 hour): Sketch in Framer.
- Build
Jerry (1 hour): Agent with embeddings using Softr and Tally.
- MVP
and Ship (1.15 hours): Automate features with Bubble and Make; deploy
and demo. Complete self-certification (e.g., Google AI Essentials badge).
Resources and Links:
- Bubble:
https://bubble.io/.
- Softr:
https://www.softr.io/.
Framer: https://www.framer.com/.
Tally: https://tally.so/.
- Make:
https://www.make.com/.
- YouTube:
"Complete Bubble.io Course for Beginners: Build an App in 2025":
https://www.youtube.com/watch?v=6N5Gny4YlbU.
"How to build a Bubble app FAST using AI": https://www.youtube.com/watch?v=mvmUOB0IuFA.
- X
Profiles: @WillLovesNoCode (Bubble expert), @NoCodeNeil (no-code dev).
- X
Posts: Bubble + Zapier tips: https://x.com/skrrr1109/status/1942858716233228724.
Pagination tutorial: https://x.com/CoachingNoCode/status/1937903616112906706.
Assignment: Deploy MVP; prepare a 1-min self-pitch on how it applies to your IT work. Earn a badge via Google AI Essentials.
Common Pitfalls/Gotchas:
- Scope
Creep: Adding too many features mid-build crashes no-code apps like
Bubble. (Tip: Stick to 3 core functions; iterate post-MVP.)
- Deployment
Hiccups: Softr/Framer previews work but live deploys fail on custom
domains. (Tip: Use free subdomains; test links immediately.)
- Embedding
Overkill: Misusing vector embeddings bogs down performance. (Tip: Only
add if needed for search; keep simple for your first MVP.)
- Pitch
Neglect: Forgetting to document makes reflection hard. (Tip: Record a
1-min video; tie back to IT goals.)
Additional Learning Resources
To continue your journey beyond this course, here's an
updated, curated list of resources focused on no-code and low-code AI for IT
professionals, with an added emphasis on code-based tools integrated with
Visual Studio Code (VS Code). These resources extend the no-code theme of the
course while providing a gradual bridge to low-code and code-based AI
development, tailored for IT pros with minimal coding experience but strong
tech intuition. Prioritize based on your goals—start with no-code/low-code for
immediate wins, then explore VS Code tools for advanced projects. All resources
are selected for relevance to 2025 trends (e.g., agentic AI, predictive
analytics) and accessibility (free or freemium tiers).
No-Code Tools (2025 Recommendations)
These build on course tools for IT applications like
predictive analytics, automation, and app building. Free tiers available; focus
on drag-and-drop interfaces.
- Akkio:
No-code ML for predictions (e.g., IT ticket forecasting): https://www.akkio.com/.
- Lindy
AI: Agentic workflows for automations (e.g., IT alerts): https://www.lindy.ai/.
- Knack:
No-code AI/ML for databases and apps (e.g., IT inventory management): https://knack.com/.
- Synthesia:
AI video generation for IT training content: https://www.synthesia.io/.
- DhiWise:
No-code AI app builders for rapid prototyping: https://www.dhiwise.com/.
Low-Code Tools
These offer visual interfaces with minimal coding, ideal for
IT pros transitioning from no-code to light scripting, often compatible with VS
Code for configuration.
- AppGyver:
Low-code platform for building apps with AI integrations (e.g., IT
dashboards): https://www.appgyver.com/.
- OutSystems:
Low-code for enterprise IT apps with AI (e.g., workflow automation): https://www.outsystems.com/.
- Mendix:
Low-code for rapid app development, supports AI plugins: https://www.mendix.com/.
- Microsoft
Power Automate: Low-code automation for IT tasks (e.g., ticket
routing): https://powerautomate.microsoft.com/.
Code-Based Tools (Integrated with VS Code)
These are beginner-friendly for IT pros ready to explore
coding, leveraging VS Code as a lightweight IDE. VS Code extensions simplify AI
development.
- Visual
Studio Code (VS Code): Free, open-source IDE for AI scripting and tool
integration: https://code.visualstudio.com/.
- Why
Use? VS Code supports Python, JavaScript, and no-code/low-code
extensions, making it ideal for IT pros experimenting with AI libraries.
- Setup
Tip: Install extensions like Python, Jupyter, and GitHub Copilot for
AI assistance.
- Hugging
Face Transformers: Open-source AI library for LLMs, usable in VS Code
with Python: https://huggingface.co/docs/transformers/index.
- VS
Code Integration: Use the Hugging Face extension (search in VS Code
marketplace) for model management.
- TensorFlow.js:
JavaScript-based ML library for browser-based AI, runs in VS Code: https://www.tensorflow.org/js.
- VS
Code Integration: Use JavaScript extensions and Live Server for
testing.
- PyTorch:
Open-source ML framework, beginner-friendly with VS Code Python support: https://pytorch.org/.
- VS
Code Integration: Install PyTorch via pip in VS Code’s terminal; use
Jupyter notebooks for experiments.
- LangChain.js:
JavaScript version of LangChain for agentic AI, usable in VS Code: https://js.langchain.com/.
- VS
Code Integration: Use Node.js extension for scripting; pair with
LangChain templates.
- Ollama
Extension for VS Code: Run local models directly in VS Code: https://marketplace.visualstudio.com/items?itemName=ollama.ollama.
- Why
Use? Extends course’s Ollama usage with a familiar IDE interface.
Free/Open-Source Courses
These are beginner-friendly, no-code/low-code focused, with
certificates where possible. Some include VS Code for light coding.
- Elements
of AI: Free intro to AI basics (no-code): https://www.elementsofai.com/.
- AI
for Everyone by Andrew Ng (Coursera): Non-technical overview: https://www.coursera.org/learn/ai-for-everyone.
- Introduction
to AI by IBM: Free on Cognitive Class: https://cognitiveclass.ai/courses/ai-for-everyone.
- MyGreatLearning
Free AI Courses: Machine learning and more: https://www.mygreatlearning.com/ai/free-courses.
- Hugging
Face Learn: Open-source AI/ML tutorials, some using VS Code: https://huggingface.co/learn.
- fast.ai:
Practical deep learning (no-code friendly, supports VS Code): https://course.fast.ai/.
- MIT
OpenCourseWare AI Courses: Beginner-friendly, e.g., Introduction to
Machine Learning (6.036): https://ocw.mit.edu/courses/6-036-introduction-to-machine-learning-fall-2022/;
Introduction to Deep Learning (6.S191, includes VS Code labs): https://ocw.mit.edu/courses/6-s191-introduction-to-deep-learning-january-iap-2023/.
- edX
AI Courses: Free from universities (e.g., AI Fundamentals): https://www.edx.org/learn/artificial-intelligence.
- Microsoft
Learn AI Fundamentals: Low-code AI with Power Automate, VS Code
optional: https://learn.microsoft.com/en-us/training/paths/get-started-ai-fundamentals/.
YouTube Videos and Channels
Visual, tutorial-based learning for no-code, low-code, and
VS Code-integrated AI. Subscribe for ongoing updates.
- Channels:
- freeCodeCamp:
Comprehensive no-code/low-code AI tutorials, some with VS Code: https://www.youtube.com/c/Freecodecamp.
- NoCodeDevs:
No-code app building with AI: https://www.youtube.com/c/NoCodeDevs.
- WeAreNoCode:
Beginner no-code AI projects: https://www.youtube.com/c/WeAreNoCode.
- Two
Minute Papers: Quick AI research summaries: https://www.youtube.com/c/K%C3%A1rolyZsolnai.
- Sentdex:
Practical AI, including VS Code Python tutorials: https://www.youtube.com/c/sentdex.
- Analytics
Vidhya: AI for beginners, some low-code: https://www.youtube.com/c/AnalyticsVidhya.
- Tech
With Tim: Python and VS Code AI tutorials: https://www.youtube.com/c/TechWithTim.
- Specific
Videos:
- “10
FREE AI Courses for Absolute Beginners in 2025”: https://www.youtube.com/watch?v=pIo4mbGGyhE.
- “Right
Way To Learn AI In 2025”: https://www.youtube.com/watch?v=TYEqenKrbaM.
- “5
Best APP Builders For Beginners In 2025 (No-Code + AI)”: https://www.youtube.com/watch?v=EXajQaw0tWI.
- “Top
5 YouTube Channels to Learn AI in 2025”: https://www.youtube.com/watch?v=FpK09bYIkIk.
- “VS
Code for Beginners – Build AI Models with Python (2025)”: Search for
recent equivalents on YouTube.
- “Hugging
Face Transformers in VS Code Tutorial”: Search for 2025 tutorials on
YouTube.
Advanced Resources
For next-level learning once comfortable with
no-code/low-code, including VS Code workflows.
- NoCode
Founders Community: Forums and tools for no-code/low-code: https://nocodefounders.com/.
- Buildfire
2025 No-Code AI Guide: In-depth tool reviews: https://buildfire.com/no-code-ai-tools/.
- Airtable
No-Code AI Tools Guide: https://www.airtable.com/articles/no-code-ai-tools.
- Pragmatic
Coders AI Tools List: Includes VS Code-compatible tools: https://www.pragmaticcoders.com/resources/ai-developer-tools.
- GitHub
Copilot: AI-powered coding assistant in VS Code: https://github.com/features/copilot.
- Jupyter
Notebooks in VS Code: Interactive AI development: https://code.visualstudio.com/docs/datascience/jupyter-notebooks.
- Reddit
r/nocode: Community for no-code/low-code AI: https://www.reddit.com/r/nocode/.
- Reddit
r/MachineLearning: Beginner AI discussions, including VS Code tips: https://www.reddit.com/r/MachineLearning/.
Learning Path Suggestions
- No-Code
First: Start with Elements of AI and Akkio for immediate IT
applications.
- Low-Code
Transition: Try AppGyver or Power Automate, using visual scripting to
ease into coding concepts.
- VS
Code Exploration: Install VS Code with Python/Jupyter extensions;
follow Sentdex or fast.ai tutorials for light scripting (e.g., simple LLM
queries).
- Community
Engagement: Share projects on NoCode Founders or Reddit; ask for
feedback on X.
- Certification:
Complete Google AI Essentials or MIT’s 6.S191 for a badge to boost your IT
resume.
These resources are current for July 2025, emphasizing
no-code/low-code with a clear path to VS Code for IT pros ready to experiment.