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Ai For Beginners – Learn Chatgpt, Claude, Gemini (No Code)
Published 9/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.66 GB | Duration: 2h 53m​

Learn AI tools and skills: prompts, context, fact checking, productivity, and creativity using ChatGPT, Claude and more!

What you’ll learn

Distinguish between predictive AI and generative AI, and explain how large language models generate text one token at a time.

Set up and use free accounts with ChatGPT, Claude, Microsoft Copilot, and Google Gemini, and compare how each works.

Write effective prompts and apply context engineering techniques to guide AI behavior.

Use AI for real tasks such as drafting emails, summarizing articles, researching topics, brainstorming, and planning.

Evaluate AI output critically by spotting hallucinations, fact-checking answers, and applying ethical use.

Boost productivity, creativity, and learning with AI while developing durable skills such as communication and collaboration.

Requirements

No programming experience needed – this course is designed for non-coders

A computer or device with internet access to sign up for free AI tools.

Curiosity and openness to experimenting with new technology.

Description

This beginner-friendly course will help you build real confidence with artificial intelligence by showing you how to use the most popular AI tools in practical, everyday ways.You will start with the foundations of AI, learning the difference between predictive AI and generative AI, and seeing how large language models produce text one token at a time. You will also discover why context matters and how providing better context improves accuracy and usefulness.From there you will go hands-on. You will set up free accounts for ChatGPT, Claude, Microsoft Copilot, and Google Gemini with AI Mode. ChatGPT will be the main platform for practice, but you will also explore how other tools compare so you can decide which best fits your work.You will learn the essentials of prompt engineering and context engineering. You will practice writing prompts for real tasks such as drafting emails, summarizing articles, planning projects, and brainstorming ideas. You will also learn how retrieval-augmented generation (RAG) helps AI provide more reliable answers.Throughout the course, you will see how AI is embedded in search engines, writing software, and productivity platforms. You will explore advanced features like custom GPTs, projects, operators, and agents at an introductory level so you know what is possible.You will apply AI to real-world workflows, boosting productivity, doing deeper research, writing more efficiently, and generating creative output. You will also learn how to check AI responses for accuracy, how to fact-check answers with tools like Gemini or Perplexity, and how to use AI responsibly and ethically.By the end of this course, you will have a strong foundation in AI literacy and the confidence to integrate AI tools into your daily life and work. You will also know the next steps you can take, including more advanced courses on prompt engineering, accuracy and hallucination mitigation, no-code agents, and AI-powered communication and collaboration.

Overview

Section 1: Introduction and Foundations of AI

Lecture 1 Course Introduction

Lecture 2 Why AI Skills Matter Now More than Ever

Section 2: Hands On with AI Tools

Lecture 3 Getting Started with ChatGPT

Lecture 4 What are Tokens and How do they Work with AI?

Lecture 5 Signing Up for a Free ChatGPT Account

Lecture 6 Signing Up for a Free Claude Account and Testing Web Search

Lecture 7 Google AI Mode and Gemini

Lecture 8 Signing Up for a Free Gemini Account and Generating Game Code

Lecture 9 Signing Up for a Free Microsoft Copilot Account

Lecture 10 Signing Up for a Free Perplexity Account for AI Search

Section 3: AI in Productivity Tools

Lecture 11 Copilot in Microsoft Word

Lecture 12 Copilot in Microsoft Excel

Lecture 13 Copilot in Microsoft PowerPoint

Lecture 14 Gemini in Google Docs

Lecture 15 Gemini in Google Sheets

Lecture 16 Agentforce in Salesforce

Lecture 17 Free AI Playgrounds in Salesforce

Section 4: Using AI in Real Workflows – Creating with AI

Lecture 18 Custom GPTs

Lecture 19 Create a Custom GPT to Improve Your Soft Skills – AI-Powered Communication

Lecture 20 Make a Project to Improve Your Prompt Engineering and Context Engineering Skills

Lecture 21 Creating and Publishing AI Artifacts with Claude

Lecture 22 Using Study and Learn Mode to Understand RAG

Lecture 23 Generating Images with AI

Lecture 24 Generating Videos with Sora

Lecture 25 ChatGPT Agents

Absolute beginners curious about how AI works and how it fits into everyday life.,Professionals who want to understand and use AI features already built into search, productivity, and cloud tools.,Students, creatives, entrepreneurs, and career changers seeking practical AI skills without coding.,Anyone who wants to use AI for tasks like writing, research, brainstorming, or planning, while understanding its limits and risks.,Lifelong learners who want a clear foundation before exploring advanced AI topics such as agents, automation, or hallucination mitigation.

AI Engineering with Go
.MP4, AVC, 1920×1080, 30 fps | English, AAC, 2 Ch | 9h 28m | 2.26 GB
Instructor: Preslav Mihaylov​

Who said AI applications had to be built in Python?

In this course, you’ll learn how to practically integrate AI into real applications with Go – starting from basic LLM usage and gradually building toward dynamic, intelligent, autonomous AI agents.

We focus on shipping real projects every module; building your portfolio as well as your skills.

? Build 3+ complete AI projects and deploy them.
Master LLM APIs (OpenAI, Claude) with Go integration
Implement vector databases, embeddings, and semantic search
Build function calling and structured LLM interactions
Deploy AI applications to production with proper architecture
Create turn-based AI systems and intelligent content processing

Homepage

Last updated 2/2026 Created by LLM Engineer,Ed Donner MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 122 Lectures ( 18h 38m ) | Size: 13.4 GB​

Deploy AI to AWS, GCP, Azure, Vercel with MLOps, Bedrock, SageMaker, RAG, Agents, MCP: scalable, secure and observable..

What you’ll learn
Deploy SaaS LLM apps to production on Vercel, AWS, Azure, and GCP, using Clerk
Design cloud architectures with Lambda, S3, CloudFront, SQS, Route 53, App Runner and API Gateway
Integrate with Amazon Bedrock and SageMaker, and build with GPT-5, Claude 4, OSS, AWS Nova and HuggingFace
Rollout to Dev, Test and Prod automatically with Terraform and ship continuously via GitHub Actions
Deliver enterprise-grade AI solutions that are scalable, secure, monitored, explainable, observable, and controlled with guardrails.
Create Multi-Agent systems and Agentic Loops with Amazon Bedrock AgentCore and Stands Agents

Requirements
While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience!
The course runs best if you have a small budget for APIs and Cloud Providers of a few dollars. But we monitor expenses at every point, and it’s always a personal choice.

Description
This is the course that more of my students have asked for than any other course – put together.
One student called it
"The missing course in AI."
This course is for
Entrepreneurs
Enterprise engineers
.and everyone in between.
It’s not just about RAG – although we’ll work with RAG.
It’s not just about Agents – but there will be many Agents.
It’s not just about MCP – but yes, there will be plenty of MCP too.
This course is about
RAG, Agents, MCP, and so much more. deployed to production.
Live.
Enterprise-grade.
Scalable, resilient, secure, monitored – and explained.
You’ll ship real-world, production-grade AI with LLMs and agents across Vercel, AWS, GCP, and Azure, going deepest on AWS.
Across four weeks you’ll take four products to production
Week 1
You’ll launch a Next.js SaaS product on Vercel and AWS,
with AWS App Runner and Clerk for user management and subscriptions.
Week 2
You’ll become an AI platform engineer on AWS,
deploying serverless infrastructure using
Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53
Write Infrastructure as Code with Terraform
Set up CI/CD pipelines with GitHub Actions
– for hands-free deployments and one-click promotions.
Week 3
You’ll gain broad industry skills for GenAI in production
Deploy a Cyber Security Analyst agent with MCP to Azure & GCP
Stand up SageMaker inference
Build data ingest to S3 vectors
Deploy a Researcher Agent using OpenAI OSS models on Bedrock + MCP
Week 4
You’ll go fully agentic in production
Architect multi-agent systems with
Aurora Serverless, Lambda, SQS
JWT-authenticated CloudFront frontends
LangFuse observability
Overview of AWS Agent Core
By the end, you’ll know how to
Pick the right architecture
Lock down security
Monitor costs
Deliver continuous updates
Everything needed to run scalable, reliable AI apps in production.
Course sections (Weeks & Projects)
Week 1
SaaS App Live in Production with Vercel, AWS, Next.js, Clerk, App Runner
Project: SaaS Healthcare App
Week 2
AI Platform Engineering on AWS with Bedrock, Lambda, API Gateway, Terraform, CI/CD
Project: Digital Twin Mk II
Week 3
Gen AI in Production with Azure, GCP, AWS SageMaker, S3 Vectors, MCP
Project: Cybersecurity Analyst
Week 4
Agentic AI in Production: Build and deploy a Multi-Agent System on AWS (Aurora Serverless, Lambda, SQS),
with LangFuse and Bedrock AgentCore
Capstone Project: SaaS Financial Planner

Who this course is for
Well, perhaps I’m biased, but I’d say: anyone and everyone! If you’re fascinated in the potential of Agents and hungry to have the skills to create powerful Agentic AI – then you’ve come to the right place. While it’s most suited to those with programming experience, I’ve designed the course to work for all backgrounds.

Welcome to – Check it Every Days
If you have any troubles with downloading, PM me

Happy Learning!!

AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents
2026-02-04
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 24.53 GB | Duration: 33h 24m​

Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, LoRA and AI Agents.

What you’ll learn
Project 1: Make AI-powered brochure generator that scrapes and navigates company websites intelligently.
Project 2: Build Multi-modal customer support agent for an airline with UI and function-calling.
Project 3: Develop Tool that creates meeting minutes and action items from audio using both open- and closed-source models.
Project 4: Make AI that converts Python code to optimized C++, boosting performance by 60,000x!
Project 5: Build AI knowledge-worker using RAG to become an expert on all company-related matters.
Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.
Project 7: Capstone Part B – Execute Fine-tuned open-source model to compete with Frontier in price prediction.
Project 8: Capstone Part C – Build Autonomous multi agent system collaborating with models to spot deals and notify you of special bargains.
Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows
Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task

Requirements
Familiarity with Python. This course will not cover Python basics and is completed in Python.
A PC with an internet connection is required. Either Mac (Linux) or Windows.
We recommend that you allocate around $5 for API costs to work with frontier models. However, you can complete the course using open-source models if you prefer.

Description
Mastering Generative AI and LLMs: An 8-Week Hands-On JourneyAccelerate your career in AI with practical, real-world projects led by industry veteran Ed Donner. Build advanced Generative AI products, experiment with over 20 groundbreaking models, and master state-of-the-art techniques like RAG, QLoRA, and Agents.What you’ll learn Build advanced Generative AI products using cutting-edge models and frameworks. Experiment with over 20 groundbreaking AI models, including Frontier and Open-Source models. Develop proficiency with platforms like HuggingFace, LangChain, and Gradio. Implement state-of-the-art techniques such as RAG (Retrieval-Augmented Generation), QLoRA fine-tuning, and Agents. Create real-world AI applications, including: A multi-modal customer support assistant that interacts with text, sound, and images. An AI knowledge worker that can answer any question about a company based on its shared drive. An AI programmer that optimizes software, achieving performance improvements of over 60,000 times. An ecommerce application that accurately predicts prices of unseen products. Transition from inference to training, fine-tuning both Frontier and Open-Source models. Deploy AI products to production with polished user interfaces and advanced capabilities. Level up your AI and LLM engineering skills to be at the forefront of the industry.About the InstructorI’m Ed Donner, an entrepreneur and leader in AI and technology with over 20 years of experience. I’ve co-founded and sold my own AI startup, started a second one, and led teams in top-tier financial institutions and startups around the world. I’m passionate about bringing others into this exciting field and helping them become experts at the forefront of the industry.Projectsroject 1: AI-powered brochure generator that scrapes and navigates company websites intelligently.Project 2: Multi-modal customer support agent for an airline with UI and function-calling.Project 3: Tool that creates meeting minutes and action items from audio using both open- and closed-source models.Project 4: AI that converts Python code to optimized C++, boosting performance by 60,000x!Project 5: AI knowledge-worker using RAG to become an expert on all company-related matters.Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.Project 7: Capstone Part B – Fine-tuned open-source model to compete with Frontier in price prediction.Project 8: Capstone Part C – Autonomous agent system collaborating with models to spot deals and notify you of special bargains.Why This Course? Hands-On Learning: The best way to learn is by doing. You’ll engage in practical exercises, building real-world AI applications that deliver stunning results. Cutting-Edge Techniques: Stay ahead of the curve by learning the latest frameworks and techniques, including RAG, QLoRA, and Agents. Accessible Content: Designed for learners at all levels. Step-by-step instructions, practical exercises, cheat sheets, and plenty of resources are provided. No Advanced Math Required: The course focuses on practical application. No calculus or linear algebra is needed to master LLM engineering.Course StructureWeek 1: Foundations and First Projects Dive into the fundamentals of Transformers. Experiment with six leading Frontier Models. Build your first business Gen AI product that scrapes the web, makes decisions, and creates formatted sales brochures.Week 2: Frontier APIs and Customer Service Chatbots Explore Frontier APIs and interact with three leading models. Develop a customer service chatbot with a sharp UI that can interact with text, images, audio, and utilize tools or agents.Week 3: Embracing Open-Source Models Discover the world of Open-Source models using HuggingFace. Tackle 10 common Gen AI use cases, from translation to image generation. Build a product to generate meeting minutes and action items from recordings.Week 4: LLM Selection and Code Generation Understand the differences between LLMs and how to select the best one for your business tasks. Use LLMs to generate code and build a product that translates code from Python to C++, achieving performance improvements of over 60,000 times.Week 5: Retrieval-Augmented Generation (RAG) Master RAG to improve the accuracy of your solutions. Become proficient with vector embeddings and explore vectors in popular open-source vector datastores. Build a full business solution similar to real products on the market today.Week 6: Transitioning to Training Move from inference to training. Fine-tune a Frontier model to solve a real business problem. Build your own specialized model, marking a significant milestone in your AI journey.Week 7: Advanced Training Techniques Dive into advanced training techniques like QLoRA fine-tuning. Train an open-source model to outperform Frontier models for specific tasks. Tackle challenging projects that push your skills to the next level.Week 8: Deployment and Finalization Deploy your commercial product to production with a polished UI. Enhance capabilities using Agents. Deliver your first productionized, agentized, fine-tuned LLM model. Celebrate your mastery of AI and LLM engineering, ready for a new phase in your career.

Who this course is for:
Aspiring AI engineers and data scientists eager to break into the field of Generative AI and LLMs., Professionals looking to upskill and stay competitive in the rapidly evolving AI landscape., Developers interested in building advanced AI applications with practical, hands-on experience., Individuals seeking a career transition or aiming to enhance productivity through LLM-built frameworks.

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AI Engineer Agentic Track: The Complete Agent & MCP Course
2025-11-03
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 14.11 GB | Duration: 16h 48m​

Master AI Agents in 30 days: build 8 real-world projects with OpenAI Agents SDK, CrewAI, LangGraph, AutoGen and MCP.

What you’ll learn
Project 1: Career Digital Twin. Build and deploy your own Agent to represent you to potential future employers.
Project 2: SDR Agent. An instant business application: create Sales Representatives that craft and send professional emails .
Project 3: Deep Research. Make your own version of the essential Agentic use case: a team of Agents that carry out extensive research on any topic you choose.
Project 4: Build a Stock Picker Agent in minutes with CrewAI-automate your search for investment gems!
Project 5: Deploy your own 4-Agent Engineering Team-manage, build, and test software apps with CrewAI and Coder Agents in Docker!
Project 6: Build your own version of OpenAI’s Operator Agent-your Sidekick works with you inside your browser via LangGraph!
Project 7: Agent Creator-an Agent that builds and launches new Agents using AutoGen, unlocking endless AI possibilities!
Project 8: Capstone-build a Trading Floor with 4 Agents making autonomous trades, powered by 6 MCP servers and 44 tools!

Requirements
While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience!
The course runs best if you have a small budget for APIs, but it’s totally your choice. You can complete the entire course with no API spend. If you do wish to use frontier models, the typical spend would be under $5. You can choose to access more capabilities if you’re comfortable spending a little more.

Description
2025 is the year that Agents enter the workforce. This is nothing short of a watershed moment for Artificial Intelligence. It has never been more important to be an expert with Agentic AI. And that is precisely the goal of this course: to equip you with the skills and expertise to design, build and deploy Autonomous AI Agents, opening up new career and commercial opportunities.This is an intensive 6-week program to master Agentic AI. We start by building foundational expertise, connecting LLMs using proven design patterns. Then, each week, we upskill with new frameworks: OpenAI Agents SDK, CrewAI, LangGraph and Autogen. The course culminates with a full week on the remarkable opportunities opened up by MCP.Above all, this is a hands-on course. I’m a big believer that the best way to learn is by DOING. So please prepare to roll up your sleeves! We’ll build 8 real-world projects; some are astonishing, some are intriguing, and some are quite surreal. But one thing’s for sure: all are powerful demonstrations of Agentic AI’s potential to utterly transform the business landscape.So come join me on this comprehensive 6-week journey. By the end, you will have mastered Agentic AI. You will have expertise in all the major frameworks. You’ll be well-versed in the strengths and traps of Agentic AI. You’ll confidently unleash Autonomous Agents to solve real-world commercial problems. And along the way, you’ll have had a whole lot of fun with the astounding, groundbreaking technology that is Agentic AI.

Who this course is for:
Well, perhaps I’m biased, but I’d say: anyone and everyone! If you’re fascinated in the potential of Agents and hungry to have the skills to create powerful Agentic AI – then you’ve come to the right place. While it’s most suited to those with programming experience, I’ve designed the course to work for all backgrounds.

For More Courses Visit & Bookmark Your Preferred Language Blog
From Here:——–