NulledCodeSolutions.online

AI Security, Governance & Compliance
Published 2/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 46m | Size: 1.94 GB​

Design, deploy, and govern secure, compliant AI systems used in real enterprises

What you’ll learn
Design secure and compliant AI systems by identifying AI-specific risks, threat models, and failure modes across the full AI lifecycle.
Apply AI governance frameworks in real enterprise environments, including defining ownership, approval workflows, documentation standards, and operating models
Secure Generative AI and LLM-based applications using guardrails, prompt isolation, retrieval validation, and human-in-the-loop controls.
Prepare AI systems for audits and regulatory review by producing audit-ready evidence, traceability, and documentation aligned with global regulations.
Manage privacy, consent, and data protection risks in AI systems, including PII handling, data retention, and cross-border data considerations.
Respond effectively to AI incidents and failures, including hallucinations, abuse, security breaches, and autonomous agent failures.
Evaluate and mitigate risks in autonomous and agentic AI systems, including kill-switch design, rollback strategies, and operational safeguards.
Communicate AI risk, governance, and compliance decisions confidently to technical teams, auditors, regulators, and leadership.

Requirements
A basic understanding of AI or machine learning concepts (such as models, prompts, or data)
Some familiarity with software systems, products, or operations in a professional environment
An interest in deploying AI in real-world or enterprise settings

Description
"This course contains the use of artificial intelligence"

AI systems are no longer experimental tools – they are production systems making real decisions at scale. As organizations deploy Generative AI, LLMs, RAG pipelines, and autonomous agents, the biggest challenges are no longer accuracy or performance, but security, governance, privacy, and regulatory compliance.

This course is a practical, enterprise-focused guide to building secure, compliant, and trustworthy AI systems that can operate safely in real-world environments. You’ll learn why AI security is fundamentally different from traditional application security, how AI systems fail in production, and what organizations must do to manage risk, accountability, and oversight across the AI lifecycle.

Rather than abstract ethics or policy theory, this course focuses on how AI is actually governed inside enterprises today. You’ll understand AI threat modeling, prompt injection and data leakage risks, guardrails and safety layers, and how to design human-in-the-loop controls that scale. The course also demystifies AI governance frameworks, showing how teams define ownership, approvals, documentation, and decision rights without slowing innovation.

You’ll gain a clear understanding of the global AI regulatory landscape, including EU AI Act principles, US governance approaches, and industry standards, and learn how these translate into real controls, audits, and evidence. Privacy, consent, data retention, and cross-border data handling are addressed from a practical, audit-ready perspective – not legal jargon.

Through realistic enterprise case studies and hands-on design exercises, you’ll learn how to secure internal AI assistants, customer-facing GenAI applications, and autonomous operational agents, including how to handle failures, design kill-switches, and implement safe rollback strategies.

By the end of this course, you’ll be able to design AI systems that pass audits, survive incidents, and earn trust – and confidently speak the language of AI security, governance, and compliance in technical, product, and leadership settings.

Who this course is for
AI Engineers, ML Engineers, and GenAI Developers who want to understand the security, governance, and risk implications of production AI systems.
Security, Risk, and GRC professionals who need practical insight into how AI systems introduce new threat models and compliance challenges.
AI Product Managers and Technical Product Owners responsible for launching AI-powered features safely and responsibly.
Platform, MLOps, and Infrastructure Engineers supporting AI systems in production.
Architects and Technical Leaders designing enterprise AI platforms and operating models.
Professionals working with LLMs, RAG systems, or autonomous agents who want to avoid common failures and audit issues

Ai For Coding: Master Cursor Ai For 20X Faster Fullstack App
Published 10/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.44 GB | Duration: 3h 21m​

Master AI for coding with Cursor AI to build fullstack, MERN stack web apps faster,

What you’ll learn

How to use Cursor AI to build a fullstack application from scratch

Learn to build Full stack Ebook Store with Payment Integration

Integrating frontend and backend components seamlessly with minimal manual effort.

Master Cursor AI for coding 100X Faster

Master how to use Cursor AI Effectively

Master the technique on how to build Complex Project using Cursor A1

Requirements

No prior knowledge needed

Description

In this course, you’ll master the power of AI for coding using Cursor AI and GenAI, enabling you to build fullstack MERN stack web applications faster and more efficiently than ever before. As AI becomes an integral part of development, this course will guide you through the practical application of AI in coding, helping you automate repetitive tasks, optimize code, and focus more on high-level logic and design.Throughout the course, you’ll dive deep into the fullstack development process, utilizing Cursor AI to generate frontend and backend code, integrate databases, and build responsive web applications. We’ll explore how AI-driven tools can assist in generating, debugging, and optimizing code to drastically reduce development time. With a focus on the MERN stack (MongoDB, Express, React, and Node.js), you’ll learn how to leverage AI to streamline the development process across both the frontend and backend.Key areas covered include AI-powered coding, fullstack application development, and automating complex tasks such as API integration and database management. By the end of the course, you will have the skills to build fullstack web apps faster, with enhanced productivity, all while gaining a deeper understanding of how AI can revolutionize the way we approach coding and development in the modern web landscape. This course is ideal for developers at all levels who are ready to embrace the future of coding with AI!

Overview

Section 1: MASTERING CURSOR AI FOR CODING

Lecture 1 Projects Demo

Lecture 2 What is Cursor AI

Lecture 3 Installing Cursor AI

Lecture 4 Cursor AI In The Terminal

Lecture 5 Cursor Inline Editing

Lecture 6 Cursor Chat Feature

Lecture 7 Web, Files, Folder mentions

Lecture 8 Understanding Codebase feature

Lecture 9 The Doc mention

Lecture 10 Image to Code

Lecture 11 Introducing Cursor NotePad

Section 2: PROJECT: BUILD JAVASCRIPT EXPENSES TRACKER

Lecture 12 JS-Expenses Project

Section 3: PROJECT: BUILD AI CONTENT GENERATOR WITH GEMINI AI

Lecture 13 Build AI Content Generator with Cursor

Section 4: PROJECT: BUILD MERN AUTHENTICATION PROJECT UNDER 20 MINUTES

Lecture 14 MERN Auth Project Using Cursor AI

Section 5: PROJECT: BUILD AI CONTENT DETECTOR PROJECT USING RAPID API

Lecture 15 AI Content Detector

Section 6: PROJECT: FULLS TACK EBOOK STORE PROJECT

Lecture 16 Project Planing

Lecture 17 Creating Folders With One Command

Lecture 18 User Model

Lecture 19 Implementing Users Controllers

Lecture 20 Auth Routes and Server setup

Lecture 21 Testing Endpoints and Fixed Auth Middleware

Lecture 22 Change Password Endpoint

Lecture 23 Admin Controllers, Book and Transaction Models

Lecture 24 Book Controllers

Lecture 25 PdF and image Upload For Book creation

Lecture 26 Fetch All & Update Book

Lecture 27 Payment Integration

Lecture 28 Forntend Authentication

Lecture 29 Change Password

Lecture 30 Fetch All and Book Details

Beginner developers with basic coding skills looking to build fullstack apps using AI.,Intermediate developers wanting to automate coding tasks with Cursor AI.,Advanced developers seeking to streamline their workflow with AI-driven tools.,Tech enthusiasts eager to explore AI-assisted development and its potential in web apps.

AI for Business Analysts
Published 9/2025
Duration: 3h 56m | .MP4 1920×1080 30 fps(r) | AAC, 44100 Hz, 2ch | 4.47 GB
Genre: eLearning | Language: English​

Craft your Business Analysis deliverables using AI-Driven Strategies with ChatGPT

What you’ll learn

• Master AI/ChatGPT Integration: Acquire the skills to seamlessly integrate AI/ChatGPT into the Business Analysis workflow, from ideation to strategic planning.
• Craft Comprehensive Deliverables including Product Vision Boards, Business Model Canvases, Kano Models, and Porter’s Five Forces with the assistance of AI.
• Refine AI-Generated Deliverables: Hone the art of critically reviewing and refining AI-generated deliverables, ensuring they align with strategic objectives.
• Learn to write effective prompts and refine the results for a powerful feature prioritization using the Kano Model.
• Apply the knowledge gained throughout the course in a hands-on capstone project, creating a personalized Business Analysis Portfolio using ChatGPT.

Requirements

• The are no specific requirements that one has to fulfill in order to sign up for the course.
• No previous AI/ChatGPT knowledge or experience needed.

Description
Accelerate the time to market and quality of your Business Analysis deliverableswith our course, "CraftBusiness AnalysisDeliverables using ChatGPT."

Unlock the Potential of AI in Business Analysis: A Comprehensive Journey

Welcome to a transformative learning experience that goes beyond the basics. In "CraftingBusiness AnalysisDeliverables using ChatGPT," we delve into the intricate intersection of artificial intelligence and Business Analysis, providing you with practical insights and hands-on skills to accelerate the time to market and quality of your deliverables.

1.ChatGPT Account Creation

Account Creation:Understand the process of setting up your ChatGPT account, ensuring you’re ready to harness the power of this revolutionary language model.

2. Capstone Project: Create Craft your Business Analysis deliverables

Interactive Learning:Engage in hands-on exercises that bridge theory and practical application, solidifying your understanding of ChatGPT application in Business Analysis.

Refining Sample Deliverablesractice refining sample deliverables generated by ChatGPT, honing your skills for real-world scenarios.

Apply Knowledge in Real Time:Implement everything you are learning in a comprehensive capstone project.

Craft Your draft Business Analysis deliverables Portfolio in less than a monthevelop your own Product Vision Boards, Business Model Canvases, Kano Models and Porter Five Force Model using ChatGPT while attending the course.

3.ChatGPT Prompting Framework: Crafting the Foundation

General ChatGPT Prompt Structure Template custom developed for Business Analysisevelop a solid understanding of the fundamental structure of reuseable and extensible ChatGPT Prompt Structure Template custom developed forBusiness Analysisthat drives effective prompts forBusiness Analysisdeliverables in ChatGPT.

Sample Prompt Structures from Business Analysis:Explore real-world examples, gaining insights into crafting prompts for various Business AnalysisandProduct Management Frameworks and models.

**4.Product Vision Board: Unleashing Creativity with ChatGPT

Utilizing Sample Prompt Structure:Witness the practical application of the sample prompt structure to generate a compelling draft version of Product Vision Board.

Review and Refinement:Learn the art of critical review and refinement, ensuring your vision board aligns with strategic goals.

**5.Business Model Canvas: Streamlining Strategy Generation

Writing ChatGPT Prompt for Business Model Canvasevelop effective prompts for generating a detailed Business Model Canvas using ChatGPT.

Generating and Reviewing:Witness the power of AI in action as you generate and review a sample Business Model Canvas, refining it for strategic clarity.

**6.Kano Model: Elevating Product Features with AI Assistance

Crafting Kano Model Prompts:Learn to write prompts that guide ChatGPT in generating a sample Kano Model, prioritizing product features effectively.

Critical Review:Understand the importance of critical review and refinement in optimizing the results from ChatGPT.

**7.Porter’s Five Forces Model: Advanced Strategic Analysis

Writing ChatGPT Prompt for Porter’s Five Forces Modelive into the complexities of strategic analysis with effective prompts for generating a Porter’s Five Forces Model.

**8.Who Can Benefit from this Course?

Business Analysts, Product Managers and Owners:Enhance your strategic thinking, streamline and craft yourBusiness Analysisdeliverables with AI assistance.

Entrepreneurs:Leverage ChatGPT to refine your product strategies and create compelling business models.

Aspiring Product Professionals:Gain a competitive edge by integrating AI seamlessly into your skill set and develop your first draftBusiness AnalysisPortfolio in less than a month to showcase your potential employers.

**9.Why Enroll in this Course?

Practical Skills:Acquire tangible skills that can be immediately applied in yourBusiness Analyst andproduct management roles.

Cutting-Edge Knowledge:Stay ahead in the field by exploring the intersection of AI,Business Analysisand product management.

Hands-On Experience:Engage in real-world exercises, refining your abilities to integrate AI in strategic decision-making.

**10.Join the AI-Powered Future of Business Analysis

Instructor Guidance:Benefit from the expertise of a seasonedBusiness Analysis andProduct Management Coach, guiding you through the nuances of AI integration.

Networking Opportunities:Connect with a community of like-minded professionals, fostering collaboration and knowledge exchange.

Embark on this transformative journey today. Enroll in "ChatGPT for Business Analysts" and redefine the way you approach product strategy, innovation, and deliverable creation in the dynamic landscape of ChatGPT Business Analysis.

About Me: Vipesh Singla, MBA, Agile Product Management Coach

Embark on a journey of transformation with Vipesh Singla, a seasoned Agile Business Analysis and Product Management Coach with an impressive track record. Certified and licensed as a SAFe Agile Coach and SAFe Practice Consultant, I bring a wealth of experience to the table.

Throughout my career, I have played pivotal roles in Agile Transformations and Product Management Assignments for a diverse array of Global 2000 companies. Notably, I’ve collaborated with esteemed clients and employers from prestigious groups such as GAFAM, Big 4, Big Tech, Big Pharma, Fortune 100, and FTSE 100. My versatility shines through various roles, including Product Manager, Product Owner, Scrum Master, and Agile Coach.

Education forms the foundation of my expertise, holding both an MBA and a Bachelor of Engineering degree from one of India’s prestigious institutes. As a certified SAFe SPC/Agile Coach, I bring a proven track record of driving successful Agile transformations.

With a track record that speaks volumes, I am proud to be at the forefront of Agile Product Management coaching. Boasting a remarkable achievement of over 7700 registrations across all my programs, I have had the privilege of influencing and guiding a diverse community of 6,000 unique students.

My digital presence extends globally, reaching enthusiasts and professionals in 139 countries. This widespread outreach has allowed me to connect with a vast audience, transcending language barriers. Our community is not confined to English alone; we thrive in a multilingual environment, with students conversing in 35 languages.

As an Agile Product Management Coach, my commitment is to empower individuals worldwide with the knowledge and skills necessary for success in the dynamic field of product management. Join me on this transformative journey, and let’s navigate the realm of Agile Product Management together.

Who this course is for:

• This course is tailored for Business Analysts, Lead Business Analysts, Senior Business Analysts, and anyone involved in product management seeking to elevate their expertise of using ChatGPT in Product Management lifecycle.
• Anyone involved in Business Analysis who is interested to unlock the power of AI/ChatGPT in reshaping the future of their products.
• Aspiring Business Analyst Professionals: Gain a competitive edge by integrating AI/ChatGPT seamlessly into your skill set and develop your first draft Business Analysis Portfolio in less than a month to showcase your potential employers.

More Info

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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